WO1998006053A1

WO1998006053A1 - System and method for materials process control

Info

Publication number: WO1998006053A1
Application number: PCT/US1997/013553
Authority: WO
Inventors: William S. Anthony; Richard K. Byler
Original assignee: The United States Of America, Represented By The Secretary Of Agriculture
Priority date: 1996-08-01
Filing date: 1997-07-31
Publication date: 1998-02-12
Also published as: AR006065A1; AU715988B2; TR199700739A2; GR1003301B; AU3243697A; TR199700739A3; US5805452A; BR9704249A; GR970100307A

Abstract

System and method for optimizing the processing of materials, particularly the processing of cotton in a cotton gin or a textile mill. Cotton moisture, color, and foreign matter measurements are made with electronic sensors (210, 1016) at three stations. For a gin, a dynamic programming model (1020) uses input information relative to the moisture and trash content, color, lint turnout, staple length, cotton price structure, and energy costs to select and optimum drying and cleaning sequence (1106) for the cotton. The dynamic programming model optimizes cotton producer profits by selecting the amount of gin machinery (1116) necessary to achieve the most beneficial market value while minimizing the machinery used. Automated directional valves (1036) are used to route the cotton through the selected optimum combination of seed cotton cleaners, multi-path driers, and lint cleaners.

Description

SYSTEM AND METHOD FOR MATERIALS PROCESS CONTROL

Background of the Invention Field of the Invention

The present invention relates generally to a system and method for processing materials, particularly agricultural solids such as cotton. More particularly, the present invention relates to a system and method for optimizing the processing of cotton in a cotton gin.

Related Art

Cotton quality after ginning is a function of its initial quality as well as the type and degree of cleaning and drying that it receives during the gin process . The term "cotton" is generally used to refer to either seed cotton or lint. Seed cotton has the fibers or lint attached to the cottonseed, and is usually referred to as "seed cotton" . After the fiber is removed from the cottonseed, it is usually referred to as "lint" . Ginning includes drying, trash removal from seed cotton, lint-seed separation, trash removal from lint, and bale packaging. Processing cotton in a gin is an intricate task that proceeds at rates as high as 150,000 pounds per hour. Cotton ginning systems consist of several different types of processing machines, and each machine influences several physical properties of the cotton fiber (lint) .

The efficiency of the ginning process is strongly influenced by the quantity of moisture and trash that the cotton contains. Cotton contains varying amounts of trash and moisture, and is of varying colors. However, most cotton in the United States is conventionally processed through the same machines in a standard sequence, regardless of the level of trash in the cotton or the cotton color. The amount of drying received by the cotton is also relatively constant, regardless of the actual moisture content of the cotton. Therefore, in conventional cotton processing, some cotton may be over-dried, or processed through more cleaners than necessary for the level of trash in the cotton. Conventional cotton processing does not account for variations in the cotton being processed. This can result in decreased fiber quality, and increased costs and/or processing time.

One way to optimize the cotton processing sequence is to bypass certain machines, such as driers, seed cotton cleaners, and lint cleaners, that may not be necessary for the particular cotton being processed. However, in a conventional ginning system, physical properties of the cotton, such as trash content, moisture content and color, are not continuously measured as the cotton is processed in the gin. Further, no system or method exists for determining the optimal processing sequence for cotton, or for carrying out such a sequence. Additionally, changing the number of cleaners used in a conventional cotton ginning system requires downtime for the ginning system, as well as labor costs for changing the valve configurations in the system. At least five minutes is required to change the valves on a single gin stand lint cleaner device. A gin typically has three or more sets of lint cleaners in parallel processing lines . There is also the potential for malfunctions that arise when the valves are manually changed. Other gin machines and driers do not routinely have bypass valves, requiring that valves be provided.

To bypass a machine such as a lint cleaner, in a conventional ginning system, the flow of cotton is stopped through the gin stand that immediately precedes the lint cleaner. The valves to the machine to be bypassed are then closed, usually manually, and then the bypassed machine is stopped. To put the bypassed machine back on-line, the process must be reversed. In order to bypass a machine such as a seed cotton cleaner or drier, all of the preceding machines must be stopped. The flow of cotton is stopped throughout the entire system, for a period of several minutes so that the seed cotton cleaner valves can be manually changed. Once the machines are ready for operation, the valves to the bypassed machines are then opened, restoring flow to the bypassed machines.

A conventional ginning system does not continuously measure the physical properties of the cotton as it is being processed, and is not capable of determining the gin machine sequence that optimizes processing of cotton having those physical properties. An operator of a conventional ginning system cannot readily assess the need to alter the gin machine sequence to optimize cotton processing. Further, in a conventional ginning system, it is not possible to bypass a machine, or to divert the flow of entrained cotton to an auxiliary treatment unit outside the primary flow through the ginning system, without stopping the flow of cotton throughout the system. Further, bypassing machines in a conventional ginning system is slow, requires operator intervention, and requires repeated starting and stopping of the machines as they are bypassed or brought back on-line.

Thus, there is a need for an automated system that measures the physical properties of the materials as they are being processed, determines the optimum processing sequence for the materials, and implements the optimum processing sequence.

Summary of the Invention

In one aspect of the present invention, a computer program product is provided that comprises a computer useable medium having computer program logic or software recorded thereon for enabling a processor in a computer system to control the processing of cotton through a gin to produce lint . The computer program logic enables the processor to measure sensor data that correspond to color, moisture content, and trash content of the cotton as it enters the gin. The computer program logic enables the processor to generate a gin decision matrix that includes optimum process control decisions that maximize net return from the lint as a function of the input state of the cotton entering the gin. The computer program logic enables the processor to select an optimum process control decision from the gin decision matrix for an input state corresponding to the measured sensor data. The optimum process control decision corresponds to an optimum gin machine sequence for cotton with the measured input state . The processor is enabled by the computer program logic to implement the optimum process control decision by routing cotton through the optimum gin machine sequence. The computer program logic also enables the processor to compute and store predicted values for color, moisture content, and trash content for the cotton after processing through a first portion of the optimum gin machine sequence .

The gin decision matrix may be generated using a plurality of tabular transition functions. The gin decision matrix may also be generated using an algorithm for each gin machine in the optimum gin machine sequence. Each algorithm and tabular transition function quantifies the effect of that gin machine on leaf trash, moisture content, reflectance (Rd) , turnout, length, and yellowness (+b) .

The computer program logic of the present invention may also enable the processor to measure second sensor data that correspond to color, moisture content, and trash content of the cotton after it has been processed through the first portion of the optimum gin machine sequence. The processor may also be enabled to compare the second sensor data to the predicted values to generate an error, and to adjust the optimum gin machine sequence and the predicted values to compensate for the error. The computer program logic of the present invention may also enable the processor to measure lint sensor data that correspond to color, moisture content, and trash content of the cotton after it has been processed through a second portion of the optimum gin machine sequence. The processor may also be enabled to compute and store second predicted values for color, moisture content, and trash content for the cotton after processing through the second portion of the optimum gin machine sequence. The computer program logic may also enable the processor to compare the lint sensor data and the second predicted values to generate a second error, and to adjust the second portion of the optimum gin machine sequence and the second predicted values to compensate for the second error.

In a further aspect of the present invention, a program storage device readable by a machine is provided. The program storage device embodies a program of instructions executable by the machine to perform method steps for processing cotton through a gin to produce lint . The method steps include : measuring sensor data at a measurement station that correspond to color, moisture content, and trash content of the cotton at the measurement station; determining an optimum gin machine sequence for cotton entering the gin based on a physical state of the cotton at the measurement station that corresponds to the sensor data so that the optimum gin machine sequence maximizes net return from the lint; and routing the cotton through the optimum gin machine sequence. The measurement of sensor data may be performed at the measurement station as the cotton enters the gin, after the cotton has been processed through a first portion of the optimum gin machine sequence, or after the cotton has been completely processed through the optimum gin machine sequence .

The program storage device of the present invention may include an error feedback feature that may include the following method steps : measuring second sensor data at a second measurement station that correspond to color, moisture content, and trash content of the cotton after it has been processed through a first portion of the optimum gin machine sequence; computing and storing predicted values for color, moisture content, and trash content for the cotton after processing through the first portion of the optimum gin machine sequence; comparing the second sensor data to the predicted values to generate an error; and adjusting the optimum gin machine sequence and the predicted values to compensate for the error.

The program storage device of the present invention may also include a second error feedback feature that may include the following method steps: measuring lint sensor data that correspond to color, moisture content, and trash content of the cotton after it has been completely processed through said optimum gin machine sequence; computing and storing second predicted values for color, moisture content, and trash content for the cotton after processing completely through the optimum gin machine sequence; comparing the lint sensor data to the second predicted values to generate a second error; and adjusting a second portion of the optimum gin machine sequence and the second predicted values to compensate for the second error.

In yet a further aspect of the present invention, a control system is provided that controls the processing of cotton through a gin to produce lint. Such a gin has a plurality of auxiliary treatment units and a duct through which entrained cotton flows . The control system of the present invention comprises measuring means for measuring sensor data that correspond to color, moisture content, and trash content of the cotton. Processing means are coupled to the measuring means. The processing means processes the sensor data, and selects a set of the plurality of auxiliary treatment units in the gin through which the cotton is processed to produce lint. The set selected by the processing means corresponds to an optimum gin machine sequence that maximizes net return from the lint .

Each of the auxiliary treatment units in the gin is equipped with a cotton diversion means that is coupled to the processing means. The processing means activates the cotton diversion means to divert cotton to flow through each of the auxiliary treatment units in the selected set . The processing means deactivates the cotton diversion means to bypass each of the auxiliary treatment units that are not in the selected set.

The control system of the present invention may also include second measuring means coupled to the processing means for measuring sensor data that correspond to color, moisture content, and trash content of the cotton as it enters a second stage . This second stage may be a ginning stage, or a lint cleaning stage for which lint cleaner sensor data is measured. A third measuring means may also be provided for measuring color, moisture content, and trash content of the lint after processing by the set of auxiliary treatment units. The control system of the present invention may also be provided with cotton diversion means in the form of automated directional valves for controlling the flow of cotton through the set of auxiliary treatment units .

In still a further aspect of the present invention, a control system is provided for controlling the processing of lint through a mill that has a plurality of auxiliary treatment units and a duct through which lint flows. The control system includes measuring means for measuring sensor data that correspond to color, moisture content, and trash content of the lint. Processing means coupled to the measuring means is provided for processing the sensor data. The processing means selects a set, from the plurality of auxiliary treatment units, through which the lint is processed to produce lint of a predetermined quality. The set corresponds to an optimum mill machine sequence.

The control system also includes lint diversion means coupled to each of the auxiliary treatment units and coupled to the processing means. The processing means activates the lint diversion means to divert lint to flow through each of the auxiliary treatment units in the set. The processing means deactivates the lint diversion means to bypass each of the auxiliary treatment units not in the set .

In yet a further aspect of the present invention, a program storage device is provided that embodies a program of instruction to perform method steps for processing input material through a processing plant to produce processed material. The method steps comprise measuring sensor data at a measurement station that correspond to a physical state of the input material at the measurement station; determining an optimum processing machine sequence for input material entering the processing plant based on the physical state of the input material at the measurement station that corresponds to the sensor data, the optimum processing sequence maximizing net return from the processed material; and routing the input material through the optimum processing machine sequence.

Features and Advantages

A feature of the present invention is that it optimizes materials processing to maximize monetary return to producers, while minimizing the amount of machinery used and preserving quality of the materials.

A further feature of the present invention is that it provides for automated control of the gin process . The present invention has the added feature that the degree of automated control can be selected by the ginner, and customized for a particular gin.

It is yet a further feature of the present invention that it provides a real-time display to the ginner of physical properties of the cotton as it is being processed. The display also advises the ginner of the machinery sequence being used to process the cotton. The display may be located within the gin itself, as well as at other locations remote from the gin.

A still further feature of the present invention is that it can be adapted for use with fluid-entrained materials other than cotton, such as seeds, man-made fibers, or pharmaceuticals.

A still further feature of the present invention is that it provides instantaneous directional changes in the flow of fluid- entrained materials, particularly air-entrained cotton.

Yet a further feature of the present invention is that it can be adopted for use in a textile mill to control the processing and cleaning of lint to maximize quality of the lint.

An advantage of the present invention is that only the necessary machinery will be used to process a particular run of cotton, thereby saving on energy costs and minimizing waste and damage to the cotton by eliminating unnecessary processing steps.

Cotton fiber quality and profitability are improved.

A further advantage of the present invention is that it can be installed in an existing gin, as well as be included in the design of a new gin.

Still another advantage of the present invention is that the flow of cotton or other solids can be diverted without stopping the flow or shutting down machinery to carry out a manual valve changing operation.

A still further advantage of the present invention is that the flow of cotton can be diverted as necessary for cotton cleaning to provide cotton with an appropriate level of foreign matter and color. When cleaning is not necessary, the cleaning machines can be bypassed without stopping the machinery or the flow of cotton through the primary processing system.

A still further advantage of the present invention is that the continuous redirection of the flow of cotton occurs without choking a cotton duct in a ginning system.

Brief Description of the Drawings

The present invention is described with reference to the accompanying drawings . In the drawings , like reference numbers indicate identical or functionally similar elements. Additionally, the left-most digit (s) of a reference number identifies the drawing in which the reference number first appears .

FIG. 1 shows typical processing stages for a cotton ginning system;

FIG. 2 shows a schematic of a small-scale ginning system in which the present invention is installed;

FIG. 3 shows an expanded view of a sample collection installation in FIG. 2;

FIG. 4 shows an exemplary computer system suitable for use with the present invention;

FIG. 5 shows a partial view of a ginning system in which the automated directional valves of the present invention are installed with a lint cleaner;

FIG. 6 is an expanded view of the automated directional valves of the present invention;

FIG. 7 is a further view of the automated directional valves shown in FIG. 6 that illustrates selected valve positions;

FIG. 8 is an expanded view of the manually-operated slide valve shown in FIG . 6 ; FIGS. 9A-9D show alternate embodiments of the automated directional valves of the present invention;

FIG. 10 shows a block diagram illustrating implementation of the process control system of the present invention;

FIG. 11 shows a flow diagram of the process steps carried out for a first measurement station (Station 1) ;

FIG. 12 shows a flow diagram of the process steps carried out for a second measurement station (Station 2) ;

FIG. 13 shows a flow diagram of the process steps carried out for a third measurement station (Station 3) ;

FIG. 14 illustrates the error feedback process of the present invention;

FIG. 15 shows a screen display for editing a gin configuration file;

FIG. 16 shows a screen display for editing a decision matrix file;

FIG. 17a shows one embodiment of a screen display for the process control system of the present invention,-

FIG. 17b shows an alternate embodiment of a screen display for the process control system of the present invention;

FIG. 18 shows an output of optimum ginning decisions from a dynamic programming model of the present invention;

FIG. 19a shows a ladder diagram for implementing an embodiment of the present invention that includes automated valves ;

FIG. 19b shows a ladder diagram for implementing an embodiment of the present invention that includes semi-automated valves ;

FIG. 20 illustrates one embodiment of a hardware interface suitable for use with the process control system of the present invention; and FIG. 21 illustrates one embodiment of a cleaning line in a textile mill.

Detailed Description of the Embodiments Overview

The present invention is designed for use in a system that processes fluid-entrained materials. The invention will be described herein with reference to a ginning system that processes air-entrained cotton. In a ginning system equipped with the present invention, physical properties of the cotton are analyzed to determine the optimum ginning sequence to maximize return to cotton producers while producing cotton having desired fiber properties .

The present invention evaluates the physical properties and quality parameters of cotton before, during, and after the ginning process. Measurements of cotton color, moisture content, and trash content are made at three stations in the ginning system. A dynamic programming model uses these measurements, as well as information relative to staple length, lint turnout, cotton price structure, and energy cost to generate a matrix of optimum drying and cleaning sequences. The dynamic programming model optimizes producer profits by selecting the amount of gin machinery necessary to achieve the most beneficial market value, yet minimize the machinery used. The dynamic programming model uses the market price structure for cotton, and the performance characteristics for each gin machine, to determine optimum machinery sequences. The decision at each stage of processing depends on the state of the cotton entering that stage. Once the solution to the total problem has been obtained, the decisions can be related to the state of cotton when it enters the gin. Thus, the optimum decision at each stage of processing can be determined from the initial state of the cotton. The objective is to maximize the net return from the lint; i.e., the revenue from the lint minus the costs of the ginning operation. Any revenues or costs that do not vary with the processing decisions (e.g., revenue from seed and operating costs of the gin stand) are not included in the dynamic programming model because they do not affect the optimum decision. The present invention allows a ginner to process each increment of cotton through the minimum machinery necessary to achieve maximum returns, rather than processing all cotton identically.

Multiple fiber quality factors such as moisture content, color grade (yellowness and greyness) , and trash content (area, number, shape, and type of trash particles) are measured before the gin process (Station 1 in FIG. 2) . These measurements are used to ascertain the optimum seed cotton cleaning machinery, and drying temperature and exposure time, to produce specifically desired fiber properties that maximize monetary returns to cotton producers . Color is subdivided into two components for use in the process control system of the present invention: yellowness (+b) and reflectance (Rd) . Color, trash, and moisture sensors are installed perpendicularly to the flow of cotton. The cotton is forced to pause for a finite time period (typically approximately 1 second) as a sample collection means compresses the cotton against the sensors to provide a uniform measurement surface in a continuous, automatic, batch-type process. Electrical signals are transmitted from the sensors to a computer system for processing and storage .

Predicted values of each measured fiber property are stored in the computer system for subsequent comparison of the predicted value with the actual value after cleaning and drying of the seed cotton. The change in other common fiber properties such as fiber length, length distribution, uniformity, neps (small entanglements of cotton fibers) , short fiber content, micronaire, seed coat fragment size and weight, strength, upper quartile length, mean length, coefficient of variation length, elongation, lint turnout, etc. is estimated and recorded.

A second measurement station (Station 2 in FIG. 2) is used midway through the ginning system. A third measurement station (Station 3 in FIG. 2) is used after all cleaning, ginning, and drying has occurred to determine the final quality of the cotton, to provide error feedback to Station 2 , and to provide data that may be used in making machinery decisions . Samples of cotton are captured at Stations 2 and 3, and analyzed with sensors similar to those at Station 1. Measurement data obtained at Stations 1, 2 , or 3 may be used by the computer system to determine the optimum gin processing sequence for the cotton being processed.

The computer system is configured to selectively activate and deactivate cotton diversion means to individually control flow through each of the selected machines in the optimum gin processing sequence. For example, a clean cotton needs almost no cleaning to achieve its best possible grade. As such, the process control system of the present invention would determine which machines were not needed, and would bypass those cleaners.

The present invention diverts the flow of cotton through the selected combination of gin processing machines by controlling valves, such as the automated directional valves disclosed herein.

The valves are configured to provide for complete flow stoppage, or unrestricted flow. The opening and closing of the valves are sequentially controlled to allow cotton to clear the individual machines .

System Description

Typical processing stages for a cotton ginning system are shown in FIG. 1. The stages associated with a gin stand/feeder 150 and a bale press 170 are always required; the stages associated with the other illustrated machinery are optional . The ginning machinery combination recommended by the U.S. Department of Agriculture (USDA) includes two seed cotton driers 110, three seed cotton cleaners, gin stand, and two lint cleaners 160. The seed cotton cleaners typically include one or more cylinder cleaners 120, one or more stick machines 130, and one or more impact cleaners 140. The processing machinery illustrated in FIG. 1 is conventional in the gin processing industry, and the configuration and operation of the machinery is known to one of skill in the relevant art. A description of this machinery can be found, for example, in Cotton Ginners Handbook, USDA, Agricultural Handbook Number 503, December 1994, the entirety of which is incorporated herein by reference .

Most cotton in the United States is processed through the same standard USDA-recommended sequence of machines regardless of the trash level and cotton color. The amount of drying received by the cotton is also relatively constant regardless of the cotton's moisture content. Although the USDA-recommended ginning machinery sequence achieves satisfactory bale value and limits damage to the inherent quality of the fiber, it does not maximize the net cash value of each individual bale and minimize fiber damage .

The system and method of the present invention processes cotton through the minimum machinery necessary to achieve maximum returns. Rather than processing all cotton identically, the present invention provides for customized or prescription ginning of the cotton to preserve fiber quality and maximize monetary returns to cotton producers. A schematic of a small-scale ginning system in which the present invention is installed is shown in FIG. 2. The configuration shown in FIG. 2 has been provided for illustrative purposes only. A full-scale gin may include more or less machinery, or a different arrangement of machinery, than that illustrated in FIG. 2. It is to be understood that the present invention can be used with a variety of gin configurations, and is not limited to the configuration shown in FIG. 2. The ginning system of FIG. 2 includes a feed control 220 into which seed cotton is fed, two driers 110, two cylinder cleaners 120, stick machine 130, impact cleaner 140, extractor-feeder/gin stand 150, and three lint cleaners 160. At the end of the machinery sequence is a condenser 230 from which lint is expelled.

The ginning system of FIG. 2 is equipped with the process control system of the present invention which includes a computer system 240. The function and operation of computer system 240 is explained more fully below in Section 3 (Computer Program Implementation of the Preferred Embodiment ) .

An exemplary computer system 240 for use in the process control system of the present invention is shown in FIG. 4. In a preferred embodiment computer system 240 is a microcomputer such as an IBM-PC. Computer system 240 preferably includes a display, keyboard, and input/output circuitry suitable for interfacing with measuring means 210 and cotton diversion means 250. Computer system 240 includes one or more processors, such as processor 404.

Processor 404 is connected to a communication bus 406. Computer system 240 may communicate with other similarly configured computer systems or with a display (not shown) via a network 418, such as an ETHERNET local area network.

Computer system 240 also includes a main memory 408, preferably random access memory (RAM) , and a secondary memory 410.

Secondary memory 410 includes, for example, a hard disk drive 412 and/or a removable storage drive 414, representing a floppy disk drive, a magnetic tape drive, a compact disk drive, etc. Removable storage drive 414 reads from and/or writes to a removable storage unit 416 in a well known manner. Removable storage unit 416, also called a program storage device or a computer program product, represents a floppy disk, magnetic tape, compact disk, etc. As will be appreciated, removable storage unit 416 includes a computer usable storage medium having stored therein computer software and/or data.

Computer programs (also called computer control logic) are stored in main memory 408 and/or secondary memory 410. Such computer programs, when executed, enable computer system 240 to perform the features of the present invention as discussed herein. In particular, the computer programs, when executed, enable processor 404 to perform the features of the present invention. Accordingly, such computer programs represent controllers of computer system 240.

In one embodiment, the invention is a computer system operating according to software. In another embodiment, the invention is a computer program product having control logic which causes the computer to operate as discussed herein.

In another embodiment, the present invention is implemented primarily in hardware using, for example, a hardware state machine. Implementation of the hardware state machine so as to perform the functions described herein would be apparent to persons skilled in the relevant arts.

Computer system 240 is used to measure cotton characteristics at three measurement stations, shown as Stations 1, 2, and 3 in FIG. 2. Each station contains measuring means 210 for taking moisture, color, and foreign matter (trash) measurements on samples of cotton being processed. Station 1 evaluates seed cotton, whereas Stations 2 and 3 evaluate lint. Each of measuring means 210 includes a moisture meter 214 to measure moisture content of the cotton, and a camera 212 to measure color and trash content. Suitable cameras include the "Color/Trash Meter" camera made by Motion Control, Inc., and a similar device made by Spinlab, Inc., both now owned by Zellweger Uster. Suitable moisture sensors include infrared moisture sensors, such as those made by Infrared Engineering, Inc. or Moisture Systems Corporation. Resistance moisture sensors may also be used. A particularly preferred resistance moisture sensor is described in U.S. Patent 5,514,973, the entirety of which is incorporated herein by reference.

The three channels of data from the three cameras 212 shown in FIG. 2 are connected to a video multiplexer, such as model DT2859 made by Data Translation of Marlboro, MA. The multiplexer connects one of the eight input lines on the board with an output line under control of computer system 240. The appropriate camera 212 for a measurement is selected through the multiplexer. The output of the multiplexer is connected to a frame grabber, such as model HRT256 made by Catenary Systems of St. Louis, MO. The frame grabber converts a video frame to a set of digital pixel values that indicate light and dark areas of the image. Foreign material normally appears darker than the surrounding cotton fibers . The number of pixels which are dark compared to the neighboring pixels are counted to determine count data. The percent of the total number of pixels which are dark is used as the percent area of trash. The color meter is an instrument with two light sensors covered with different filters that approximate the ICI Standard Observer tri-stimulus values of Y and Z. The light sensors with filters produce a voltage that is calibrated to correspond to Y and Z. The Y and Z values are converted to the Nickerson-Hunter Rd (reflectance) , +b (yellowness) , and color code and quadrant values for cotton lint . One such transformation is contained in the COLORF.C file (discussed in more detail in Section 3.a.ii. below) in the attached microfiche appendix. The digital values of percent area trash, Rd, and +b are input to computer system 240 for processing and analysis. Turning now to FIG. 20, one embodiment of a hardware interface to computer system 240 is shown. The input to computer system 240 from the three cameras 212 of Stations 1, 2, and 3 is represented by video input lines V0, VI, and V2, respectively, of a video input 2030. The video multiplexer and frame grabber referred to above are contained within video input 2030. In a preferred embodiment, a digital interface 2040 is provided that consists of two 24-bit input/output (I/O) ports. These two 24-bit I/O ports are identified as lines DI through D48 of digital interface 2040. In a particularly preferred embodiment, one 24- bit I/O port is the PIO (programmable input/output) portion of a CIO-DAS16 board available from ComputerBoards, Inc., Mansfield, MA. The other 24 -bit I/O port is preferably a Computer Boards CI0-DI024 board. The 24 PIO lines from each of the digital I/O boards are connected to a ComputerBoards SSR-RACK24 containing 24 optoisolator modules . The optoisolator modules isolate computer system 240 from dangerous voltages associated with the digital I/O system, and are available from Gordos or OPT022. The 24 PIO lines from each of the digital I/O boards can be programmed for either input or output on each line, and the optoisolator modules are available for either input or output .

A digital-to-analog (D/A) converter 2020 is provided, and in a preferred embodiment is part of the CI0-DAS16 board. D/A converter 2020 may be used, for example, to control the temperature of the burners in drier 110. The burners in a drier are typically controlled by a burner control that is configured to receive an analog input . To change the temperature of the burners, the voltage is adjusted on line A0 of D/A converter 2020. The burner control then raises or lowers the temperature of the burners based upon this analog input .

The analog inputs to computer system 240 are captured with an analog-to-digital (A/D) converter 2010, such as the 12-bit A/D converter that is part of the CIO-DAS16 board. The two color output channels and two light level channels from each of the three measurement stations (cameras 212) are connected to A/D converter 2010. The color cells include two lines, Y and Z. The light level sensors include two additional lines, L and R. These four lines from each of the three measurement stations are input to A/D converter 2010 (lines A0 through All) . The analog output of the three moisture meters 214 is connected to A/D converter 2010 (lines A12 through A14) . In other embodiments, a digital output from moisture meter 214 is used, and is input to computer system 240 as a digital, rather than analog, input.

An analog multiplexer 2012, such as CIO-EXP32, connects to the CIO-DAS16 board. Analog signals representing the temperature of the burners in drier 110 can be connected to analog inputs on analog multiplexer 2012.

The sampling of cotton at the three measurement stations is controlled by computer system 240 through digital interface 2040.

As explained more fully below, sample collection means is used to capture a sample of cotton for measurement at each of the three measurement stations . This is achieved through the "close sample" line at Stations 1, 2, and 3 (D9, D12 , and D25, respectively).

Proximity sensors or switches are installed at each measurement station so that the position of the sample collection means (open, closed, or neither) can be measured by computer system 240 through digital interface 2040. As shown in FIG. 2 and discussed below, Station 1 uses a plunger or compression-ram type of sample collection means. Alternatively, Station 1 can be configured with a paddle-sampler type of sample collection means, as shown in FIG. 2 for Stations 2 and 3. The position of this sample collection means is input to computer system 240 on the lines labeled "Plunger Closed", "Plunger Open", and "Plunger Switch" (D21, D22, and D23) . Stations 2 and 3 are shown in FIG. 2 as configured with a "flapper" or paddle-sampler type of sample collection means. Stations 2 and 3 can alternatively be configured with a compression-ram type of sample collection means. Such a configuration is useful when Station 2 is located above the feeder shown in the lower left corner of FIG. 2. The position of the paddle sampler shown in FIG. 2 at Stations 2 and 3 is input to computer system 240 through the lines labeled "sample open" and "sample closed". The position of the paddle sampler used in connection with calibration at Stations 2 and 3 is input to computer system 240 through the lines labeled "cal . open" and "cal . closed" .

FIG. 20 shows four output lines from digital interface 2040 (D13-D16) that are input to Station 2. These lines are used to extend and retract a short stroke air cylinder and a long stroke air cylinder. These air cylinders are used during calibration of the sensors, as described in U.S. Patent No. 5,639,955.

In a preferred embodiment as shown in FIG. 20, a PLC (programmable logic controller) 2050 is used by computer system 240 to control the flow of cotton through the various gin machines. PLC 2050 is linked to a ginner' s control panel 2060 that includes a switch for selecting the method of valve control to be used, either automatic control or manual control. If automatic control is selected, computer system 240 and PLC 2050 automatically control switching of the valves to configure the gin machinery in accordance with the optimum gin machine sequence that corresponds to the optimum process control decision. If manual control is selected, then the valve settings are switched by an operator to configure the gin machinery in accordance with the optimum gin machine sequence that corresponds to the optimum process control decision, or the desires of the ginner. PLC 2050 reads the setting of this switch on ginner' s control panel 2060. As discussed below in Section 3.b., PLC 2050 is programmed to read this switch setting before initiating a change in the setting of the valves. In this manner, the degree of automated control can be selected by the ginner, and the system and method of the present invention can be customized for a particular gin.

The first line input to PLC 2050 is a computer valid line. This line is connected to a watch dog timer that is connected to line D20 of digital interface 2040. The watch dog timer switches the computer valid line to false if a monostable multivibrator is not reset by computer system 240. If the computer valid line is false, PLC 2050 defaults to a predetermined condition that safeguards the gin machinery.

The next two lines input to PLC 2050, LC A and LC B (D17 and D18) , are used to request that either or both of two lint cleaners ("A" and/or "B") be placed on-line so that cotton is diverted to flow through them. The two lines input to PLC 2050 labeled Impact Cl. and Stick Mach. (D30 and D31, respectively) are used to control selection of the seed cotton cleaners (impact cleaner 140 and stick machine 130) . Any combination of seed cotton cleaners (impact cleaners and stick machines) can be selected through D30 and D31. The line input to PLC 2050 labeled valid (D19) is used as a "handshake" line by computer system 240 to signal that the changes requested on the lint cleaner and seed cotton cleaner lines are valid. PLC 2050 is programmed to not output a change in selection of machinery while handshake line D19 is false. If a change to the selection of machinery is requested by computer system 240, the change will not be implemented (i.e., valve settings changed) until handshake line D19 returns to true.

The lines output from PLC 2050 to digital interface 2040 will now be described. Lines GS 1, 2, and 3 In (D33, D34, and D35, respectively) are used to indicate which of one or more gin stands is in position for ginning cotton. Lines DI through D6 are used to input to computer system 240 the number of lint cleaners actually on-line and being used. This number may differ from the number of lint cleaners requested by computer system 240 for two reasons. First, the machinery may be malfunctioning and set offline by the ginner. Second, the number of lint cleaners in actual use may differ from the number requested because automated control may have been disabled at ginner' s control panel 2060. Line D8 input to digital interface 2040 identifies whether automated or manual control of the valves for routing cotton through the lint cleaners has been selected at ginner' s control panel 2060. Line D7 provides an input from a proximity switch typically located on the bale press. This signal cycles once each time the bale press turns to indicate when the lint transitions from being placed in the current bale to being placed in the next bale. Lines D45 through D48 input the position of the four valves used to control the flow of cotton though the seed cotton cleaners (impact cleaners and stick machines) .

One of the major problems with measuring physical characteristics of cotton while it is continuously moving in a ginning system is enhancing the density to such a point that a homogeneous surface is achieved in order to make accurate measurements. Inconsistent surface densities create shadows in the imaging process which greatly affects the color and trash readings of the camera. Infrared moisture measurements are also greatly affected by inconsistent surface density. Sensors that respond to changes in resistance and capacitance also respond strongly to surface and/or bulk density. The present invention uses two types of sample collection means to obtain a cotton sample, and to increase the density of the cotton to enable the instrumentation to measure more accurately.

The first type of sample collection means is a compression ram 216, installed at Station 1 (see FIG. 2) . Compression ram 216 cyclically displaces a small mass of cotton from its pathway through feed control 220 toward one of the side walls, and presses the mass against the side wall so that the mass presents a face of uniform cotton density. The mass is then analyzed for color, trash content, and moisture content. These piston-type compression rams work extremely well in locations where cotton is moving very slowly such as at feed control 220. A particularly preferred compression-ram type of sample collection means is described in U.S. Patent No. 5,125,279, the entirety of which is incorporated herein by reference.

A second type of sample collection means is a paddle sampler 218, installed at Stations 2 and 3. An expanded view of the installation of paddle sampler 218 at Station 2 is shown in FIG. 3. Paddle sampler 218 systematically grasps a quantity of cotton and compresses it against the sensors where measurements are made, and then releases the cotton back into the air stream. The degree of pressing or compression is such that the halted cotton presents a face of uniform density on that part of the cotton which is pressed against the sensor surface . The uniform density is sufficient to enable the mass to be accurately analyzed for color, trash content, and moisture content. The system is typically carried out in an intermittent or cyclic manner so that a different mass of cotton is pressed against the sensor surface at specific time intervals. After compression, the pressure is removed, and each mass is allowed to resume its pathway through a duct 201 (best seen in FIG. 3) . As used herein, uniform cotton density means that the face of the mass which is pressed against the sensor surface is essentially filled with cotton and impurities, but with no voids. This enables an analyzer adjacent to the flattened face to make an analysis. Paddle sampler 218 is particularly suited for locations where cotton is moving rapidly, at speeds as high as 6,000 ft/min. A particularly preferred paddle-sampler type of sample collection means is described in U.S. Patent No. 5,087,120, the entirety of which is incorporated herein by reference.

As explained more fully below in Section 3 (Computer Program Implementation of the Preferred Embodiment ) , computer system 240 uses the measurement data obtained from Stations 1, 2, and 3 to optimize the flow of cotton through the ginning system illustrated in FIG. 2. To control the routing of cotton through the various machines, computer system 240 controls the operation of cotton diversion means 250 associated with each machine. Cotton diversion means 250 is used to route cotton through the optimum drying and cleaning sequence between Stations 1 and 2. Cotton diversion means 250 is also used to route cotton through the optimum cleaning sequence between Stations 2 and 3. Cotton diversion means 250 is used to divert cotton from duct 201 to flow through one or more auxiliary treatment units 202, which are shown in FIG. 2 as containing lint cleaner 160.

Cotton diversion means 250 diverts cotton to flow from duct 201, through auxiliary treatment unit 202, and return to duct 201.

Each cotton diversion means 250 is coupled to and controlled by computer system 240. Computer system 240 activates cotton diversion means 250 to divert cotton to flow through auxiliary treatment unit 202, and deactivates cotton diversion means 250 to discontinue flow of cotton through auxiliary treatment unit 202.

In the preferred embodiment, cotton diversion means 250 includes the automated directional valves described below.

A partial view of a ginning system in which the automated directional valves of the present invention are installed with one of several auxiliary treatment units is shown in FIG. 5. A conventional low pressure source, such as a fan (not shown) , moves entrained cotton through duct 201. A diversion unit in the form of auxiliary treatment unit 202 is disposed adjacent duct 201.

As illustrated in FIG. 5, auxiliary treatment unit 202 includes a lint cleaner, shown generally at 160. It is to be understood that auxiliary treatment unit 202 may include other types of cotton treatment machines, for example, a drier, a seed cotton cleaner, or an apparatus for moisture restoration, cotton combing, cotton blending, and the like.

A supply conduit 505, connected to duct 201 at a supply connection location 665, conveys cotton from duct 201 to auxiliary treatment unit 202. A return conduit 507, connected to duct 201 at a return connection location 675, returns treated cotton to duct 201. The connection of conduits 505 and 507 to duct 201, and the associated automated directional valves, are shown in more detail in FIG. 6.

Turning now to FIG. 6, a duct valve for controlling the flow of cotton through duct 201 is shown generally at 609. Duct valve 609 is a leaf valve having a leaf 699, and is operated by an air cylinder 629. Air cylinder 629 includes a stationary end 639, and a movable end 649 connected to leaf 699. As best seen in FIG. 7, duct valve 609 is mounted so that leaf 699 may be positioned in a recess 707 in duct 201. Leaf 699 is recessed into duct 201 to prevent cotton from hanging on leaf 699.

The flow of cotton through supply conduit 505 is controlled by a supply valve 611. Supply valve 611 is also a leaf valve having a leaf 791 (see FIG. 7) , and is operated by an air cylinder 621. As best seen in FIG. 7, leaf 791 is mounted in a recess 708 in supply conduit 505 to prevent cotton from hanging on leaf 791.

The flow of cotton through return conduit 507 is controlled by a return valve 613. Return valve 613 is also a leaf valve, and is operated by an air cylinder 623. Return valve 613 includes a leaf portion 683 that moves within supply conduit 505, and a leaf portion 693 that moves within return conduit 507.

Duct valve 609, supply valve 611, and return valve 613 are each operable between a fully opened position that provides for unrestricted flow, and a fully closed position for complete flow stoppage. As used herein, "operable between a fully opened position and a fully closed position" means that the valve has two positions of operation, a fully opened position and a fully closed position. These positions are illustrated in more detail in FIG. 7 for duct valve 609 and supply valve 611. In a fully opened position 709, leaf 699 of duct valve 609 is positioned within recess 707, out of the cotton flow through duct 201. In a fully closed position 710, leaf 699 of duct valve 609 is transverse or perpendicular to the flow of cotton through duct 201. In a fully opened position 712, leaf 791 of supply valve 611 is positioned within recess 708, out of the cotton flow through supply conduit 505. In a fully closed position 711, leaf 791 of supply valve 611 is positioned transverse or perpendicular to the flow of cotton through supply conduit 505.

FIG. 6 illustrates return valve 613 in a fully opened position with leaf portions 683 and 693 aligned to permit unrestricted flow through supply conduit 505 and return conduit 507. In a fully closed position, leaf portion 683 is positioned transversely across supply conduit 505, and leaf portion 693 is positioned transversely across return conduit 507. In the fully closed position, return valve 613 prevents cotton from flowing through supply conduit 505 and return conduit 507.

In a small-scale system, leaf 699, leaf 791, leaf portion 683, and leaf portion 693 are each approximately six inches high by 15 inches wide. In a full-scale system, the valve leafs are approximately 66 inches or 96 inches wide, rather than 15 inches. The valve leafs shown in FIGS. 6 and 7 are preferably constructed from two pieces of 16-gauge steel, with -inch thick felt (element 713 in FIG. 7) sandwiched between to seal against the sides of the duct. The steel is bolted and welded to a 5/8-inch cold-rolled steel rod that extends beyond one side of the duct to connect to the movable end of the air cylinder (see, for example, movable end 649 of air cylinder 629 in FIG. 6) . A preferred air cylinder is a five-inch stroke, 5/8-inch diameter rod, 1.5-inch diameter air cylinder, such as Speedaire model 6X374, activated by a Humphrey Max-Myte model 345-4E2 solenoid.

In a diversion mode of operation, cotton is diverted from duct 201 to flow through auxiliary treatment unit 202. In the diversion mode, duct valve 609 is in fully closed position 710 to completely stop the flow of cotton through duct 201. Supply valve 611 is in fully opened position 712 to allow unrestricted flow of cotton from duct 201 through supply conduit 505. Similarly, return valve 613 is in the fully opened position to provide unrestricted flow of cotton from auxiliary treatment unit 202, through return conduit 507, to duct 201.

In a bypass mode of operation, diversion is deactivated to discontinue flow of cotton through auxiliary treatment unit 202. In the bypass mode, duct valve 609 is in fully opened position 709 to allow unrestricted flow of cotton directly through duct 201. Supply valve 611 is in fully closed position 711 to completely stop the flow of cotton from duct 201 through supply conduit 505. Similarly, return valve 613 is in the fully closed position to completely stop the flow of cotton through return conduit 507.

The sequencing of the valves to transition from the bypass mode of operation to the diversion mode of operation will now be described. Supply valve 611 and return valve 613 are opened to provide communication between duct 201 and auxiliary treatment unit 202. Duct valve 609 is closed to block the flow of cotton through duct 201. Duct valve 609 should be moved from fully opened position 709 to fully closed position 710 sufficiently fast to prevent cotton from hanging between duct 201 and leaf 699. Supply valve 611 and return valve 613 should be opened substantially simultaneously with the closing of duct valve 609 to release the vacuum suddenly created on the upstream side of duct valve 609. This prevents cotton from being pulled around leaf 699 of duct valve 609 to avoid creating a potential blockage.

The sequencing of the valves to transition from the diversion mode of operation to the bypass mode of operation will now be described. Duct valve 609 is opened substantially simultaneously as supply valve 611 is closed. Return valve 613 is then closed after a pre-determined time delay. The pre-determined time delay is necessary to allow cotton to clear auxiliary treatment unit 202. The time delay may be selected by one of skill in the relevant art to allow for differences in the machinery selected for the auxiliary treatment unit. A time delay of approximately five to eight seconds is suitable when the auxiliary treatment unit consists of a conventional lint cleaner, such as lint cleaner 160 shown in FIGS. 1 and 2. The time required for cotton to enter and exit a machine such as lint cleaner 160 is approximately three seconds, i.e., three seconds is required to "clear" the cotton from the machine. A time delay of five to eight seconds is thus adequate to clear a machine such as lint cleaner 160. However, cotton that bypasses auxiliary treatment unit 202 after supply valve 611 closes and duct valve 609 opens is mixed for five to eight seconds with cotton that is still flowing through auxiliary treatment unit 202. This results in a "double load" of cotton passing through return connection location 675 for approximately two to five seconds (predetermined time delay minus three seconds to clear auxiliary treatment unit 202) . The pneumatic system in a typical gin should be adequate to handle the momentary overload.

Computer system 240 controls the opening and closing of duct valve 609, supply valve 611, and return valve 613. Computer system 240 sequences the valves to transition from the bypass mode of operation to the diversion mode of operation. Computer system 240 also sequences the valves to transition from the diversion mode of operation to the bypass mode of operation. To control the pneumatic air cylinder of each of the valves, output signals from computer system 240 are transmitted through, for example, solid- state relays on a relay card.

To partially compensate for the sudden change in pressure in duct 201 during transition from the diversion mode of operation to the bypass mode of operation, a pressure stabilization valve may be disposed in duct 201. When a vacuum is produced in duct 201, cotton hangs or stagnates in the vacuum. The cotton can be released back into the flow by allowing atmospheric air to enter the duct. A preferred pressure stabilization valve is a manually- operated slide valve, shown generally at 619 in FIG. 6, that allows air to enter duct 201. As best seen in FIG. 8, slide valve 619 allows air to enter duct 201 through an opening 601 in the wall of the duct. A slide 821 is positioned to control the amount of air that enters through opening 601. For example, in a fully closed position 819, no air enters through opening 601. In a partially open position 820, air will enter duct 201 through the open space between position 819 and position 820. Opening 601 may be restricted by a perforated metal covering or a fine mesh screen to prevent extraneous material from entering duct 201.

Slide valve 619 can also be used to prevent cotton from stagnating in supply conduit 505. As shown in FIG. 6, slide valve 619 allows air to enter supply conduit 505 through an opening 605. Slide valve 619 usually remains at one setting for a particular machinery and duct arrangement. However, slide valve 619 can be equipped with vacuum switches for automatic control.

Auxiliary treatment unit 202 may alternatively include a seed cotton cleaner. In that situation, duct valve 609 and supply valve 611 may be several feet apart because the inlet and outlet of seed cotton cleaners are typically several feet apart. With such a configuration, slide valve 619 is particularly important to prevent cotton from stagnating in the duct between the valves .

An alternate embodiment of the automated directional valves of the present invention is shown in FIG. 9A. In this embodiment, a first diversion unit is shown as machine 1, and a second diversion unit as machine 2. Machine 1 is connected to duct 201 through supply conduit 505 and return conduit 507. Machine 2 is connected to duct 201 through conduit 905. In a manner similar to that shown and described above for FIG. 6, three valves are used to divert cotton to flow through machine 1. These valves include a duct valve 909, a supply conduit valve 911, and a return conduit valve 913. Duct valve 909 is operated between a fully opened position and a fully closed position by a rotary actuator 929. Similarly, supply conduit valve 911 and return conduit valve 913 are operated between a fully opened position and a fully closed position by a rotary actuator 921, and 923, respectively. The diversion and bypass modes of operation for machine 1 are analogous to those described above in connection with the embodiment shown in FIGS. 5-8.

Two valves are used to divert cotton to flow through machine 2. A duct valve 917 is operated between a fully opened position and a fully closed position by a rotary actuator 927. Similarly, a conduit valve 915 is operated between a fully opened position and a fully closed position by a rotary actuator 925. In the diversion mode of operation for machine 2 , cotton is diverted from duct 201 to flow through machine 2. In the cotton diversion mode, duct valve 917 is in the fully closed position to completely stop the flow of cotton through duct 201. Conduit valve 915 is in the fully opened position to allow unrestricted flow of cotton from duct 201 through conduit 905.

In the bypass mode of operation, diversion is deactivated to discontinue flow of cotton through machine 2. In the bypass mode, duct valve 917 is in the fully opened position to allow unrestricted flow of cotton through duct 201. Conduit valve 915 is in the fully closed position to completely stop the flow of cotton from duct 201 through conduit 905.

To partially compensate for changes in pressure, and to prevent cotton from stagnating, slide valves 619 are provided in duct 201 adjacent duct valve 909 and duct valve 917. Slide valve 619 is located on the upstream side of each duct valve so that, upon entry of the air, cotton is released into the upstream flow. As shown in FIG. 6, slide valves 619 are also used in supply conduit 505 and conduit 905 to prevent cotton from stagnating in these conduits. Computer system 240 may be used to control the valves in the embodiment shown in FIG. 9A in a manner similar to that described above for the embodiment of FIGS. 5-8.

Alternate embodiments of the automated directional valves of the present invention are shown in FIGS. 9B through 9D. The embodiments shown in FIGS. 9B through 9D are particularly preferred as cotton diversion means 250 for the seed cotton cleaners shown in the top row of FIG. 2, whereas the embodiments shown in FIGS. 5-9A are particularly preferred as cotton diversion means 250 for the lint cleaners shown in the bottom row of FIG. 2.

In the embodiment of cotton diversion means 250 shown in FIG. 9B, cotton enters under the force of gravity by falling though an opening 930. In this embodiment, air suction is not used to move the cotton. Once the cotton enters through opening 930, it flows through a diverted or active leg, leg 932 shown in FIG. 9B. A valve leaf 942 is in the fully opened position, allowing cotton to flow through leg 932. To close off the flow of cotton through leg 932, valve leaf 942 is rotated about a shaft 943 along an arc 952 to a fully closed position. Movement of valve leaf 942 can be done through use of, for example, a rotary actuator (not shown) mounted on a mounting 950.

Cotton is prevented from flowing through a bypassed or inactive leg, leg 934 shown in FIG. 9B . A valve leaf 944 is in the fully closed position, preventing cotton from flowing through leg 934. To allow cotton to flow through leg 934, valve leaf 944 is rotated about a shaft 945 along an arc 954 to a fully opened position. Movement of valve leaf 944 can also be done through use of, for example, a rotary actuator mounted on mounting 950. Valve leafs 942 and 944 are moved substantially simultaneously. Valve leafs 942 and 944 may be connected by an adjustable, threaded turnbuckle, or other similar device, so that they move together. Alternatively, valve leafs 942 and 944 may be driven by separate devices .

A sponge rubber seal 940 is used to prevent valve leaf 942 and valve leaf 944 from vigorously impacting into the metal sides of leg 932 and leg 934, respectively, as they move to the fully opened position. Use of sponge rubber seal 940 prevents the creation of undue fatigue, as well as noise.

Computer system 240 controls the opening and closing of valve leafs 942 and 944. To change the leg through which cotton is diverted to flow, computer system 240 substantially simultaneously directs the valve leaf currently in the fully opened position (valve leaf 942 in FIG. 9B) to close, and directs the valve leaf currently in the fully closed position (valve leaf 944 in FIG. 9B) to open .

A further embodiment of cotton diversion means 250 is shown in FIG. 9C. The configuration of this embodiment is similar to that of FIG. 9B, and only the differences will be noted. Cotton diversion means 250 illustrated in FIG. 9C is equipped with an expanded metal element 960 on leg 934 and leg 932. Expanded metal element 960 is shown in more detail in FIG. 9D. Expanded metal element 960 allows air to flow into a leg when the corresponding valve leaf has been moved away from expanded metal element 960 to the fully closed position. In FIG. 9C, valve leaf 944 is in the fully closed position. When suction means, such as a fan, is used to draw suction in leg 934, air will flow through expanded metal element 960 and seal 940 to purge cotton from the inactive (bypassed) leg. Seal 940 allows air to pass when suction is drawn on the corresponding leg, but seals against air entering the leg through expanded metal element 960 unless desired by drawing suction. In FIG. 9C, expanded metal element 960 is closed off by valve leaf 942 to prevent air from entering into leg 932.

To change the leg through which cotton is diverted to flow, auxiliary suction means (not shown) , such as an auxiliary fan, is activated prior to changing the position of the valve leafs. Consequently, air is drawn through inactive leg 934 through expanded metal element 960. Air is drawn through active leg 932 via the main fan or suction means moving cotton through the system. Computer system 240 then substantially simultaneously directs the valve leaf currently in the fully opened position (valve leaf 942 in FIG. 9B) to close, and directs the valve leaf currently in the fully closed position (valve leaf 944 in FIG. 9B) to open. The auxiliary fan is powered for a time period sufficient to purge cotton from the previously active leg. This time period is a function of the length of duct in which the cotton can be trapped. Motion sensors can be used to determine when to turn off the auxiliary fan, or a timer with a predetermined time delay can be used. Alternatively, the auxiliary fan can remain continuously powered, such as when continuous changing between the active and inactive legs is occurring .

In one embodiment of the present invention, computer system 240 uses PLC 2050 to control the operation of cotton diversion means 250 associated with each gin machine. The connection between PLC 2050 and cotton diversion means 250, such as valves 609, 611, and 613, or valve leafs 942 and 944, would be readily apparent to one of skill in the relevant arts, and has been omitted for brevity.

Computer Program Implementation of the Preferred Embodiment

The process control system of the present invention is implemented by computer system 240 that includes control logic or computer software that directs its operation. In one embodiment, the present invention is directed to a computer program product comprising a computer readable medium having control logic (computer software) stored therein. The control logic, when executed by processor 404, causes processor 404 to perform the functions of the invention as described herein. In another embodiment, the present invention is directed to a program storage device readable by a machine that tangibly embodies a program of instructions executable by the machine to carry out the control process of the present invention.

FIG. 10 shows a block diagram illustrating implementation of the process control system of the present invention. In one embodiment, the process control system of the present invention is implemented using three software programs: (1) a process control decision and measurement program 1010; (2) a dynamic programming model 1020; and (3) a process control implementation program 1030. These three programs will be described in Sections 3. a., 3.b., and 3.c. below. To assist personnel operating the gin, process control decision and measurement program 1010 and process control implementation program 1030 provide output to a display 1040. Display 1040 includes the display associated with computer system 240, as well as other computer systems or CRTs communicating with computer system 240 via network 418 (see FIG. 4) . The present invention preferably includes a display configured for the ginner' s use (see, for example, FIG. 17b described below) .

A flow diagram of the process steps carried out for Station 1 (see FIG. 2) is shown in FIG. 11. In a step 1102, a sample of seed cotton is collected at feed control 220 using, for example, ram 216. In a step 1104, the seed cotton sample is measured using camera 212 and moisture meter 214 to obtain sensor data (shown as 1016 in FIG. 10) on color, trash content, and moisture content. The staple length of the cotton and the maximum lint turnout are not measured. Rather, a reference staple length is input by the operator at the time of processing or as the cotton module or trailer comes into the cotton gin. If staple length and turnout are not entered into computer system 240 by the ginner, then the system of the present invention defaults to typical reference values for staple length and turnout stored within dynamic programming model 1020. Such a reference staple length and turnout can be readily determined by one of skill in the relevant art based upon the variety of cotton being processed, the time of harvest, etc.

Using sensor data 1016 and the reference staple length and lint turnout obtained in step 1104, and a gin decision matrix generated by dynamic programming model 1020, a gin process control decision for the optimum gin machine sequence is made in a step 1106. As explained more fully below, dynamic programming model 1020 generates a gin decision matrix using cotton quality parameters 1026 and price structure 1024 that are input to a gin model 1022. Step 1106 optimizes the gin machine sequence for drying and cleaning between Stations 1 and 2 for the particular cotton input into the ginning system at feed control 220. Predicted values for the color, trash content, moisture content, staple length, and lint turnout for the cotton after it has undergone the selected drying and cleaning sequence between Stations 1 and 2 are computed and stored in a step 1108. The predicted values are computed using the sensor data values measured in step 1104, the drying and cleaning sequence selected in step 1106, and the effect on each of the parameters by the machines actually used in the selected sequence.

The predicted values computed in step 1108 are used in a step 1110 during which an error feedback Error₁₂ is received (denoted by 1208) and processed. As best seen in FIG. 14, Error₁₂ is the difference (denoted by Δ in FIG. 14) between the data measured at Station 2 for color, trash content, and moisture content, and the predicted values, computed and stored in step 1108, that each of these parameters will have at Station 2. Error₁₂ is weighted, as denoted in a step 1112. The weight accorded to Error₁₂ may be zero, in which case Error₁₂ is ignored, and the error feedback process of the present invention is disabled. The predicted values for color, trash content, and moisture content are adjusted using Error₁₂ in a step 1114. Error₁₂ is also used to adjust the decision for the optimum gin machine sequence in a step 1116. The measured values are adjusted by Error₁₂, and the decision process is iterated. The error feedback process of the present invention corrects for differences in the performance characteristics of the machinery. This is needed because different machines have different efficiencies, and the performance of each machine also changes with use and over time. Additionally, the ease of removal of foreign matter and moisture differs for varying types of cotton. The error feedback process of the present invention eliminates the need for precise performance characteristic tables or algorithms for each gin machine.

A flow diagram of the process steps carried out for Station 2 (see FIG. 2) is shown in FIG. 12. In a step 1202, a sample of seed cotton is collected using paddle sampler 218 after the cotton flows through gin stand 150. In a step 1204, the seed cotton sample is measured using camera 212 and moisture meter 214 to obtain sensor data on color, trash content, and moisture content. In a step 1206, the measured sensor data is compared to the predicted values computed in step 1108 to determine Error₁₂. Error₁₂ is fed back to Station 1 (step 1110) in a step 1208.

Using the sensor data obtained in step 1204, and the gin decision matrix generated by dynamic programming model 1020, a gin process control decision for the optimum gin sequence of lint cleaners is made in a step 1210. Step 1210 optimizes the gin sequence of lint cleaners for cleaning between Stations 2 and 3 for the particular cotton after processing between Stations 1 and 2. Predicted values for the color, trash content, and moisture content for the cotton after it has undergone the selected lint cleaner sequence between Stations 2 and 3 are computed and stored in a step 1212. The predicted values are computed using the data values measured in step 1204, the cleaning sequence selected in step 1210, and the effect on each of the parameters by the lint cleaners actually used in the selected sequence.

The predicted values computed in step 1212 are used in a step 1214 during which an error feedback Error₂₃ is received (denoted by 1308) and processed. As best seen in FIG. 14, Error₂₃ is the difference (denoted by Δ in FIG. 14) between the data measured at Station 3 for color, trash content, and moisture content, and the predicted values, computed and stored in step 1212, that each of these parameters will have at Station 3. Error₂₃ is weighted, as denoted in a step 1216. The weight accorded to Error₂₃ may be zero, in which case the error feedback process of the present invention is disabled. The predicted values for color, trash content, and moisture content are adjusted using Error₂₃ in a step 1218. Error₂₃ is also used to adjust the decision for the optimum gin sequence of lint cleaners in a step 1220. The measured values are adjusted by Error₂₃, and the decision process is iterated. The measured values at Station 3 are also used to verify predicted values for the entire system.

A flow diagram of the process steps carried out for Station 3 (see FIG. 2) is shown in FIG. 13. In a step 1302, a sample of cotton is collected using paddle sampler 218 after the cotton has completed processing through the selected sequence of lint cleaners 160. The seed cotton has now been processed into lint. In a step 1304, the lint sample is measured using camera 212 and moisture meter 214 to obtain sensor data on color, trash content, and moisture content. In a step 1306, the measured sensor data is compared to the predicted values computed in step 1212 to determine Error₂₃. Error₂₃ is fed back to Station 2 (step 1214) in a step 1308.

Each of the three software programs illustrated in FIG. 10 that carry out the process of the present invention will now be described. It is to be understood that the use of three software programs as shown in FIG. 10 is presented by way of example only. The functions of the three software programs could be carried out, for example, in one software program. In a particularly preferred embodiment, the three software programs illustrated in FIG. 10 are combined into a composite software program written in the C programming language. Also, the functionality described below could alternatively be achieved using hardware modules .

a. Process Control Decision and Measurement Program 1010 In a preferred embodiment, process control decision and measurement program 1010 is implemented using the C programming language, although other languages can be used. Program 1010 performs the function of selecting the optimum gin process control decision, as indicated by 1012. To select the optimum gin process control decision, program 1010 controls the measurement of cotton being processed in the gin, as shown at 1014, to obtain sensor data 1016. Sensor data 1016 includes color and moisture and trash content measurements made on the cotton as it progresses through the gin.

Filtering or smoothing of the sensor data measured by the system of the present invention is preferable because there is electrical and other noise inherent in the measurement process, and because an incorrect process control decision can have adverse economic impact on the farmer whose cotton is being processed in the gin. Such filtering or smoothing can be carried out by taking a series of electrical signal measurements over a specific time interval (e.g., 64 measurements during 1/60 second), and using the arithmetic mean of the readings. In addition, analog filters can be used to reduce the high frequency noise, and digital filters can be used to reduce the lower frequency noise as described in R. Bibbero, Microprocessors in Instruments and Control , John Wiley & Sons, Inc. (1977). It is also preferable to require that several, or a plurality of several, consecutive gin process control decisions (1012) be the same before the decision is implemented (1032) .

Another preferred method of implementing hysteresis control, and controlling unwanted variability of the output, is to use a counter. The counter incremented after every control decision that calls for a first state. The counter is decremented when the control decision calls for a different second state. When the counter increases past a predetermined value, the first control decision is implemented. When the counter decreases below a lower predetermined value, the second control decision is implemented. The counter is not allowed to count above or below additional predetermined limits .

Process control decision and measurement program 1010 implements the error feedback process of the present invention. As noted above, the present invention may be used in gins equipped with various configurations and types of machines made by a variety of manufacturers. These machines will also be in varying states of repair. Thus, the performance of each of the machines in a particular gin may not be perfectly represented by the tabular or algorithm-based transition functions of the present invention. As such, the error feedback process of the present invention compensates for the error resulting from the difference between the actual performance of the machines in a gin and the mathematical functions used by the present invention.

To implement the error feedback process , one embodiment of program 1010 measures a set of data (color, moisture content, and trash content) at Station 1, and assigns a time to that set of data. The time it takes, in seconds, for the cotton to get from Station 1 to Station 2 (and from Station 2 to Station 3) as a function of gin machinery sequence is contained in a gin configuration file. The contents of one embodiment of a gin configuration file are shown in FIG. 15. Program 1010 uses the clock contained in computer system 240, along with the time assigned to the set of Station 1 data and the times in the gin configuration file, to track when the cotton measured at Station 1 should be at Station 2. A number of measurements are taken at Station 2 in the vicinity of the computed arrival time. The average of these Station 2 measurements is used to represent the characteristics of the cotton initially measured at Station 1 after processing between Stations 1 and 2. Program 1010 compares the average of the Station 2 measurements to the values predicted from the Station 1 data to generate Error₁₂. A similar process may be used between Stations 2 and 3 to generate Error₂₃.

The error may be weighted using a weighting factor from 0 to 100%. With a weighting factor of 0, the error feedback process of the present invention is "off" or disabled. With a weighting factor of 100%, the Station 2 measurement is averaged one for one with the Station 1 measurement to adjust the predicted values for Station 2 and to adjust the optimum gin machine sequence between Stations 1 and 2. Likewise, with a weighting factor of 100%, the Station 3 measurement is averaged one for one with the Station 2 measurement to adjust the predicted values for Station 3 and to adjust the optimum gin machine sequence between Stations 2 and 3. With a weighting factor of 50%, the measurement at Station l would be weighted twice that of the measurement at Station 2. Conversely, with a weighting factor of 50%, the measurement at Station 2 is given half the weight of the measurement at Station 1 in adjusting the predicted values for Station 2 and the optimum gin machine sequence between Stations 1 and 2. Similarly, with a weighting factor of 50%, the measurement at Station 3 is given half the weight of the measurement at Station 2 in adjusting the predicted values for Station 3 and the optimum gin machine sequence between Stations 2 and 3. The weighting factors may be contained in a gin configuration file, such as show in FIG. 15. Measurements at each station are taken at time intervals, controlled, for example, by time delay relays at the measurement stations. In a preferred embodiment, measurements at Stations 1 and 2 are taken every 3 seconds, and once per second at Station 3. All measured data is recorded in an ASCII file. In a separate file, histograms, means, standard deviations, and minimum and maximum values are calculated and stored for each variable . Although staple length and lint turnout are not measured, the change in the value of these variables is calculated since these variables are affected by machinery in the gin machine sequence. The measurements at Stations 1, 2, and 3 can be used to instantaneously change the machinery sequence, or the changes can be made after a selected time period, or after a selected number of consecutive decisions that require the identical machine change . For example , the machinery sequence can be changed after a pre-determined time interval (e.g., five minutes) has elapsed after the change is identified. Alternatively, the machinery sequence can be changed after a specified number of measurements are taken that all indicate that the machinery sequence should be changed to the same new machinery sequence . Changing the machinery sequence after a selected time period or after a selected number of consecutive decisions provides hysteresis control for the system. In a preferred embodiment, four consecutive decisions to change the machinery sequence to the same new machinery sequence are required before the sequence is changed, i.e., before the decision corresponding to the new machinery sequence is implemented by process control implementation program 1030. The number of decisions that are required before the sequence is actually changed is a parameter that can be made available for change by the operator, or can be pre-programmed as a fixed value. In this manner, the system and method of the present invention can be customized to meet the needs of a particular gin. The machine sequence actually being used can be continuously displayed on display 1040, as well as the recommended sequence .

Another preferred method of implementing hysteresis control, and controlling unwanted variability of the output, is to use a counter. The counter incremented after every control decision that calls for a first state. The counter is decremented when the control decision calls for a different second state. When the counter increases past a predetermined value, the first control decision is implemented. When the counter decreases below a lower predetermined value, the second control decision is implemented. The counter is not allowed to count above or below additional predetermined limits. Process control decision and measurement program 1010 can also implement an override feature that allows the measurements taken at Station 3 to "override" the decision made at Station 2. Measuring means 210 at Station 3 generally provides the most accurate measurements because the cotton is at the end of the processing sequence and it has been combed and blended several times. In a preferred embodiment, program 1010 uses the level of reflectance, yellowness, moisture, and trash content at Station 3 to determine what the gin machinery sequence decision at Station 2 should have been. If the gin machinery sequence decision actually made at Station 2 was different, then the override feature can be implemented so that the gin machinery sequence determined from the measurements at Station 3 overrides the gin machinery sequence decision made at Station 2. The override feature is preferably implemented as a menu option. The override feature can be particularly useful if measuring means 210 at Station 2 is malfunctioning.

Process control decision and measurement program 1010 can also implement an automated calibration procedure for calibrating the various instruments of measuring means 210. A particularly preferred autocalibration procedure is described in U.S. Patent No.: 5,639,955 the entirety of which is incorporated herein by reference .

In one embodiment, program 1010 uses a gin configuration file, such as shown in FIG. 15, to store such items as valve positions, process times for the various gin machines, weighting factors for the error feedback process, time before machine selection can change, and how often to sample or measure data at each of Stations 1, 2, and 3. A screen display for editing the gin configuration file is shown in FIG. 15. The screen display of FIG. 15 is divided into three areas. The area on the left consists of a matrix in which each row corresponds to 13 machines: drier 1 at levels 1, 2, and 3 (1D1, 1D2 , and 1D3 , respectively); cylinder cleaner 1 (CCl) , stick machine 1 (SMI) ; drier 2 at levels 1, 2, and 3 (2D1, 2D2 , and 2D3 , respectively); cylinder cleaner 2 (CC2) ; impact cleaner 1 (IC1) ; and three lint cleaners (LCI, LC2, and LC3) . The three levels for the drier refer to the number of shelves or fraction of the drier that is being used. Drier level 1 refers to 6 shelves or % of the drier; drier level 2 refers to 12 shelves or Yi of the drier; and drier level 3 refers to 24 shelves or all of the drier. Each column in the area on the left corresponds to a particular machine sequence character, '

(blank) and ^X ' through * Z' . A ^VY' under a particular sequence character and in a particular row results in that machine being used whenever that particular sequence character was read from the decision matrix. A ^Λ ' (blank) results in that machine not being used. For example, machine sequence "R" includes drier 1 at level 1 (1D1) , cylinder cleaner 1 (CCl), drier 2 at level 2 (2D2) , impact cleaner 1 (IC1) , and two stages of lint cleaning (LCI and LC2) . A stick machine (SMI) is not used in machine sequence "R" . The middle area of the screen display of FIG. 15 is organized by rows corresponding to the 13 machines, and columns corresponding to various parameters of each machine . The entry column contains the time in seconds that it takes the cotton to travel from Station 1 (reference point for time measurement) to the valve used to route cotton either through (diversion mode) or around (bypass mode) the particular machine. The exit column contains the additional time in seconds that it takes the cotton to go through the machine (diversion mode) and reach the valve where the cotton reenters the main flow of cotton. The bypass column contains the time in seconds that it takes the cotton to bypass the machine, i.e., to travel between the valve at the entrance to the machine and the valve at the exit of the machine.

The filter column contains the time in seconds that a particular machine must be continuously selected (diversion mode) or not selected (bypass mode) before the valve can be switched to the other mode of operation. This filters out momentary changes in the position of the valves that would otherwise occur. The foregoing applies for valves, such as those shown in FIGS. 5-9A, for routing cotton through or around lint cleaners, as well as for valves, such as those shown in FIGS. 9B-9D, for routing cotton through or around seed cotton cleaners .

The middle area of the screen display of FIG. 15 also contains a column labeled Weight % . The weight % value is used when cotton diverted through the particular machine reenters the main duct and combines with cotton that had bypassed that machine . The weight % value is used to weight the predicted values of moisture content, trash content, and color based on this mixing of diverted and bypassed cotton. With a weight % value of 1.00, the predicted values are based upon the cotton that was diverted through that machine, and with a weight % of 0.00, the predicted values are based upon the cotton that bypassed that machine . As another example, a weight % value of 0.75 results in a predicted value that is equal to the sum of 0.75 times that of the cotton that was diverted through the machine and 0.25 (1-0.75) times that of the cotton that bypassed the machine . A weight % value of 0.5 is preferably used.

The third area of the screen display of FIG. 15 (located at the extreme right) is organized into a section for each of measurement Stations 1, 2, and 3. The rate is the time in seconds between requests by computer system 240 for the measurement of data. Computer system 240 requests a new reading from measuring means 210 at a time interval equal to the rate shown. The rate at the three measurement stations does not have to be the same, so that each station can have a rate that is different from the rate at the other stations. Filter is the time in seconds over which the readings from measuring means 210 are averaged. Entry is the time in seconds that it takes the cotton to reach Station 2 or Station 3 from Station 1, assuming the cotton has bypassed all machines. Finally, weight in this area of the screen display is used to determine the amount of the error (difference between actual and predicted values) that is fed back to the previous measurement station. The error feedback is computed by multiplying the difference between the actual and predicted values by the weight value, taking the sum, and dividing by the number of sample readings. A weight value of 0.00 disables the error feedback function.

A screen display for editing the gin decision matrix file is shown in FIG. 16. FIG. 16 shows one element of a decision matrix for one price structure and the transition function tables provided in Tables 1-15. The gin decision matrix is a three dimensional matrix with the X axis corresponding to moisture content, the Y axis corresponding to trash content, and the Z axis corresponding to color. The moisture content ranges from 3.00 to 10.00 in increments of 0.25. The trash content is represented by a statistical index that ranges from 72 to 100 in increments of 2. Finally, the color is represented by color code values from 31 to 73. The cell position at a particular value of moisture, trash, and color will contain a machine sequence character. The machinery configuration that corresponds to the machine sequence character is contained in the gin configuration file discussed above. The complete three dimensional gin decision matrix is composed of many elements, of which FIG. 16 is a representative example, that correspond to all possible combinations of moisture content, trash content, and color.

The first stage (Station 1 to Station 2) machine sequence character is either a ' (blank) or character from ^%A' to ^ΛZ' .

The moisture, trash, and color readings from Station 1, adjusted by error feedback if not disabled, are used to enter the gin decision matrix. The first stage machine sequence character located at that cell position is used to determine from the gin configuration file which of the machines between Stations 1 and 2 will be used (diversion mode) and which will be bypassed. The drier sequence character is used in a similar manner to determine the number of shelves to be used in each drier.

The second stage (Station 2 to Station 3) machine sequence character determines which of three lint cleaners are to be used in the second stage. The moisture, trash, and color readings from Station 2, adjusted by error feedback if not disabled, are used to enter the gin decision matrix to locate the cell position for the second stage machine sequence character.

In the example shown in FIG. 16, machine sequence V includes a cylinder cleaner (CCl) , a stick machine (SMI) , and an impact cleaner (IC1) in a first portion of the optimum machine sequence. A "Y" indicates that the particular machine is used in the sequence, whereas a "blank" indicates that the machine is not used. Based upon processing through such a first stage, the predicted values of moisture, trash, and color at Station 2 are shown. A second portion of the optimum machine sequence is machine sequence C that includes two stages of lint cleaning (LCI and LC2) . Based upon processing though such a second stage, the predicted values of moisture, trash, and color at Station 3 are shown.

One embodiment of a screen display for the process control system of the present invention is shown in FIG. 17a. This display includes the raw sensor data measured at Stations 1, 2, and 3 , the predicted values for Stations 2 and 3 , and the error feedback for Stations 1 and 2. For example, at Station 2, a reflectance (Rd) of 56.3 and a +b (yellowness) of 8.2 was measured. These raw values of Rd and +b correspond to a color code of 61. A conversion or lookup table can be used to convert between Rd, +b and color codes. Such a conversion table is contained in file UPLND.COL in the attached microfiche appendix. The raw measured data for trash at Station 2 is area 54 (0.54% of the pixels covered by trash) and count 31 (related to the number of pixels covered by trash) . The area and count are converted to a leaf or trash code that ranges from 2 to 8; in this example , code 5.

The screen display shown in FIG. 17a contains a line labeled "Filtered Reading" at each measurement station. The moisture reading represents the actual moisture content (percentage) measured at each station, e.g., 6.38% at Station 2. The color code listed for the filtered reading at each station represents the better of the predicted color value based on the measurements made at Station 1, and the actual color measured at Station 3. The most accurate reading of color is made at Station 3 because the cotton has been cleaned and the seeds removed so that a more uniform product is available for measurement. The filtered trash reading is obtained by converting the area and count to a statistical trash index, such as is done by the procedures in the CONTDECF.C file of process control decision and measurement program 1010 described below.

The screen display in FIG. 17a also includes the error feedback values for Stations 1 and 2. In the example shown in FIG. 17a, the error feedback provided to Station 2 (Error₂₃) is +0.14 for moisture, +0.00 for color, and +1.4 for trash. These values are computed using the difference between the predicted and actual values and the weight contained in the gin configuration file for Station 3.

The gin machine sequence in use is also displayed in FIG. 17a, including the first stage machines between Stations 1 and 2, and the second stage lint cleaning machines between Stations 2 and 3. The decision matrix file and the gin configuration file being used are also indicated.

A particularly preferred embodiment of process control decision and measurement program 1010 is provided in the attached microfiche appendix. This preferred embodiment can be used in a gin having a configuration substantially as shown in FIG. 2, and can be used with the hardware interface shown in FIG. 20. The source code refers to paddle sampler 218 as a "flapper" . This preferred embodiment of process control decision and measurement program 1010 is written to use the embodiment of dynamic programming model 1020 attached hereto in the microfiche appendix.

As explained more fully below in Section 3.b., in such an embodiment of dynamic programming model 1020, algorithmic rather than tabular transition functions are used. The optimum machine sequences are generated by the algorithms, rather than being stored in a table. As such, a gin configuration file is not used in this preferred embodiment of process control decision and measurement program 1010.

The attached preferred embodiment of program 1010 is written in the C programming language, and contains a total of 20 files.

There are seven ".C" files and 12 external included " .H" files.

The function of each of these files will be briefly summarized below. A computer programmer skilled in the relevant art could readily interpret and implement the present invention based on the disclosed source code, i . LCADV2. C This file includes a MAIN_SECTION that records the current computer screen display settings, runs a setup procedure, and runs an open menu procedure. When the program returns from the open menu procedure, this section returns the screen to the mode it was in when the program was called, and exits the program. In the setup procedure, output control lines are set to the failsafe condition for the gin, either high or low for a particular line. Files and variables are also initialized.

The open menu procedure is the first portion of the code that provides an interface to the user. A menu is displayed so that a user can select one or more functions to be performed. The functions include implementing process control and measurement, performing selected diagnostics, or performing calibrations of the equipment and sensors within the system. If the user selects "0", the system autocalibrates the sensors at Station 2, and returns to the menu. A selection of "9" autocalibrates the sensors at Station 3. If the user selects "1", the system sets the sample collection means at each measurement station for proper operation, and begins to run the data collection and control portion of the program (getdata2 procedure described below) . If the user selects "2", the digital input lines are read, and the values displayed on the screen. If the user selects "3", the program outputs a varying series of bits to the output data lines as a diagnostic check. A selection of "5", "6", or "7" results in color calibration of the camera at Stations 1, 2, and 3, respectively. A selection "a", "b" , or "c" results in trash calibration of the camera at Stations 1, 2, and 3, respectively. If the user selects "e", the values from A/D converter 2010 are displayed so that the analog inputs can be checked. If the user selects "f", a measurement of color and trash is immediately obtained from one of the measurement stations, and displayed on the screen. If the user selects "8", the use of data from Station 3 is switched on or off, and the setting is displayed on the screen. A selection of "x" or "X" will exit the program to the operating system (DOS) . Additional functions are possible with the embodiment contained in the attached microfiche appendix, even though these functions are not presented to the user in the menu. For example, if the user enters "d", the seed cotton cleaner selection is changed, even though this is not listed as a menu choice. If "d" is selected, computer system 240 passes control bits to PLC 2050 to change the selection of seed cotton cleaners. If the user enters "g", computer system 240 requests PLC 2050 to switch to one lint cleaner. A selection of "h" generates a request to PLC 2050 to switch to two lint cleaners. A selection of "i" cycles paddle samplers 218 between open and closed. A selection of "j" cycles the position of calibration tiles used to calibrate the color and trash sensors at Stations 2 and 3. If the user enters "k" , a tag message is checked. The tag message refers to the bar code information contained on the tag for each bale being processed. A selection of "1" cycles the sample collection means at Stations 1, 2, and 3 as they are done during a data collection phase. Finally, a selection of "m" cycles an additional sample collection means which may be used for infrared moisture measurements behind gin stand 150.

The getdata2 procedure is the primary procedure for data collection and process control. It cycles continuously until a function key is pressed to exit the procedure. This procedure starts by clearing the screen and initializing variables. This procedure sets up the frame grabber used in the trash measurement, checks function keys, and also measures analog inputs not related to color or trash. It checks the last moisture content readings to determine if they are within a reasonable range. If the moisture content readings are within a reasonable range, they are left unchanged. If the moisture content readings are not within a reasonable range, the procedure sets them to extreme values to flag them as incorrect readings for other parts of the code.

The getdata2 procedure then starts data collection at Station 1. The sample collection means at Station 1 is triggered to collect a sample, the most recent readings from Station 3 are added to the running total so that average values can be calculated, and a "wait closure" for Station 1 is executed. The wait_ closure procedure waits for a certain period of time (time out period) , or until closure of the sample collection means is verified through the use of position or proximity sensors, whichever comes first . At the beginning of the wait_closure procedure, the location of the bit that signals whether the sample collection means ("flapper") is closed is read, along with the number of seconds for the wait or time out period. If either the sample collection means is verified to be closed, or the time out period expires, the wait_closure procedure returns to the calling program. A flag is passed back indicating whether verification of closure of the sample collection means was obtained.

Once the sample collection means has closed, or the wait_closure procedure has "timed out", the getdata procedure collects the data for Station 1. Similar procedures are repeated for Stations 2 and 3. The getdata procedure controls color and trash data collection. The code executes based upon three camera counts of 0 , 1, and 2. The code first sets up the frame grabber channel by switching the multiplexer between the three channels . Trash and color measurements are then made. The trash and color measurements are then analyzed to determine if the readings are within a reasonable range. If the readings are within a reasonable range, they are left unchanged. If the readings are not within a reasonable range, the readings are set to extreme values to flag other parts of the code that the readings are incorrect .

The getdata2 procedure also calculates the number of lint cleaners and the sequence of seed cotton cleaning recommended by dynamic programming model 1020. These calculations are made based upon measured values of Rd, +b, and percent area of trash. When measured values of moisture content are within an acceptable range indicating that they are reliable, actual measured values of moisture content are used in these calculations. Otherwise, a value of 5% moisture content is used in the calculations. This procedure also controls the number of decisions or readings that are required before a change in the number of lint cleaners is made. Finally, the getdata2 procedure checks the time of day, and opens a new file for data logging if the date has changed. This procedure also keeps track of when autocalibration is required at each measurement station. If the autocalibration feature is active and it is time for a new autocalibration, the autocal procedure is called.

In the attached embodiment, the autocal procedure is written to run automatic calibrations at Stations 2 or 3. Preferably, automatic calibration is performed at Station 1 as well. It would be readily apparent to one of skill in the relevant arts how to modify the attached code to perform automatic calibration at Station 1. The attached autocal procedure code is divided into two sections, one section for each station. The procedure begins by opening and closing the paddle samplers to which the calibration tiles for the sensors are attached. This removes dust that tends to settle on the calibration tiles. The calibration tiles are pulled across a section of lambs wool to clean them before calibration begins. When the calibration routine is completed, the calibration tile paddle samplers are again opened and closed several times to dislodge any cotton that may have been caught on the paddle samplers. The autocalibration procedure is described in more detail in U.S. Patent No. 5,639,955, the entirety of which is incorporated herein by reference.

The LCADVl . C includes several procedures for keeping track of bale numbers, and for calculating the means and modes of the measured parameters for each individual bale . ii . COLORF . C

This file contains a collection of procedures that relate to color calibration based on a five tile procedure, to color measurement, and to measurement of other variables, such as analog moisture values and analog temperature data, using A/D converter 2010. All readings of A/D converter 2010 are made in this collection of procedures. This file also contains the compute_color procedure for converting to color code from the measured Rd and +b readings .

The mcmgr procedure in this file is the moisture content measurement manager software. It controls data collection from the resistance moisture sensors installed at Stations 1, 2, and 3. iii. TRASHF.C

This file contains procedures for measurement of trash content . The do_a_frame procedure takes a reading from an individual frame of the channel being pointed to by the video multiplexer that is part of video input 2030. It determines whether an individual pixel should be considered as trash. It counts the number of pixels that are trash in the complete image, and converts this reading to the percent of the total number of pixels that are in the complete image. The file calls a number of library functions that deal with the frame grabber that is also part of video input 2030.

This file also contains a number of procedures for calibration. The trsh_cal procedure is for calibration of the trash reading based upon a properly presented trash tile. Adjustments to the Y, Z, and percent area readings based on the calibration tiles are calculated in the calc_ctile_adj procedure. The calc_ctmean procedure takes the mean of several readings of Rd, +b, or percent area and stores them in a matrix. This is used to check he correct readings of the autocalibration tiles. iv . CONTDECF . C

This file contains the procedures for calculation or selection of the optimum process control decision using the gin decision matrix generated by dynamic programming model 1020. The ASCII file containing the gin decision matrix generated by dynamic programming model 1020 is opened, and the contents are read into a decision matrix within this C language program. The moisture content readings, as well as those for trash and color, are converted to indices which are then used to point into the decision matrix. The parea_to_clgr procedure converts the percent area measured by the trash meter to an estimated leaf value, used in the pricing of cotton. The scc_lookup procedure uses the values of Rd, +b, moisture and percent area to look up the optimum seed cotton cleaning sequence (between Stations 1 and 2) based on the decision matrix obtained from dynamic programming model 1020. The lc_lookup procedure uses the values of Rd, +b, moisture content and percent area to look up the optimum lint cleaning sequence (between Stations 2 and 3) based on the decision matrix obtained from dynamic programming model 1020. The lc_check and rule_of_thumb procedures are similar procedures used to adjust the decision relating to the number of lint cleaners being used to ensure that revenue is maximized. These two procedures use price structure 1024, as well as color and trash data from Station 3, to refine the decision for the number of lint cleaners based upon the level of cleaning actually achieved so that revenue is maximized. These two procedures ensure that in the region of a break point in price structure 1024, sufficient cotton cleaners are being used so that revenue will still be maximized, v. DGTLIOF. C

This file contains procedures used in digital input and output (I/O) . The main section of this code provides bitwise communication with PLC 2050, control of the sample collection means, and reading of the position sensors throughout the system. Additionally, procedures are provided for reading files on network 418 for communication with other computers that are measuring parameters associated with the gin system (kp_f_read and kp_f_write procedures) . For example, some gins are equipped with a gin computer into which the ginner will enter data that is contained on tags attached to the modules or trailers of seed cotton entering the gin. This tag data may include, for example, the name of the farmer, the variety of cotton, the farm number, the field number, and the harvest date. The tag data can be transmitted via network 418 from the gin computer to computer system 240. The kp_f read and write procedures can be used to display and record the tag data . The kp_f_ write procedure stores enough data to completely describe the current functioning of the system including: the tag data, the temperature of each of the dryers, the position of each of the seed cotton and lint cleaners, whether each gin stand is "in" or "out," the moisture content of the cotton at several places in the gin, the color and trash level of the cotton being ginned, the ginning rate, the bale number, and the mean value for the moisture, color, and trash of the last 10 bales . This information can be monitored from any computer on network 418 and displayed in near real time. In addition, it is possible to monitor the functioning of the gin from any computer through transfer of this data over telephone lines . In addition to displaying the tag data for the ginner, the tag data can also be used in determining the optimum process control decision. For example, default values for staple length and micronaire can be stored in a lookup table as a function of variety. The default value to be used by dynamic programming model 1020 for these two parameters can be obtained from such a lookup table after obtaining the variety from the tag data. The flapper procedure is used to control the flappers or sample collection means such as paddle sampler 218 or compression ram 216. Individual flappers can be opened or closed one at a time, or all flappers can be opened and closed at the same time. The calflap procedure controls movement of the flappers associated with the calibration tiles.

The chk_tagmsg procedure checks for a new bale tag message . The bale tag message is created by a computer at the bale press that reads the bar code tag that is attached to each bale of cotton. The bale tag message includes the bale number as well as the bale weight . The computer at the bale press sends the bale tag message to computer system 240 via network 418. If a new bale tag message is available on network 418, this message is read and stored by computer system 240 in a file, and the network file is erased. The chk_bc procedure monitors the state of a switch, usually a proximity switch attached to the bale press, to determine when bales are changed. This procedure reads the time at which the bale press turns , which is the exact moment that cotton is switched from the current bale into the next bale . The procedure provides for software debouncing to accommodate the bouncing encountered with mechanical switches .

The chk__lcu procedure reads the current number of lint cleaners for each of the gin stands, and the number of seed cotton cleaners being used, as transmitted to computer system 240 by PLC 2050.

The CompOK procedure provides a safety feature so that other computers or components in the system can detect if computer system 240 is not functioning properly. The code alternately switches one bit between high and low that resets a monostable multivibrator. If the code is operating properly, the monostable multivibrator will be continuously reset to the computer OK state. However, if the software stops proper operation of the computer, the monostable multivibrator is not reset, and this bit changes to an error condition that can be sensed by other computers or components in the system to detect that computer system 240 may not be functioning properly.

The wait_samp_open, wait_cal_closed, and wait_cal__open procedures all operate in a manner similar to the wait_closure procedure discussed above. At the beginning of the procedure, the byte and the bit signaling the opening (or closing) of the sample collection means ("flapper"; paddle sampler 218 or compression ram 216) ) , and a maximum number of seconds (time out period) the software is allowed to wait for the flapper to open, are read. This procedure reads the current state of the flapper as sensed by the proximity or position sensors, checks for keyboard function key entries, signals the monostable multivibrator not to time out, and checks the time. The process is repeated until a reading of open (or closed) is received from the proximity switch, or the time out period expires, vi. DISPLAYF.C This file displays information for the ginner on the display of control system 240 relating to the operation of the machinery, the process control decisions, how the control decisions are reached, and the bale averages for the past ten bales. The showCT procedure displays, for example, the data (color, trash, and moisture contents), current decisions, and current operating conditions (gin machine sequence currently being used) . The showBA procedure displays data on the last ten bales processed through the gin. The showCalBa procedure displays calibration and other data in the same area where the bale average data is normally displayed. vii. LOGDATAF.C This file contains procedures for logging data to hard disk drive 412 of computer system 240 and network 418. The procedures ensure that files are opened under unique names based on the date, and the files that have already been opened on that date. If a file is available on network 418 and hard disk drive 412, then the data is written to both locations. viii. ".H" Files

The attached microfiche appendix contains twelve ".H" files which are external files that are included into the seven ".C" files discussed above. These files are used to include other files that are part of a Microsoft C package, files that are part of a color and trash measurement system obtained from MCI , and files that are part of a frame grabber system obtained from Catenary Systems .

HVICONST.H contains code that defines values and structures for the MCI color and trash measurement system. CAINC.H contains many of the external "includes." The three files "vicdefs.h, vicfcts.h, and vicerror.h" are part of the Victor Software Library for the frame grabber card. The three files "hviconst .h, hvimain.h, and driver. h" are part of the MCI package for the color and trash measurement cameras . The remainder of the files that are included in CAINC.H are part of the basic Microsoft C package. These are all files that contain drivers and software for the hardware in the system, as well as the operating system. CADEF.H contains many of the "defines" used throughout process control decision and measurement program 1010. The defines in this file are addresses and unchanging variable values. CAEXT.H contains declarations for all the global variables that are used in program 1010.

The CAPROTO.H file contains the seven "include" files that have the declaration of the types for each of the seven ".C" files . They are located in separate files that correspond to the source code files that contain the C source code. The ColorPrt.h file contains the declarations for the procedures contained in the COLORF.C file. The declarations pertain primarily to color measurement and color calibration, but also include declarations of all the analog data collection that is used in the system. The TrashPrt.h file contains declarations for the procedures related to the frame grabber and trash measurements used in the TRASHF.C file. The ContDPrt.h file contains declarations for procedures used in the CONTDECF.C file. The DgtIIPrt.h file contains declarations for all of the procedures used in the DGTLIOF.C file for digital input and output (e.g., opening and closing flappers for sample collection as well as the bitwise data transfer between PLC 2050 and computer system 240). The DisplPrt.h file contains declarations for the procedures used in DISPLAYF.C to display data on the computer display in the gin. The LcadvPrt.h file contains declarations for the procedures used in LCADVl.C. The declarations for these procedures are related to control of data collection, calculation of means and modes of the collected data, and execution of autocalibration procedures. The LogDaPrt.h file contains declarations for the procedures contained in LOGDATAF.C. An alternate embodiment of a screen display for the process control system of the present invention is shown in FIG. 17b. The screen display shown in FIG. 17b is representative of a display that would be provided for the ginner in a gin equipped with the preferred embodiment of process control decision and measurement program 1010 described immediately above. In the example shown in FIG. 17b, the gin is actually equipped with three parallel gin machinery sequences, identified as Gin 1, Gin 2, and Gin 3. FIG. 17b shows in the upper left hand corner, beneath the date/time display, that 1 cleaner (lint cleaner) is in operation for each of Gin 1, Gin 2, and Gin 3. FIG. 17b shows 1 Cleaner Recommended, i.e., the optimum gin machine sequence requires the use of one lint cleaner. Working On Station 1 indicates that color, trash content, and moisture content readings are being taken at Station 1.

The table in the upper right hand portion of FIG. 17b provides the current values of Color, %Area, and Moisture at Stations 1, 2, and 3. Rather than displaying the measured Rd and +b values, these values are transformed and displayed as color code and quadrant . The %Area and Leaf table that appears in the lower left hand corner of the FIG. 17b display provides a simplified transformation between the %Area trash measurement values and a manual leaf grade classification standard. This is provided as a quick reference guide so that the ginner can quickly correlate the %Area readings being displayed to a standard leaf grade classification.

The table in the lower right hand corner of FIG. 17b provides a history of the last 8 bales for the ginner . The show BA procedure discussed above is written to display the last 10 bales . This procedure could be readily modified by one of skill in the art to display a history of the last "N" bales as selected by the ginner. In a typical gin, a bale is processed through a sequence such as the one shown in FIG. 2 approximately every two minutes. Thus, the lower right hand table in FIG. 17b provides the ginner with data from approximately the previous 16 minutes of operation. The first column identifies the bale number. The second and third columns display the average values of color and leaf grade for each bale at Station 2 (Before LC - Lint Cleaner) and Station 3 (After LC - Lint Cleaner) , respectively. The average moisture value for each bale at Stations 1, 2, and 3 is also displayed.

The screen display shown in FIG. 17b could be readily modified by one of skill in the art to display additional information for a ginner. Such additional information could include, for example, bale weight, gin rate, and bale moisture content . b. Dynamic Programming Model 1020

In the embodiment shown in FIG. 10, dynamic programming model 1020 is a program separate from process control decision and measurement program 1010. In one such embodiment, dynamic programming model 1020 is implemented using the FORTRAN programming language and is run off-line to generate the gin decision matrix prior to running process control decision and measurement program 1010. In a preferred embodiment, dynamic programming model 1020 is written in the C programming language and is incorporated into process control decision and measurement program 1010 so that dynamic programming model 1020 is running in real-time rather than off-line.

Dynamic programming model 1020 includes a gin model 1022 that uses price structure 1024 of the cotton as an input . Dynamic programming model 1020 uses price structure 1024, cotton quality parameters 1026, and the performance characteristics for each gin machine to determine the optimum machinery sequence to maximize returns to the producers. Dynamic programming model 1020 uses input information relative to the moisture content, color (reflectance = Rd and yellowness = +b) , trash content, maximum possible turnout, price structure of the cotton market, and energy cost to determine the optimum drying and cleaning sequence.

When lint is sold, the price is determined by its final length, leaf grade, and color grade. Color grade is a step function of values such as 21, 31, 41, 51, etc. The present invention tracks two components of color, Rd and +b, which are continuous functions. A conversion or lookup table is used to convert between Rd, +b and color grades. Such a conversion table is contained in file UPLND.COL in the attached microfiche appendi .

Monetary returns are a function of the quality of lint cotton after ginning, and are determined by color grade, leaf grade, staple length and micronaire . The staple length and micronaire fiber qualities are established before the cotton is removed from the plant . The micronaire is influenced only minimally by gin machinery, but the length is affected by the degree of drying and cleaning. The color of the cotton is strongly influenced by the weathering effects in the field. Gin machines, especially lint cleaners , tend to comb and blend the cotton and have been shown to improve the color grade .

Cleaning machinery improves the color grade and leaf grade of lint cotton by removing foreign matter and by blending the cotton. As the machines clean and blend, they change the fiber length. They also remove some lint that could be included as marketable lint, thereby reducing the lint turnout. Lint turnout, normally expressed in percent, is the ratio of the weight of lint to the weight of the seed cotton before removal of the cottonseed moisture, and foreign matter. Lint turnout is a function of the genetic characteristics of the cotton and of the amount of foreign material in the cotton. Thus, the return to a producer for a given quantity of seedcotton with a specific staple length and micronaire is a function of the lint turnout, color grade, and leaf grade .

Dynamic programming is used to model the ginning process to determine which combination of ginning operations maximize the return from the cotton. Dynamic programming can be applied to many problems that can be structured as a multistage system, and ginning can be considered a multistage system in which each operation represents a stage. A schematic of the ginning process is shown in FIG. 1. The gin stand 150 and bale press 170 stages are always required, and the other processes are optional.

In dynamic programming, the state of the cotton as it moves through the gin must be described. This description is accomplished with six state variables: foreign matter (leaf); Rd and +b, together representing color; moisture content (percent) ; staple length (inches) ; and turnout (percent) . These variables are designated herein as LF, RD, PB, M, LN, and T, respectively. The decision at each operation depends on the state of the cotton entering that operation. Once the solution to the total problem has been obtained, the decisions can be related to the state of cotton when it enters the gin. Thus, the optimum decision at each operation can be determined from the initial state of the cotton. The objective of dynamic programming model 1020 is to maximize the net return; i.e., the revenue from the lint cotton minus the costs of the ginning operations. The variable "Fi ( RD_j, PBi, LFi LNi i Ti ) " is used to represent the net return from 100 pounds of seed cotton, assuming that cotton enters the gin just before operation i, that it is in state "RDi, PB_i; LF_± LN_i M_±ι T_A " and that optimal decisions are made at operation i and at all operations that follow it in the gin. Any revenues or costs that do not vary with the decisions (e.g., revenue from seed cotton and cost of operating the gin stand) are not included, since they will not affect the optimum decisions.

The operations of the gin alter the state of the cotton. The state at the output of any operation i, is a function of the input state and the decision (D) at that operation: i.e.,

RD! = t, (RD, , PB, , LF, ,LN, , M, , T, . D.) • PB! = t, (RD, , PB, , LF, , LN, , M„ T, , D.) , LF! = (RD, , PB, , LFi, LN, , M, , T, , D.). LN,' =/, (RD, , PBi , LF, , LN, , M, , T, . D.) , Mi = t, (RD, , PB, , LF, , LN, , M, , T, , D.) ,

and T.' = t, (RD, , PB, , LF, , LN, ,M,,T,, D.) ,

where RD, ,PB1,LF!,LN! '.hi!, and T, represent the output state variables. The transition functions for each operation may be represented by performance tables or equations, as discussed in more detail below. The output state of one operation is the input state of the following operation.

Dynamic programming is based on the "principle of optimality, as discussed in Bellman, R. Dynamic Programming, Princeton University Press, Princeton, New Jersey (1957). The reference states that "[a]n optimal policy has the property that whatever the initial state and initial decision are, the remaining decisions must constitute an optimal policy with regard to the state resulting from the first decision." This "principle of optimality" leads to the following recursive equations:

F,(S,) = Max[ F,(S,,D,)] D,

and

F,(S ,)= Max [ R, ( S, , D,)+ F,., (Sf) J D,

for i = 2, N

subject to S, = t,(S,,D,), where F = Function,

S = State variables,

R = Returns,

D = Decision, and t = Transition function. (R,(S,,D_ι) is the return for stage i. For the ginning problem, these returns represent the negative of the operating cost for each operation. State variable Si is a six-dimensional vector, ⁿRD,,PB,,LF,,U4,,M,,T, ■"

In the gin, the last operation is the press (See FIG. 1) . Thus, that operation is the first one to be considered in the dynamic programming formulation. There is no decision, and F_P(RD_P,PBP.LFP.LHP,MP,TP) is obtained as follows:

Fp(RDp.PBp.LFp. ip.Mp.Tp) = (T^p/ I00)x( PRICEfRDp.PBp.LFp. ip.Mp ))x!00.

where PRICE ( R∑)p , PBp _• LF , LNp ) = price per pound of lint of grade

CP = Final color; based on PB_P and RD_P, MP = Moisture content of the cotton at the press j

PBP = Plus b at the press,

LFP = Leaf at the press, TP = Turnout at the press,

LN/> = Length, and

RDP = Reflectance at the press Moving backward through the system shown in FIG. 1, the next operation is the lint cleaners. The decision at this operation is to use zero, one, or two lint cleaners. The number is determined from

F_p (RD_L,PB_L,LF_L,LN_L,M_{L L}), for D_L = 0 or

F_L(RD_L,PB_L,LF_L,LN_L,M_L,T_L) - -E_L (RD_L,PB_LlLF_L,LN_L,M_L) x D_L x COSTE ÷ F_P (RD ,PB[,LF ,LN[,M ,T_L') for D_L = 1 or 2 with the following transition functions:

and

where F = Function,

RD = Reflectance,

PB = Plus B,

LF = Leaf,

LN = Length,

M = Moisture,

T = Turnout ,

E = Energy,

D = Decision, t = Transition function,

L = Lint cleaner, and

COSTE = Cost per unit of electricity.

E_L (RD_L , PB_{L >} LF_L , _L , M_L ) , the amount of electricity required to operate one lint cleaner, varies with the color, trash, length and moisture content of the cotton at the input of the lint cleaners. The electrical energy consumption (W-h/kg) for the various types of gin machinery as a function of color grade, leaf grade, and moisture content is shown in Table 1. COSTE is the cost per unit of the electricity. At the gin stand, no decision is to be made since the gin stand must be included. However, the gin stand changes the state of the cotton so it must be included in the analysis. Thus,

FG(RDG,PBG,LFG,LNG>MG>TG) ⁼ FL(RDG,PBG,LFG^/,LNC^,,MC,TG),

RDG = to (RDG . PBc . LFG , LN_G . MG , To )

PBG = to (RDG , PBc , LFG . LNG » MG , To ) where LFG' = to (RDG , PBG . LFG , LNG , MG , To )

LNG' ⁼ to (RDG , PBG » LFG . LNG , MG , TG )

and

TG = tc(RDc , PBG > LFG , LNc , MG , TG ) ^■ In a manner similar to that used at the lint cleaners, the problem solving continues for one operation at a time. Gin model 1022 is used to solve the problem. In the program, the state variables for each operation are permitted to vary over the ranges and increments shown below:

As the problem is solved, the optimal decision for each possible input state is stored as a six-dimensional array or matrix in an ASCII file (gin decision matrix) . Thus, once the solution for the whole problem is completed, the program can start at the first operation (first drier shown in FIG. 1) with a particular input state, and then use the transition functions to move sequentially through the operations and identify the optimal decision for each one. Hence, the optimal ginning sequence can be determined from the state of cotton when it enters the gin.

Table 2 illustrates the possible decisions, transition functions, and optimal return functions for each ginning operation. In one embodiment of the present invention, the transition functions of Table 2 are implemented using a series of tabular values, such as those contained in Tables 3 through 15. Tables 3-15 were developed using three state variables, composite grade (G) , moisture (M) , and turnout (T) . Historically, the U.S. Department of Agriculture (USDA) graded or classified cotton based on human assessment of the color and trash content (leaf grade) of the cotton, as well as on the fiber length and micronaire. Prior to 1993, color grade and leaf grade were combined into a composite grade, and the market price of cotton was based on this composite grade. The tabular transition functions of Tables 3 through 15 provide performance tables for the various types of gin machinery based on the state variables of composite grade, moisture content, and turnout. For example, Table 3 quantifies the effect of one lint cleaner by providing the final composite grade as a function of the initial composite grade and moisture content. Similarly, Table 9 quantifies the effect of one lint cleaner by providing the turnout as a function of the initial composite grade and moisture content.

Tables 3-15 can be used to generate a gin decision matrix containing machine decisions as a function of moisture and initial composite grade. A typical decision matrix for a market price based on Strict Low Middling at $0.70 per pound and a maximum color grade of Middling is shown in Table 16. The machinery specified by the sequence codes in Table 16 is identified in Table 17. The gin decision matrix is written by dynamic programming model 1020 into an ASCII file that is read by process control decision and measurement program 1010. The machinery sequence file, such as that shown in Table 17, can be part of process control decision and measurement program 1010.

Table 18 shows a comparison of typical returns for the USDA recommended sequence and the model sequence generated by dynamic programming model 1020 and Tables 3-15. The dollar values are based upon an input of 1001b of seed cotton. Typically in the United States, 1500 lb of spindle harvested seed cotton is needed to produce a 500 lb bale of lint. Thus, the increased dollar value with use of the present invention can be on the order of $7- $23 per bale.

In a particularly preferred embodiment of dynamic programming model 1020, the six state variables of leaf, Rd, +b, moisture content, staple length, and turnout are used, and the transition functions of Table 2 are implemented through algorithms contained in subroutines of dynamic programming model 1020. A particularly preferred embodiment of dynamic programming model 1020 is contained in the attached microfiche appendix. This source code uses a set of state variables as follows :

These state variables appear throughout the source code with various suffixes that represent the processing stage at that point in the program. A suffix of "T" indicates the "INT" or initial condition of the variable; a suffix of "L" indicates the actual condition of the variable after processing through the respective machine; and a suffix of "M" indicates the maximum condition of the variable after processing through the respective machine. Before processing by a machine, each variable has an initial value . The variables are then processed through a machine using the transition functions to produce the "L" suffix variables. If the "L" suffix variable is better with the machine than without the machine, this variable then becomes an "M" suffix variable. The initial value for the next machine is set to be the value that came out of the previous machine . Subroutines OPT and OPTM carry out the transition and optimal return functions identified in Table 2 by cycling through the subroutines for the various machines. Subroutine OPT does a complete enumeration of all possible solutions. Subroutine OPTM retains the optimum or maximum values found from subroutine OPT.

In one embodiment, dynamic programming model 1020 operates in an "interactive" mode by evaluating the transition functions for only one specific value of each state variable, as input, for example, by the user. The computations are made based on one value for each state variable, and the optimum gin decision for that value of the state variables is generated. In this manner, the optimum gin decisions are being generated one at a time, in real-time. This embodiment of dynamic programming model 1020 is contained in file COTTON. C in the attached microfiche appendix. Alternatively, this embodiment of dynamic programming model 1020 can be implemented in the FORTRAN programming language.

In an alternate embodiment, dynamic programming model 1020 operates in a "batch" mode by generating decisions using the entire value range for each state variable. This embodiment of the program evaluates all possible combinations of state variables within the value and increment ranges given above, and generates all possible decisions which are stored in a gin decision matrix. The primary difference between this embodiment of dynamic programming model 1020 and that contained in file COTTON. C is in the MAIN routine which iterates to cover the entire range of values for the state variables . The MAIN routine for the batch embodiment is contained in file COTTONL.C in the attached microfiche appendix.

The data used by COTTON. C and COTTONL.C is contained in the attached files DRIER.DAT, GREENE. CCC, and UPLND.COL. The optimum decisions for the range of input cotton properties are output to two files: LCDEC95A.OUT; and SCCD95A.OUT. The data file LCDEC95A.OUT has the optimum decisions for the lint cleaner portion of the gin (between Stations 2 and 3) and data file SCCD95A.OUT has the optimum decisions for the seed cotton cleaning portions of the gin (between Stations 1 and 2) .

Gin control, including data collection and display, is implemented through the set of "C" language instructions contained in the seven ".C" files and 13 external included " .H" files discussed above in Section 3. a, using the decisions in LCDEC95A.OUT and SCCD95A.OUT. Data on the current operation of the gin is written to the files: BDATF.DAT; BA.DAT; and 0THER.DAT. These files are also read by the control program upon initialization to determine initial settings.

Each machine in FIG. 2 has a corresponding subroutine in dynamic programming model 1020. If the particular machine is not used in a sequence, then the set of state variables is unaffected by that machine. If the particular machine is used in a sequence, then the subroutine contains an algorithm that indicates how the set of state variables is affected by that machine. A particular machine may not affect each of the state variables so that only the affected variables are adjusted in the machine subroutine. For example, the various cleaners do not affect the moisture content of the cotton. Consequently, the moisture after each of the cleaners (SML) will be the same as the moisture going into that particular cleaner (SM) . As another example, driers have a great impact on the moisture content of the cotton, but do not affect the color. Consequently, the Rd and +b after a particular drier (SRDL and SPBL) will be the same as the Rd and +b going into that particular drier (SRD and SPB) . Although length and turnout are not measured parameters, the change to the reference or default value of these state variables is computed since they are affected by the gin machinery.

The particular algorithms used to quantify the effect on the cotton properties identified by the set of state variables are not absolute, and can be varied by one of skill in the relevant arts to account for differences in machinery configuration, machinery wear and tear, and the cotton varieties typically processed. The following algorithms are exemplary, and it is to be understood that the present invention is not limited to use of the algorithms that follow.

In one embodiment, the cotton properties identified by the set of state variables are affected by a cylinder cleaner (subroutine CC) as follows:

SLFL = -0.1305 - 0.0619 * SM + 1.0599 * SLF

SML = SM

SRDL = 3.4151 - 0.0008 * SM + 0.9606 * SRD

STOL = -0.6071 - 0.0057 * SM + 1.0127 * STO

SLNL = 0.2557 - 0.0012 * SM + 0.7764 * SLN

SPBL = 2.8104 - 0.0137 * SM + 0.6457 * SPB In one embodiment, the cotton properties identified by the set of state variables are affected by a gin stand (subroutine GINSTD) as follows:

SLFL = SLF

SML = SM

SRDL = 19.52 - 0.12 * SM + 0.75 * SRD

STOL = 9.22 + 0.14 * SM + 0.72 * STO

SLNL = 0.31 + 0.002 * SM + 0.72 * SLN

SPBL = 1.50 + 0.02 * SM + 0.81 * SPB

In one embodiment, the cotton properties identified by the set of state variables are affected by an impact cleaner (subroutine IC) as follows:

SLFL = -0.1305 - 0.0619 * SM + 1.0599 * SLF

SML = SM

SRDL = 3.4151 - 0.0008 * SM + 0.9606 * SRD

STOL = -0.6071 - 0.0057 * SM + 1.0127 * STO

SLNL = 0.2557 - 0.0012 * SM + 0.7764 * SLN

SPBL = 2.8104 - 0.0137 * SM + 0.6457 * SPB

In one embodiment, the cotton properties identified by the set of state variables are affected by one lint cleaner (subroutine LC) as follows:

SLFL = -0.6665 + 0.0937 * SM + 0.8296 * SLF

SML = SM

SRDL = 25.9279 - 0.0834 * SM + 0.6757 * SRD

STOL = -8.0604 - 0.1694 * SM + 1.2043 * STO

SLNL = 0.1742 + 0.0003 * SM + 0.8288 * SLN

SPBL = 3.3751 - 0.0222 * SM + 0.5970 * SPB

In one embodiment, the cotton properties identified by the set of state variables are affected by two lint cleaners (subroutine LC) as follows:

SLFL = -1.0150 + 0.1483 * SM + 0.7278 * SLF SML = SM

SRDL = 38.1983 - 0.2905 * SM + 0.5302 * SRD

STOL = -12.6405 - 0.1969 * SM + 1.3191 * STO

SLNL = -0.0520 + 0.0003 * SM + 1.0266 * SLN

SPBL = 2.3649 - 0.0183 * SM + 0.7439 * SPB

In one embodiment, the cotton properties identified by the set of state variables are affected by a stick machine (subroutine STMCH) as follows:

SLFL = 0.1625 - 0.0710 * SM + 1.0326 * SLF

SML = SM

SRDL = 2.3777 - 0.0299 * SM + 0.9736 * SRD

STOL = 1.8168 - 0.0011 * SM + 0.9419 * STO

SLNL = 0.1996 - 0.0003 * SM + 0.8226 * SLN

SPBL = 1.8629 - 0.0025 * SM + 0.7587 * SPB

In one embodiment, the cotton properties identified by the set of state variables are affected by a drier (subroutine DRIER) as follows :

SLFL = SLF

SRDL = SRD

STOL = STO* (1.0- (SM-SMD/100.0)

SLNL = SLN

SPBL = SPB

SML = 4.2767 + 0.6397*SM - 0.1713*TEMP where TEMP represents the temperature of the drier.

A table of values can also be used to determine the affect on moisture of the drier (see Table 19) . Table 19 includes the moisture content after drying at temperatures of 65.5, 93.2, 120.9, and 131°C as a function of initial moisture content before drying. This data is accessed by dynamic programming model 1020 through the DRIER.DAT file in the microfiche appendix. If the moisture of the cotton that is input to the drier (SM) is in the range of 4-14%, then subroutine TABLI2 determines the moisture content of the cotton after drying (SML) . If the moisture is out of range, then the closest in-range value (either 4% or 14%) is used as a default. To control the moisture content, the present invention can be configured to vary the temperature of the driers, for example in increments of 50 F. The present invention can also be configured to bypass all of a drier, or to use a portion of a drier, for example Λ (6 shelves) or . (12 shelves) .

Dynamic programming model 1020 uses a standard subroutine,

GINCOM, for variable dimensions and declarations to ensure that all information is in the same format. A subroutine CHGSYS is provided so that a user can input the status of the gin machines .

For example, if a particular machine is not available in the gin, the user can input this information so that this machine is not included in the optimization sequence. In this manner, the present invention can be customized for use in various gins with varying configurations of ginning machines.

The monetary return or value of the cotton is calculated by the function CLINT. One example of price structure 1024 is included in the GREENE. CCC file in the attached microfiche appendix. The GREENE. CCC file contains premiums and discounts that are used to adjust a base price of cotton. The premiums and discounts in the GREENE.CCC file are for a given color grade, leaf grade, and staple length as set by the Commodity Credit

Corporation (CCC) . The base price of the cotton is coded into dynamic programming model 1020 as the cost per pound, and the values in the GREENE. CCC file are divided by 100 and added to the base price. Negative entries in the GREENE. CCC file represent discounts that reduce the base price. Price structure 1024 may be from any source, as long as it is in a format compatible with dynamic programming model 1020. FIG. 18 shows an output of optimum ginning decisions from dynamic programming model 1020. "Input States" refers to the state of each of the state variables at the input to the machine listed in that row of the table. The OUTPUT line identifies the value of the main variables after processing in accordance with the decisions for each machine as identified in the "DEC" decision column (a "0" indicates the machine is not used; a "1" indicates the machine is used; for the driers, "0"=no drier; "1"=150°F;

^»2"=200°F; "3"=250°F; and ⁿ4"=300°F).

Table 18a shows a comparison of typical returns for the USDA recommended sequence and the model sequence generated by dynamic programming model 1020 using the algorithms described herein. The dollar values are based upon an initial input of 100 lb of cotton, having a price of $0.7960 per pound. The increase in dollar value using the system and method of the present invention can be on the order of $13-$34 per bale.

As discussed in Anthony, W.S. and S.T. Rayburn, Cleanabili ty of Smooth- and Hairy-Leaf Cottons - - Quality Effects, Transactions of the ASAE, Vol. 32, No. 4, pp. 1127-1130 (1989), the leaf hairiness of cotton affects its cleanability. The cleaning efficiency of cleaning machinery is lower for hairy-leaf varieties of cotton than for smooth-leaf varieties of cotton. This characteristic impacts two of the state variables that are used by dynamic programming model 1020, i.e., trash and turnout. The other four state variables are unaffected by this characteristic, and are the same for smooth and hairy leaf varieties of cotton. Because of this cleanability characteristic, the transition functions or performance algorithms for smooth- and hairy-leaf varieties have statistically different coefficients for trash and turnout . Using algorithms that take into account this cleanability characteristic reduces the need for error feedback. The predicted values of the state variables more closely approximate the actual values of the state variables when separate algorithms having different coefficients are used for smooth- and hairy-leaf varieties of cotton.

In a further embodiment of the present invention, two sets of algorithms are used, one for smooth-leaf varieties of cotton, and one for hairy-leaf varieties of cotton. In such an embodiment, the variety of cotton (part of the module tag data) is input to computer system 240 either directly, or via network 418 from the gin computer (see Section 3. a.v. above) . Process control decision and measurement program 1010 uses a lookup table to identify by variety of cotton, a reference staple length and whether that variety is smooth-leaf or hairy-leaf . The values in such a lookup table would be readily apparent to one of skill in the relevant art. Dynamic programming model 1020 then uses the reference staple length and the appropriate smooth-leaf or hairy- leaf algorithms to generate the optimum gin decisions. A default of hairy-leaf, and a staple length of 1.12 inches, are preferably used if no variety is input.

In a preferred embodiment, the smooth-leaf algorithms are obtained by modifying the algorithms, i.e., the coefficients of the state variables, given above as follows. Any equation not changed remains as given above .

Cylinder Cleaner

SLFL = 0.0538 - 0.0913*SM + 1.0617*SLF

STOL = -0.6839 + 0.0098*SM + 1.0119*STO

Impact Cleaner

SLFL = 0.3634 + 0.0128*SM + 0.8572*SLF

STOL = 0.8109 - 0.0606*SM + 0.9784*STO

One Lint Cleaner

SLFL = -0.1213 + 0.0395*SM + 0.7488*SLF

STOL = -15.5084 - 0.1566*SM + 1.4290*STO Two Lint Cleaners

SLFL = -0.6638 + 0.1320*SM + 0.6425*SLF

STOL = -20.4123 - 0.1928*SM + 1.5585*STO

Stick Machine

SLFL = 0.3564 - 0.0643*SM + 0.9573*SLF

STOL = -0.4192 + 0.0490*SM + 0.9997*STO

In a preferred embodiment, the hairy-leaf algorithms are obtained by modifying the algorithms, i.e., the coefficients of the state variables, given above as follows. Any equation not changed remains as given above .

Cylinder Cleaner

SLFL = -0.4301 - 0.0259*SM + 1.0709*SLF

STOL = 0.0035 - 0.0257*SM + 0.9993*STO

Impact Cleaner

SLFL = -0.0675 + 0.0249*SM + 0.9544*SLF

STOL = 0.7170 - 0.0441*SM + 0.9778*STO

One Lint Cleaner

SLFL = -1.0871 + 0.2083*SM + 0.8256*SLF

STOL = -18.4213 - 0.2101*SM + 1.4888*STO

Two Lint Cleaners

SLFL = -1.2258 + 0.2098*SM + 0.7387*SLF

STOL = -36.5362 - 0.2445*SM + 1.9773*STO

Stick Machine

SLFL = 0.0965 - 0.0476*SM + 1.0501*SLF

STOL = 3.8250 - 0.0628*SM + 0.8955*STO

In yet a further embodiment of the present invention, the error feedback data (Error₁₂, Error₂₃ and associated predicted values) are used to modify the coefficients of the state variables in the algorithms. This reduces the amount of error, and Error₁₂ and Error₂₃ would eventually approach zero with predicted values equal to actual values . One way to modify the coefficients in the algorithms using the error feedback data is through the use of a neural net . By neural net is meant a computer program that recognizes patterns and is designed to take a pattern of data and generalize from it . A neural net typically takes pairs of input and output data and matches them, thereby "training" the neural net. Once a neural net has been trained, new data can be input and the net will output a learned response. Neural nets can readily be integrated by one of skill in the art into an existing computer program. A neural net could thus be used to match or correlate algorithm coefficients with error feedback data so that the error was minimized. Once the neural net was trained with matched algorithm coefficients and error feedback data, the algorithms could be determined as a function of the error feedback data generated during operation of the present invention, c. Process Control Implementation Program 1030 In a preferred embodiment, process control implementation program 1030 is implemented using the C programming language as part of process control decision and measurement program 1010. The embodiment of process control decision and measurement program 1010 attached hereto in the microfiche appendix includes the code for carrying out process control implementation program 1030. Alternatively, implementation program 1030 may be a separate program that is called by process control decision and measurement program 1010. Program 1030 performs the function of implementing the selected optimum gin process control decision, as indicated by 1032 (see FIG. 10) . To implement the optimum gin process control decision, program 1030 controls valves, such as the automated directional valves of the present invention, to route the cotton through the selected machinery sequence, as shown at 1036. Program 1030 uses valve position sensor data 1034 to verify proper valve position. If a change of valve settings is to be made, program 1030 uses valve position sensor data 1034 to determine what change needs to be made. The appropriate valve control signals 1036 are sent to cause power units, such as air cylinders, rotary actuators, hydraulic motors, electric motors, etc. to be activated to change the position of the valves.

In the preferred embodiment, PLC 2050 (see FIG. 20) is used to send valve control signals 1036 to change the position of the valves. Program 1030 causes signals to be sent from computer system 240 through digital interface 2040 to PLC 2050 to control the valves that put the selected machinery sequence on-line. Lines D17 and D18 output from digital interface 2040 are used by computer system 240 to request that selected lint cleaners be put on-line. Lines D30 and D31 output from digital interface 2040 are used by computer system 240 to request that selected seed cotton cleaners (e.g., impact cleaners and stick machines) be put online. Output line D19 is used by computer system 240 as a handshake line with PLC 2050 to ensure that the request is valid.

With reference to the C language program contained in the attached microfiche appendix, the PLC_scc and PLC_lc procedures are used to control the signals sent to PLC 2050 that control the request for seed cotton cleaning equipment and lint cleaning equipment, respectively. Depending on the function passed to each procedure, it can either: (1) set the handshake signal (D19) to untrue, meaning the value on the request lines (D17, D18, D30, and D31) is invalid and no change should be made; or (2) set the handshake signal to true, and set the request lines for 0, 1, 2, or 3 cleaners, meaning that the value is valid and the bits represent proper data for the number of cleaners (seed cotton or lint) to be used.

PLC 2050 is programmed to carry out the instructions generated by process control implementation program 1030. PLC 2050 is programmed to continuously check the settings of the cleaner request lines (D17, D18, D30, and D31) while computer valid line (D20) remains true, and after handshake line D19 returns to true . If the settings of the cleaner request lines have changed, and the switch on ginner' s control panel 2060 has been selected for automated control, then PLC 2050 initiates the change in valve settings required to carry out the request for the selected machinery. Once a change in valve settings is initiated by PLC 2050, further changes are not accepted by PLC 2050 until the current change is complete .

In some gins, the ginner may turn power off to certain machinery that is usually in the bypass configuration, such as seed cotton cleaners in excess of the number typically used. In that situation, PLC 2050 may be programmed to check if power is applied to a particular piece of machinery before signaling the valve for that piece of machinery to change from the bypass position to the diversion or on-line position.

Valves are used to control the flow of cotton through the gin. The valves are positioned to route the cotton through a selected machine (the diversion position with the machine on-line in the cotton flow) , or to route the cotton so that it bypasses a particular machine (the bypass position) . Particularly preferred valves are the automated valves of the present invention, described above with respect to FIGS. 5-9. Proximity switches or sensors are installed on the valves that control the flow of cotton. Suitable proximity switches include those that are installed on the outside of an air piston cylinder to sense the position of the piston in the air cylinder that is used to control the position of the valve (see, for example, air cylinders 621, 623, and 629 in FIG. 6) . Other suitable proximity switches include commercially available reed relay and magnet switches.

With such a proximity switch, the magnet is preferably mounted on the shaft of the valve . The reed relay and magnet switches are more sensitive to valve position, more flexible in mounting position, and more sensitive for detecting a larger range of error conditions. A particular valve may be equipped with more than one proximity switch or sensor so that the system could detect whether the valve is positioned in the fully opened or fully closed position. Internal sensors on the cylinders and actuators could alternatively be used.

To change the position or setting of a particular valve, PLC 2050 sends a signal to the air cylinder controlling that valve to either extend or retract, thereby changing the position of the valve in the desired manner. The interface between the air cylinder and PLC 2050 can be done in a conventional manner, and is omitted for brevity. To ensure that the valve is in the desired position, PLC 2050 reads valve position sensor data 1034 to determine the actual valve position. While the position of a valve is being changed, valve position sensor data 1034 indicates that the valve is neither open nor closed. If the valve becomes jammed, or cotton prevents the valve from moving fully into the requested (open or closed) position, PLC 2050 senses an error condition. The error condition signals for operator assistance.

Computer system 240, through the use of PLC 2050, controls the opening and closing of the automated valves of the present invention. PLC 2050 is programmed to sequence the valves to transition from the bypass mode of operation to the diversion mode of operation, and to sequence the valves to transition from the diversion mode of operation to the bypass mode of operation. With the automated valves of the present invention (see FIGS. 5-9) , the valves are transitioned without stopping the flow of cotton through the gin. Computer system 240 directs PLC 2050 to change the positions of the automated valves of the present invention while cotton is flowing through the system. To accomplish this, control hardware is provided at ginner * s control panel 2060 that preferably includes a thumbwheel switch that can be set to indicate the number of lint cleaners being used. For example, a thumbwheel switch setting of "0" would indicate that no lint cleaners were being used, a setting of "1" would indicate one lint cleaner, etc. The control hardware also preferably includes a push button switch to lock in the lint cleaner selection made through use of the thumbwheel switch. In a preferred embodiment, a series of indicators is included in the control hardware . Each of the lint cleaners has an indicator that indicates whether that lint cleaner has been selected for operation. A "not ready" indicator is also preferably provided that comes on when a new lint cleaning configuration is chosen and stays on until all the valves have been set and the system is ready to resume ginning.

In addition to the automated computer control of the valves through PLC 2050, a set of switches can directly communicate with PLC 2050 to allow the gin operator to select any or all of the valve settings, overriding whatever optimum selection has been indicated.

FIG. 19a shows a ladder diagram for programming a PLC to sequence the valves to transition between the diversion and bypass modes of operation. On the ladder diagram shown in FIG. 19a (and 19b discussed below) , each line where a function or action is performed starts with a set of double lines that represents a relay or switch contact. If the contact is closed, the function on that line is executed. A relay is indicated in FIGS. 19a and 19b through the use of ( res ) or ( set ) .

The main program is contained in lines 01 through 04 of FIG. 19a. Line 01 starts by determining whether the control computer is okay. Subroutine 01 is called to determine if the control switch settings have changed. Line 02 starts by determining whether there is a new control switch setting. This contact is labeled "0101" which corresponds to the "new setting" relay in line 06. Line 02 turns on the "not ready" light and calls subroutine 02 to decide the outputs for the new valve settings.

Line 03 includes a timing relay, represented by two lines enclosing a "T" and spaces for the number of the relay. Above the relay is a number for the delay time in seconds, typically 5-15 seconds. The timing relay in line 03 is used to allow a delay between the changing of each valve. This prevents the valves from physically interfering with each other, and also prevents small voltage surges and errors. After the valves are set, subroutine 03 is called to check if the valves are set properly.

Line 04 is executed last. The indicators for the lint cleaners being used are set, and the "not ready" light is turned off.

Subroutine 01 is contained in line 06. Line 06 includes a relay contact for the new control switch setting. Line 06 also includes two logic symbols, represented by "< >". The first is a "< cmp >" that compares the new switch setting to the old switch setting. The second is a "< sta >" that stores the new switch setting if it is different.

Subroutine 02 is contained in line 09. Line 09 sets new outputs for the valves. This is done by providing a control signal to the air solenoids that change the position of the valves . The correct sequencing of the automated valves to transition between the diversion and bypass modes of operation are carried out in subroutine 02.

Subroutine 03 is contained in line 12. The "check valve settings" contact in line 12 represents several contacts that correspond to the proximity switches used to verify that each valve is in the proper position.

The process control system of the present invention can also be used in a gin that is not equipped with the automated valves of the present invention. Such an embodiment is referred to herein as the semi-automated valve embodiment. In the semi- automated valve embodiment, the existing valves in the gin are equipped with actuators or air cylinders, as well as proximity switches or sensors . The actuators and proximity switches are connected to PLC 2050, in a manner similar to that described above for the automated valves of the present invention. The primary difference between this embodiment and the automated valve embodiment described above, is that the flow of cotton through the system has to be stopped in order for PLC 2050 to control the changing of valve position. In the semi-automated valve embodiment, the PLC is programmed to perform the following functions: sequentially stop gin stand 150; allow the cotton to clear the valves; redirect the valves; verify valve position; and signal the ginner to re-engage gin stand 150. FIG. 19b shows a ladder diagram for programming a PLC to carry out these functions .

The main program is contained in lines 01 through 04 of FIG. 19b. Line 01 starts by determining whether the push button switch has been pressed and released. If it has been, the contact is closed, and subroutine 01 is called to determine if the thumbwheel switch settings have changed. Line 02 starts by determining whether there is a new thumbwheel switch setting. This contact is labeled "0101" which corresponds to the "new setting" relay in line 06. Line 02 also includes a timing relay to delay to allow the cotton to clear the lint cleaners before the position of the valves is changed. Line 02 also includes a relay to stop the gin stand. Finally, line 02 calls subroutine 02 to decide the outputs for the new valve settings .

Line 03 includes a timing relay to allow a delay between the changing of each valve. This prevents the valves from physically interfering with each other, and also prevents small voltage surges and errors. After the valves are set, subroutine 03 is called to check if the valves are set properly.

Line 04 is executed last . The indicators for the lint cleaners being used are set, the "not ready" light is turned off, and the gin stand is re-engaged.

Subroutine 01 is contained in line 06. Line 06 includes a relay contact for the thumbwheel switch. This relay contact actually represents one contact for each of the switches in the thumbwheel. For example, if a thumbwheel is used that has four switches, the relay contact in line 06 represents four contacts, one for each of the four thumbwheel switches. Line 06 also includes two logic symbols, represented by "< >". The first is a "< cmp >" that compares the new switch setting to the old switch setting. The second is a "< sta >" that stores the new switch setting if it is different.

Subroutine 02 is contained in line 09. Line 09 sets new outputs for the valves . This is done by providing a control signal to the air solenoids that change the position of the valves .

Subroutine 03 is contained in line 12. The "check valve settings" contact in line 12 also represents several contacts, in a manner similar to the thumbwheel switch relay contact in line 06. The "check valve settings" contact represents several contacts that correspond to the proximity switches used to verify that each valve is in the proper position.

The source code provided herewith in the microfiche appendix is one embodiment for implementing the present invention. A computer programmer skilled in the relevant art could readily interpret and implement the present invention based on the disclosed source code. Examples and Results

The ability of the system and method of the present invention to increase returns to the cotton producer is demonstrated by the following examples. A sample run was made using the dynamic programming model of the present invention. Inputs to the model for the sample run were :

All calculations were based on an input mass of 45.4 kg (100 lb) of seed cotton.

The computer model generates a complete set of decision codes for each machine (gin decision matrix) for reflectance (50 to 80) , plus b (5.5 to 13.5), leaf (2 to 10), moisture content (3.5 to 9.5%), and lint turnout (30 to 40%). Output of the model also includes the final values for the state variables as well as the monetary returns at the completion of ginning. For the sample run with the inputs given above, the optimum machine sequence was two lint cleaners . Comparison of the model value to the values from the USDA-recommended machinery sequence is shown below.

Output Process Value from Control USDA-recommended value sequence

72.1

8.1

2.0

5.0

34.36

27.35

The decisions generated by the dynamic programming model 1020 of the present invention would yield monetary returns of $28.58 for an input of 45.4 kg (100 lb) of seed cotton, whereas the USDA- recommended ginning sequence would yield $27.35. The $1.32 additional return per 100 pounds of seed cotton would equate to $17.22 for the seed cotton (635.6 kg or 1400 lb) that would be necessary to produce a 500 pound bale of lint cotton. An additional example is shown in Table 18a, discussed above.

The process control system of the present invention results in improved fiber quality, as well as improved profitability. Control of fiber moisture and elimination of one or more stages of lint cleaning improves fiber quality by: (1) increasing length; (2) reducing short fibers; (3) increasing seed-coat fragment size and improving removability at the textile mill; (4) decreasing the number of seed-coat fragments; (5) increasing measured strength; and (6) increasing fiber yield. These improvements are documented and quantified in Anthony, W. Stanley, Process Control for Optimum Lint Quali ty and Value, 1992 Beltwide Cotton Conferences, pg. 7-12 (1992) .

Processing in a Textile Mill

The system and method of the present invention can also be used to process lint in a textile mill. Lint, the final product of processing in a gin, is further processed in a textile mill.

Mill processing can include, for example, cleaning of the lint, as well as blending, carding, combing, drawing, spinning, weaving, dyeing, and finishing.

One embodiment of a cleaning line in a textile mill is illustrated in FIG. 21. The cleaning line of FIG. 21 represents a typical opening and cleaning sequence in a textile mill. It is to be understood that some textile mills use a different sequence, and some mills have more cleaning machines than shown in FIG. 21. In a typical machine sequence at a textile mill such as that shown in FIG. 21, a bale opener 2102 extracts cotton from bales of lint cotton, such as that produced at a typical cotton gin, and feeds it into an airstream. A condenser 2104 separates the cotton from the air steam, and feeds the cotton into a pre-mixer 2106.

Pre-mixer 2106 mixes the cotton from several different bales at one time and feeds it into a double-roll cleaner 2108. Double- roll cleaner 2108 removes foreign matter, and feeds the cotton into a blender 2110. Blender 2110 ensures that the cotton is uniformly mixed and blended together. A condenser 2112 separates the cotton from the airstream, and feeds the cotton into a cleaner 2114 which removes foreign matter, and transfers the cotton to a dust cage 2116. Dust cage 2116 removes dust and feeds the cotton to a cleaner 2118. Cleaner 2118 removes foreign matter. A condenser 2120 then removes cotton from the airstream, and transfers it to a card feeder 2122. Card feeder 2122 feeds cotton into a card machine 2124. Card machine 2124 cleans cotton, and forms a web for further processing. The process sequence described above differs with manufacturers and textile mills as various combinations and models of the cleaning, separating and blending machines are used.

The present invention can be used in a textile mill to select an optimum mill machine sequence that maximizes lint quality. Automated directional valves as disclosed herein can be used to route lint through the selected sequence of cleaners. In a textile mill configured with the present invention, double-roll cleaner 2108, cleaner 2114, dust cage 2116, and cleaner 2118 can be bypassed. Bypassing of the foregoing machines is not possible in a conventional textile mill (without the process control system of the present invention) . Based upon the disclosure herein, one of skill in the relevant arts could readily implement the appropriate algorithms for use in a textile mill .

% Also includes the energy required to convey the lint cotton between machines.

Table 1, Continued. Natural gas energy required by either drier 1 or drier 2.

Energy (Btu/kg of cotton) required for drier temperature (°C) of

Initial lint moisture content, percent

14.0

12.0

10.0

9.0

8.0

7.0

6.0

5.0

4.0

Table 2. Possible decisions, transition functions, and optimal return functions for each ginning operation.

Operation Decision Transilion Junction" Qpjimal return function

Press None None F_p{RD_p.PB_p.LF_p.LN_p,M_p.T_p) -- (T_pnθO)X PRICE {RD_p.PB_p,LF_p,LN_p,M_p.T_p)X \00

Lmt cleaner 0 - none forO_t * 0' RD_l'RD_i.PB_L-PB_l.LF_L^LF_L for D_L >0 F_l(RD_L,PB_i,LF_L,LN_l.M_l,T_L) 'Maximum of F_p[RD_L,PB_i.LF_l,LN_L, LrV_l' =./.Λ/_l.M_l'^«M_l,τ{ ^« T_T M..T_L)

1-one Maximum of F_P(RD_L,PB_L

2 -two F_L.LN_L,M_{L L}) X D_L X COST E ♦

NO

Gm stand 1-onβ P.D' t_a(RD₀.PB_β,LF₀,LN₀.M..T₀) F_a(RD_a<PB₀.LF_a.LN_a.M_a,T_a) - _L(RD₀'.PB₀',L _α'. N M_{α 0}')

PB_β. - l₀iRD₀,PB₀.LF₀,LN₀,M_a,T_a) LF_β. - l₀(r70_β,P^β ₀,tF₀.l.N_β.M_β,r_β) tw;. - f_β(RD_β.Pfl_β.LF„.LrV₀, ₀.T_β) M₀' -- M₀ _a' - t₀'lRD₀,PB_a.LF_t,LN₀,M₀.T₀)

Impact cleaner 0-do not use for D, =^■ 0. RD, • RD,,PB, • PB,,LF, = LF₍, forO, = 0:F,(RD₍,Pβ,,..F,,-.Λι,,M,.r,) = Maximum of F_α(RD„PB_l,LF,.LN_l,M,.T_l) LN,' ^• LN,, M,' = M,, r,' » r,

1-use forO, « 1: RO, « f₍(RO,,PB₍._.F,,_.rV„M₍, T,) for O, * 1 F,(RD,_lPa₍.LF_r.LΛ/,,M_|ir,) = Maximum of F_DI(RD,,PB,.LF„ LN,. M,.T,)

Pβ_l'-f_l(ΛO,₁Pβ_/.LF_|.LW,.W_l.T-,) or -E_l{RD_l,PB_l,LF_l,LN_l,M_l,T,) X COST E ♦ F„ (RD/.Pfl/.LF/./ V/.W,. T,')

LF/=f,(RO,₁PB,.lF,.I.Λ/„M_/.r₎) t Λ/ « f,(RD,, Pβ₍. LF,.LN,.M_I. T,)

M,' • M,.r,' - f,'(RO,.P0_/.tF,,t.fV,.M₍.r_/)

Table 2. Possible decisions, transition functions, and optimal return functions for each ginning operation - contlnuad.

Operation Decision Transition function^* Optimal return function

Oner 2 0 - do not use for D_n, • 0: RD_D. = RD O_nf,.PB -DI PB, ^{,of D}o, " ° ^Fo,(^RD ₀r^PBo.-^LF.yl-N_D,.M₀₁.T_D,) - Maximum 0/ ₍(RO_D,.PB_c

I ,., LN 01 LN

^LF," 01' ^LFo,'^L»or^Mo ^To,)

M. = r

1 • use at 6S^*C lo ^Fo,W_D,-™_DrLF_DJ,LN_{D D1}.T_D,) »

2 - use at 93'C Maximum of F₀₁{RD_M,PB_Di,LF_ot,LN₀₁.M_D„T_Di) or

3 use at 121'C -£_l{RD_D,.Pβ₀,.LF_0}.LrV_e,,M₍„) X Cosf E - Gas (M₀₎,D_DI) • use al 131'C X Cost (RD,PB,LF,LN.M,T) ^♦ F, iRD_o PB_0VLF_ot,LN_Dt,M_t

Slick machine 0 - do not use for D. 0: RD. RD_s,PB_t « PB_j (or D_s ^« 0: F_t (RD^Pβ_j.LF_j.Lr _j.M,,!,) =

LF. LF_S,LN, = LN_S, Maximum of F_OI(RO_J,PB_J,/-F_J,LΛ_J.M_J,r_j)

1 - use torD, * 1:RD,.

PB_S',

LF_.

LN_a',

M. M.

T; - t, (RD_s.PB_s.LF_t.LN_t.M_s.T_s)

Cylinder cleaner ^■do not use for D_c ^« 0: RD_e = R

Table 2. Possible decisions, transition functions, and optimal return functions for each ginning operation - continued.

Operation Decision Transition function* Optimal return (unction

1 - use for D_c * 1'RD_j * f_c(RD_c,PB_c.-F_c.LfV_c.M_c,r_c). lor D_c = 1: F_C{RD_C.PB_CXF_C,LN_C.M_C,T_C) Maximum of F_SIRD_C,PB_C.LF_C PB_C' - I_C{RD_C.PB_C.LF_CILN_C,M_C.T_C), LN_C,M_C,T_C) or -E_t {RD_C,PB_C.LF_C.LN_C.M_C, T_e) X

LF f_c(RD_e.Pfl_c. F_c.L/V_c,M_c,r_c). COST E * F_t

LN_C - t_c(RD_c,PB_c,LF_c,LN_c.M_e.T_e),

M' M„ T - f'(RD,.Pβ_c.LF_c.

Drier 1 0 - do nol use for D_D, = 0. RD₀'₁ RD_0I for 0, = 0: F₀, [RD_ol.PB_ot,LF₀,.LN₀,.M_ot.T_Oi) = Maximum of F_C(RD₀,,PB_D, PB_D, PB_D, LF₀„LN_D„M₀„T_ot)

NO

LF, LF_D,.

LN, LN_n.

^01 ° **OI' ^0

1 -use for D_0I «1.2.3, or A- for D_D, «1,2,3,or4 F_D,{RD₀₁.PB_D LF_D,,LN₀,,M_D,.T₀,) ■= Maximum of

RD₀, - l_D,{RD_Dl.PB_D„LF_DI,LN_Di,M_Dt.T_DI) F_ciRD_ol.PB_D„LF_D,_%LN₀„M_D„T_0i) ot PB_D, = t_o,iRD_D„Pβ_Dl.LF_D„LN₀„M₀,,T_DI) -E_LIRD_D,,PB_D,,LF_DI.LN_0I.M₀,) X COST E - GAS (M_DI< LPόi " to,l^RDo,_> ^p _D,-<-^Fo,-l-^No,'M₀„T_D,) D_0I) X COST G ♦ F_C[RD_D,,PB_D„LF₀,,LN₀₁,M₀„T_D1) LN₀, - t₀,(RD₀,,PB_D,.LF₀,.LN_D,.M_D„T_0l) ' 'o,(^Wo.. ^DO,)- ^rό, ' T_D, - M_D, ^♦ M_D,

' Tabular values for the transition function are given in Tables 3-15.

Table 3. Final grade, as a function of initial grade and moisture, when only one lint cleaner was used.

Final grade for moisture content (percent) of

Initi al 3.5 4.5 5.5 6.5 7.5 8.5 9.5 grade

Table 4. Final grade, as a function of initial grade and moisture content, when two lint cleaners were used.

Final grade for moisture content (percent) of

Initial grade 3.5 4.5 5.5 6.5 7.5 8.5 9.5

72 93.2 92.2 91.2 90.2 89.2 88.2 87.2

74 94.1 93.0 92.0 91.0 90.0 89.0 88.0

76 94.9 93.9 92.9 91.9 90.9 89.8 88.8

78 95.7 94.7 93.7 92.7 91.7 90.7 89.7

80 96.6 95.6 94.6 93.5 92.5 91.5 90.5

82 97.4 86.4 95.4 94.4 93.4 92.4 91.4

84 98.3 97.2 96.2 95.2 94.2 93.2 92.2

86 99.1 98.1 97.1 96.1 95.1 94.1 93.1

88 99.9 98.9 98.8 97.8 96.7 95.7 94.7

90 100.8 99.8 98.8 97.8 96.7 95.7 94.7

92 101.6 100.6 99.6 98.6 97.6 96.6 95.6

94 102.5 101.4 100.4 99.4 98.4 97.4 96.4

96 103.3 102.3 101.3 100.3 99.3 98.3 97.3

Table 5. Final grade, as a function of initial grade and moisture content, when only one gin stand was used.

Table 6. Final grade, as a function of initial grade and moisture content, when only one impact cleaner was used.

Table 7. Final grade, as a function of initial grade and moisture content, when only one stick machine was used.

Table 8. Final grade, as a function of initial grade and moisture content, when only one cylinder cleaner were used.

Table 9. Turnout change, as a function of initial grade and moisture content, when one lint cleaner was used.

Table 10. Turnout change, as a function of initial grade and moisture content, when two lint cleaners were used.

Table 11. Turnout change, as a function of initial grade and moisture content, when only a gin stand was used.

Table 12. Turnout change, as a function of initial grade and moisture content, when one impact cleaner was used.

Table 13. Turnout change, as a function of initial grade and moisture content, when one stick machine was used.

Table 14. Turnout change, as a function of initial grade and moisture content, when one cylinder cleaner plus gin stand were used.

Table 15, Turnout change after either drier 1 or drier 2.

Turnout change (percent) after drier at

Table 16. Overall machine decisions for color of Middling with a price based on Strict Low Middling at $0.707pound

*Each alphabetic character represents a different sequence of gin machinery (See Table 17 for description).

Ill - Table 17. Machine and drier decision codes for dynamic gin model

Table 18. Comparison of typical returns for the USDA recommended sequence and the model sequence

* Based on 45.4 kg (100 lb) of seed cotton. Does not include energy costs. Multiply by

14 to determine per bale value, t Cylinder cleaner, impact cleaner, and two lint cleaners were used. i One drier at 66°C and one impact cleaner were used. § Two lint cleaners were used

I One drier at 66°C and two lint cleaners were used. ** Stick machine was used. tt No conditioning equipment other than gin stand and feeder was used. it One drier at 66°C was used.

Table 18a. Comparison of typical monetary returns for the USDA- recommended sequence and the process control sequence.

____———_—__—--_---———-__---———— — _'—

Initial values USDA sequence Process control sequence

Rd +b Leaf Rd +b Leaf XM¹ TO² LN³ Rd +b Leaf %M^> TO² LN³ i<

5.0 34.36 1.09 26.17 69.6 8.1 2.4 6.0 35.2 1.10 28.05

5.0 34.36 1.09 27.35 70.5 8.0 3.0 6.0 35.9 1.10 28.58

5.0 34.66 1.09 27.35 71.8 7.5 3.7 6.0 37.3 1.10 29.70

5.0 34.36 1.09 27.35 74.3 8.0 4.0 6.0 37.4 1.10 29.79

5.0 34.36 1.09 27.35 69.6 8.1 4.0 6.0 35.2 1.10 28.05

5.0 34.36 1.09 26.06 71.5 7.7 4.2 6.0 35.5 1.09 28.29

5.0 34.36 1.09 27.35 74.3 7.7 4.2 6.0 35.5 1.09 28.29

5.0 34.36 1.09 27.35 75.6 8.1 4.9 6.0 36.0 1.10 28.34

¹ Assumes limited drying. Initial moisture was 6%.

² TO = turnout, %

³ LN = length, %

⁴ Based on a base price of $0.7960 per pound (1995 Commodity Credit Corporation prices).

⁵ Based on 100 pounds of initial cotton, at least 1400 pounds are required to produce a 500-pound bale of lint.

⁶ Used two cylinder cleaners and two lint cleaners.

⁷ Used one cylinder cleaner and one lint cleaner.

⁸ Used one cylinder cleaner.

⁹ Used no cleaning.

¹⁰ Used two lint cleaners.

¹¹ Used one lint cleaner.

Table 19. Final moisture content after driers.

Initial moisture Drier temperature (°C) of content, percent 65.5 93.2 120.9 131

14.0 11.0 10.3 9.5 8.5

8.0 7.0 6.5

7.0 6.0 5.0

7.0 5.0 4.5

5.5 4.0 4.0

4.5 4.0 3.5

4.0 3.5 3.0

3.7 3.5 3.0

Conclusion

While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. For example, the present invention can be implemented in hardware only, or through the use of other programming languages. The present invention may also be adapted to process other types of materials, other than cotton. Multiple-leaf valves, high-speed sequential leaf valves, or other suitable types of diversion means may also be used. Thus, the breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.

"COMPUTER CONTROL LOGIC"

The following is a computer program listing showing a computer program which can be used to practice the present invention.

/* */ /* COTTON.c */ /* */ /* input file names were hardcoded */ /* (and assumed to be in current directory) they arβi */ /* Drier data : drier.dat */ /* Price data . greenccc.dat */ /* Grading data: uplndcol.dat */ /* */ /* */ /* */ /* */ /* GINCOM */ /* */

#include <atdio.h> #include <string.h> #inσlude <stdlib.h>

/*For abor () function in for failure to open fxle*/

#define TRUE 1 #define FALSE 0 int DR1 CCl SMCH IC1 DR2 CC2 IC2, LC; int IDR1M, ICC1M, ISMCHM, IIClM , IDR2M, ICC2M, IIC2M, ILCM; float DD[5], TM[37], TMX[5], TMY[10]_r GASUSD[5]j

float PRC[31][31]; int ICLR[31][31] j int ICOLOR[46][142]; int IPRICE[851[9H10]> float FX, FM, BPRICE, PRICE, PRICEM; int ICR, ICLRM, IPDR, IPGS;

/* */ /* Forward Declarations of functions */ /* (Given in order of appearance in the listing below) */ /* */ void READfilo (char FILENM[ 50 ] , float Xλ[ 10 ) , float YA[ 10 ] ,

vo »id main (void)

/* Reading drier data */

READfile(drier_file,TMX,TMY,TM,4,9);

/* */

/* Initialize Array */ for( IC=0 ; IC<=84 ; IC++) for(LG-0 ;LG<«8; G++) for(LN-0 ;LN<«9 ;LN++) /* if use -29999 then need to use different type of integer */

IPRICE[IC][LG][LN]=-29999;

/* Reading pricing data */ if( (price_data = fopen(price_file, "r" ) ) == NULL )

{ printf("*** The current directory does not contain the price datafilet %s\n", price_file); abor ( ) ;

} while(fscanf(price data, "%2d%ls%ld", &IC, &junk, S.LG) 1= EOF) for( N«0;LN<9;LN++) fscanf(price_data, ^H%d", &IPRICE[IC-11] [LG-2] [LN] ) ;

/* Reading grading data */ if ( (grade_data - fopen(grade_file, "r" )) ∞ NULL )

{ printf("*** The current directory does not contain the grading datafilci %s\n^M, grade_file); abort( ) ;

} do

{ check - fscanf (grade data, "%2d%3d" , £IRD,&IPLUSB) ; fscanf (grade data, "%2d%l3^H ,&ICOLOR[IRD-40] [IPLUSB-40] , S,junk) ;

} while(check 1- EOF);

/* Close input files */ if( fclose( price_data ) ) printf( "The price datafile was not closed. %s\n" ,price_file ); if( fclose ( grade_data ) ) printf( "The grading datafile was not closed: %s\n", grade_file ) ;

SLFLO = 2. Of; SLFMAX-lO.Of ;

SMLOW » O.Of; SMMAX =20.Of;

SRDLOW=50.0f; SRDMAX=80.0f ;

STOLOW=35.0 ; STOMAX»40.0f ;

SLNLOW- l.Of; SLNMAX= l.lβf;

SPBLO - 5.5f; SPBMAX-13.5f;

BPRICE = 79.6f;

SLFINT - β.Of;

SMINT = β.Of;

SRDINT ■» 56.Of;

/* Check to see if user wants to exit */ printf("\n\n Do you want to quit? (Y/N) => " ) ; scanf("%s" ,&quit); printf("\n\n") ; if(strcmp(quit,^,'Y")"==0 || strcmp(quit, "y")==0) run ^■ FALSE;

}

/* SUBROUTINE READ(FILENM,XA, YA,ARRAY,NDIMX,NDIMY) */

void READfile(char FILENM[50], float XA[10], float YA[10], float ARRAY[37], int NDIMX, int NDIMY)

{

FILE *input_file; float DUM[21][8],TAB[21][8]; int RT, IND; int i,j,k; if ((input_file « fopen(FILENM, "r" )) == NULL ) printf(-*** The current directory does not contain the datafile: %s\n" ,FILENM) ; abor ( ) ;

f βcanf (input_file, ^H%d" ,fiKT) ; or ( i^»l I i<«*NDIMX ; i++ ) fscanf (input_file, "%f", 8XA[i]; for(i=l; i<=NDIMY; i++)

fscanf (input_file,"%d %f^H,&KT, &YA[i]); for ( j=l ; j<=NDIMX; j++ ) fscanf (input_file,"%f",&DUM[i][ j]);

for( i=»1 ; i<«=NDIMY; i++) for( j=l; j<=NDIMX; j++)

{

IND=i+HDIMY* ( j-1 ) ;

ARRAY[ IND]=DUM[i] [ j ] ; } printf (" REPRODUCTION OF DRIER DATA \n ",KT); for(i-l;i<-NDIMX;i++) printf("%10.2f ",XA[i]); printf ("\n");

] [ j ] ) ;

if ( f close ( input file ) ) printf ( "The file %s was not

j

/* SUBROUTINE CHGSYS */

void CHGSYS (void ) int CV[ 9 ] , IX=0 ;

J

CV[6]«= CC2; CV[7]= IC2; CVf8)= LC; while(IX != 9)

{ printf("\n\n");

PRTSYS(); /* Write out the current module status to screen */ printf(" To change the status of an operation, enter the number\n") ; printf(" in parenthesis to the left of the operation -> "); scanf ("%d",&IX); while(IX < 1 I I IX > 9)

{ printf(" Must enter a 1, 2, 3, 4, 5, 6, 7, 8, or 9. Try again -> " ) ; scanf(^H%d",&IX); } if(IX >« 1 && IX <= 8) if(CV[IXJ)

CV[IX]=FALSE; else

CV[IX]=TRUE;

DR1 = CV[1];

CCl = CV[2];

SMCH= CV[3];

IC1 = CV[4];

DR2 = CV[5);

CC2 - CV(β];

IC2 * CV[7];

LC = CV[8];

/ * Bssssnzsas:

/* SUBROUTINE PRTSYS */

/* nnaansni void PRTSYS (void) { if(DRl) printf(" (1) Drier 1 In \n" ) ; else printf(" (1) Drier 1 Out\n" ) ; if(CCl) printf(" (2) Cylinder Cleaner in \n- ) ; else print (" (2) Cylinder Cleaner Out\n" ) ; i (SMCH)printf(" (3) Stick Machine In \n" ) ; olβe printf(" (3) Stick Machine Out\n" ) ; if(ICl) printf(" (4) Impact Cleaner 1 In \n" ) ;

void INTS (void)

{ int IX—9; float input_value, var_limit[14] j var_limit[0] =0.0f; var_limit[l] - 9«9.9...-O.f-.,; /* Price input limits **// var_limit[2) -SLFLO ; var_limitf3] =SLFMAX; /* Leaf input limits */ var_limit[4] =SMLOW; var_limit[5] -SMMAX; /* Moisture input limits */ var_limit[6] =SRDLOW; var_limit[7] -SRDMAX; /* Reflectance input limits */ var_limit[8] =STOLOW; var_limit[9] =STOMAX; /* Turn out

^"iinnppuutt lliimmiittss * ^w/t var_limit [10]"SLNLOW; var_limit[ll]=SLNMAX; /* Length input limits */ var_limit[ 12]=SPBLO ; var. _nli-m.i*+tπ[ 13-Ji]->,_S _p.B.MAX; /* Plus B ^"input limits */ while(IX ! 8)

{ printf(^M\n\n\nlnitial Values t\ snn") ); printf(" (1) Base price $%5.2f\n",BPRICE); printf (" (2) ^" Leaf' %5.2f Range ( %5.2f - %5.2f )\n", SLFINT,var_limit[ 2 ) , var_limit[ 3 J ) ; printf (" (3) Moisture = %%55..22ff RRaannggee (( %ϊ5b..2ϋfr - %5.2f )\n",

SMINT,, v„a_r___limit[4] , ^■var_limit[5]); printf(" (4) Reflectance - %%55..22ff RRaannggee (( %%55..22ff - %5.2f )\n",

SRDINT,var :__lliimmiitt[[ 66 ]] ,, 'var_limlt[ .7_.].) ; printf (" (5) Turn out %5.2f RRaa ιnnngggeee (( %%55..22ff -- %%55..22ff ))\\nn"",, STOINT,var :__lliimιιit [ 8 ] , var_limit [ 9 ] ) ; printf (" (6) Length %5.2f Ra ιnnggβe („ %.5.2f - %5.2f ) \n" , SLNINT,var :_ lliimmiitt[|10 J ,var_limit [ ll ] ) l printf(" (7) Plus B - %5.2f Range ( %5.2f - %5.2f )\n",

SPBINT,var limit[12] ,var_limit[ 13] ) ; printf(" (8) Make no further changes.Yn" ) ; printf("\nTo change a value, enter the number in parenthesis\n" ) ; printf( "associated with the value to be changed -> "); scanf C%d",&IX); printf( "\n") ;

while (IX < 1 j I IX > 8)

{ printf ( " You must enter 1, 2, 3, 4, 5, 6, 7 or 8 => "); scanf("%d^H,&IX);

}

/* Use of "switch" statement to replace nested IF's in FORTRAN */ if(IX 1= 8)

{ switch(IX)

{ case 1: printf( "Enter a new value for Base price -> "); break; case 2: printf( "Enter a new value for Leaf -> "); break; case 3: printf("Enter a new value for Moisture -> "); break; case 4: printf("Enter a new value for Reflectance -> ⁿ);break; case 5: printf("Enter a new value for Turn Out -> "); break; case 6τ print ( "Enter a new value for Length -> "); break; case 7: printf("Enter a new value for Plus B -> " ) ; } scanf("%f" ,&input_wvalue);

/* Check input value to ensure it is within specified range */ if(input_value < var_limitr2*IX-2] ) printf("\n*** Value entered (%5.2f) is lower than the permited value (%5.2f) ***" "\n*** NO CHANGE WAS MADE. ***" ,input_value, var_limit[ 2*IX-2 ] ) ; else if (input_value > var_limit[2*ix-l] ) printf("\n*** Value entered (%5.2f) is higher than the permited value (%5.2f) ***'*

"\n*** NO CHANGE WAS MADE. *** ",input_value, var_limit[2*IX-l]); else switch(IX) case l . ii break;

C SΘ 2!»l break; case 3I:« break; caβo i break; case 51

break;

case 6: SLNINT=input_value; break; case 7: SPBINT-input_value; }

void OPT(void)

{

/* Counters and Upper bounds on the number of devices */ int IDR1, IDR1U = int ICC1, ICC1U - int ISMCH, ISMCHU- int IIC1, IIC1U - int IDR2, IDR2U - int ICC2, ICC2U = int IIC2, IIC2U - ; int ILC, ILCU - 2;

SLFL- SLFINTj SML » SM1NT SRDL- SRDINT; STOL- STOINT; SLNL= SLNINT; SPBL- SPBINT; if(lDRl ) IDR1U -0; if(iCCl ) ICC1U =0; if(ISMCH) ISMCHU-0; if(IICl ) IIC1U -0; if ( 1DR2 IDR2U ssO; if(tCC2 ICC2U -0; if(IIC2 IIC2U -0; if(ILC ILCU =0 ;

IPDR-0 ; IPGS-0;

/* DRIER 1 */ RECORD( 1 ) J for(IDRl^«-0)IDRK- >IDR1U;IDR1++)

{

UPDATE( 1 ) ; DRIER(IDRl); /* CYLINDER CLEANER 1 */ RECORD(2 ) ; for(ICCl=0;ICCK=ICClU;ICCl++)

{

UPDATE(2 ) ; CC(ICCl);

/* STICK MACHINE */ RECORD(3); for( ISMCH=0;ISMCH<==ISMCHU;ISMCH++)

{

UPDATE(3); STMCH(ISMCH);

/* IMPACT CLEANER 1 */ RECORD(4); for(IICl=0;IICl<=IIClU;IICl++)

{

UPDATE( ) ; IC(IICl);

/* DRIER 2 */ RECORD(5) ; for( IDR2-0;IDR2<=IDR2U; IDR2++)

{

UPDATE(5) ; DRIER(IDR2);

/* CYLINDER CLEANER 2 */ RECORD( 6 ) ; for(ICC2-0; ICC2<-ICC2U;ICC2++)

{

UPDATE( 6 ) ;

CC(ΪCC2);

/* IMPACT CLEANER 2 */ RECORD(7); for(IIC2-0; IIC2<-IIC2U; IIC2++) {

UPDATE(7);

IC(IIC2);

/* GINSTAND */ RECORD(8); GINSTD(IDR1,IDR2);

/* LINT CLEANER */ RECORD( 9 ) ; for(ILC=0 ; ILC<-ILCU; ILC++)

UPDATE(9 )

lint_cleaner(ILC) ; RECORD(10);

FX-CLIN (SLFL,SM ,SRDL,STOL,SLN ,SPB ) ; FX=FX- (IPDR+IPGS) *9000; /* This is a penalty that applies in some cases */ if(FX > FM fi.fi, FX > 0)

OPTM( IDRl , ICCl , ISMCH,IICl , IDR2 ,ICC2 , IIC2 , ILC) ; /* FM is the maximum value of the objective function to date for the run */ > } } }

/* SUBROUTINE RECORD(K) _ *

/* «»«e=-B-B=«=srs==--;:_:s:======,=-s=sB====β>-«-»««"""™"""™«=^M»=^l='»=--—^B====ss=-———⁼⁼ * / void RECORD(int k)

{

SLFT[k]- SLFL;

SMT[k] = SML;

SRDT[k]= SRDL;

STOTlk]- STOL;

SLNT{k]- SLNL;

SPBT[k]= SPBL; >

/ ★ »-.==============================-.-.——=«-===-«================== * /

/* SUBROUTINE UPDATE(K) */

/* ===5====β==βB«ββS.»=-B=«---=---«i-^β»-»-=««====!================-^!*===="=-^β= * / void UPDATE(int k)

SLF - SLFT[k]» SM = SMT[k]; SRD - SRDT[kj; STO - STOT{k); SLN ^β SLNT[k]; SPB - SPBT[k];

/* =»«»---.-.-.-«-----■.._„=--»================»==-=—————==^■====^■ * /

/* SUBROUTINE DRIE (IDR) */

/* Data for driers are for SM ranging between 4.0 and 14.0.

The subroutine does not call TABLI2 when SM is outside this range. Since the program evaluates IDR=0 first and the value of FX should be the same when TABLI2 is not called, the decision should be IDR«=0. */ void DRIER(int IDR)

{ if(IDR -» 0)

{

SLFL=SLF;

SML =SM;

SRDL=SRD;

STOL=STO;

SLNL=SLN;

SPBL=SPB;

} else if(IDR >= 1 £,& IDR <= 4)

{

SLFL=SLF; if(SM >= 4.0 && SM <= 14.0)

{

SML =TABLI2("M,TMX,TMY,DD[IDR],SM,4,9);

IPDR=0 ;

} else

IPDR-1 ;

SRDL=SRD;

STOL-STO* (1. Of-(SM-SML) /100. Of) ;

SLNL«=SLN;

SPBL⁼SPB• if(SML0ϊ > SML) SML = SMLOW; /* SML= AMAXl (SML,SMLO ) */ if(SMMAX < SML) SML - SMMAX; /* SML= AMINl (SM ,SMMAX) */ if(STOLOW > STOL) STOL = STOLO ; /* ST0L~AMAXl (STOL,STOLOW) */ } }

/* SUBROUTINE CC(ICC) * l

void CC(lnt ICC)

/* WITHOUT CYLINDER CLEANER * /

if (ICC 0) {

SLFL-SLF;

SML »SM;

SRDL=SRD;

STOL-STO;

SLNL«SLN;

SPBL=SPB;

/* WITH CYLINDER CLEANER */ else if(ICC »' 1)

{

SLFL ' -0.1305f - 0.0619f * SM + 1.0599f * SLF;

SML ^■■ SM;

SRDL ■ 3.4151f - O.OOOβf * SM + 0.960δf * SRD;

STOL ■ -0.6071f - 0.0057f * SM + 1.0127f * STO;

SLNL ' 0.2557f - 0.0012f * SM + 0.7764f * SLN;

SPBL ' 2.8104f - 0.0137f * SM + 0.6457f * SPB; if(SLFLOW > SLFL) SLFL«=SLFLOW; /* SLFL«AMAXl(SLFL,SLFLOW) */ if(SMLOW > SML) SML=SMLOW; /* SML -AMAXl (SML ,SMLOW ) */ if (SMMAX < SML) SML=SMMAX} /* SML =AMIN1(SML ,SMMAX ) */ }

}

/* SUBROUTINE STMCH(ISMCH) */

void STMCH(int ISMCH)

(

/* WITHOUT STICK MACHINE */ if (ISMCH «« 0)

{

SLFL»SLF;

SML-SMJ

SRDL=SRD;

STOL=STO;

SLNL-SLN;

SPBL-SPB; }

/* WITH STICK MACHINE */ else if(ISMCH »= 1)

SLFL ■ 0.1625f - 0.0710f * SM + 1.0326f * SLF;

SML «= SM;

SRDL - 2 .3777 f - 0. 0299f * SM + 0 .9736f * SRD ; STOL = 1.8168f - O.OOllf * SM + 0.9419f * STO; SLNL = 0.1996f - 0.0003f * SM + 0.8226f * SLN; SPBL «= 1.8629f - 0.0025f * SM + 0.7587f * SPB; if(SLFLOW > SLFL) SLFL=SLFLOW; /* SLFL~AMAX1 (SLFL,SLFLOW) */ if (SMLOW > SML ) SML=SMLOW; /* SML =AMAXl(SML ,SMLOW ) */ if(SMMAX < SML ) SML=SMMAX; /* SML =AMIN1(SML ,SMMAX ) */ }

/* assess

/* SUBROUTINE IC(IIC) */

/* ====================== void IC(int IIC)

{

/* WITHOUT IMPACT CLEANER */ if (IIC =» 0)

{

SLFL=SLF;

SML "SM;

SRDL=SRD;

STOL-STO;

SLNL=SLN;

SPBL=SPB; }

/* WITH IMPACT CLEANER */ else if(IIC == 1)

{

SLFL - -0.1305f - 0.0619f * SM + 1.0599f * SLF; SML = SM; SRDL = 3.4151f O.OOOβf SM 0.9606f SRD; STOL « -0.6071f 0.0057f SM 1.0127f STO; SLNL «= 0.2557f 0.0012f SM 0.7764f SLN; SPBL - 2.8104f 0.0137f SM 0.6457f SPB; if(SLFLOW > SLFL) SLFL»SLFLOW; /* SLFL=AMAX1(SLFL,SLFLOW) */ if(SMLOW > SML ) SML«SMLOW; /* SML =AMAX1(SML ,SMLOW ) */ if(SMMAX < SML ) SML=SMMAX; /* SML =AMIN1(SML ,SMMAX ) */ }

}

/*

/* SUBROUTINE GINSTD(IDRl , IDR2 ) */ /* void GINSTD(int IDRl, int IDR2)

/* COTTON COMING INTO THE GINSTD CANNOT EXCEED 8.5 */ /* Insuring that driers are fully used if moisture above 8.5 */ if((DRl && SM>8.5 && IDRK4) || (DR2 && SM>8.5 && IDR2<4))

IPGS=1; else

IPGS-0;

SLFL= SLF;

SML = SM;

SRDL=19.52f - 0.12f *SM + 0.75f*SRD;

STOL= 9.22f + 0.14f *SM +.0.72f*STO;

SLNL= 0.31f + 0.002f*SM + 0.72f*SLN;

SPBL= 1.50f + 0.02f *SM + 0.81f*SPB;

if(SLFLOW > SLFL) SLFL=SLFLOW; if(SMLOW > SKL) SML=SMLOW; if (SMMAX < SML) SML=SMMAX; if(SRDLOW > SRDL) SRDL-SRDLOW; if(SRDMAX < SRDL) SRDL=SRDMAX; if(SLNLOW > SLNL) SLNL-SLNLOW; if(SLNMAX < SLNL) SLNL«SLNMAX; if(SPBLOW > SPBL) SPBL-SPBLOW; if(SPBMAX < SPBL) SPBL-SPBMAX;

.= */

/* SUBROUTINE lint cleaner(ILC) */ == */ void lint cleaner(int ILC)

{

/* NO LINT CLEANERS */ if (ILC == 0)

{

SLFL=SLF;

SML »SM)

SRDL-SRD;

STOL»STO;

SLNL-SLN ;

SPBL-SPB; }

/* ONE LINT CLEANER */ also if(ILC -= 1)

{

SLFL- -0.6665f + 0.0937f * SM + 0.8296f * SLF;

SML - SM;

SRDL- 25 . 9279 f - 0 . 0834 f * SM + 0 . 6757f * SRD ;

STOL-. _8.0604f - 0.1694f * SM + 1.2043f * STO;

SLNL= +0.1742f + 0.0003f * SM + 0.8288f * SLN;

SPBL= +3.3751f - 0.0222f * SM + 0.5970f * SPB; }

/*

if(SLFLOW > SLFL) SLFL-SLFLOW; if(SMLOW > SML) SML-SMLOW; if(SMMAX < SML) SML=SMMAX; if(SRDLOW > SRDL) SRDL-SRDLOW; if(SRDMAX < SRDL) SRDL=SRDMAX; if(SLNLOW > SLNL) SLNL-SLNLOW; if(SLNMAX < SLNL) SLNL_*=SLNMAX; if(SPBLOW > SPBL) SPBL-SPBLOW; if(SPBMAX < SPBL) SPBL-SPBMAX;

/* FUNCTION CLINT(SLFX,SMX,SRDX,STOX,SLNX,SPBX) */

float CLINT(float SLFX, float SMX, float SRDX, float STOX, float SLNX, float SPBX) int IRD,IPLUSB, LG, LN} float PR;

IRD=(int) (SRDX+0.5); IPLUSB=(int) (SPBX*10.f+0.5); if (IRD > 85 I f IRD < 40) print ("*CLINT* IRD outside of range - IRD - %d\n",IRD); if(IPLUSB > 180 j| IPLUSB < 40) printf("*CLINT* IPLUSB outside range - IPLUSB ^»

%d\n^M, IPLUSB); ICR=ICOLOR[ IRD-40 ] [ IPLUSB-40 ] ;

LG= int) (SLFX+0.5),

LN=(int) (SLNX*32.0f+0.5); if (LG > 10 || LG < 2) printf("*CLINT* LG outside range - LG = %d\n",LG); if(LN > 37 f| LN < 29) printf("*CLINT* LN outside range - LN = %d\n",LN); PR-IPRICE[ICR-ll][LG-2][LN-29] ; PRICE-PR/100. Of+BPRICE;

/* PRICE is set to -99 if it is not in range of data. */ if (PRICE > 0) return(PRICE*STOX/100.0f ); else return(-99.f) ;

*/

/* SUBROUTINE OPTM(IDRl , ICCl ,ISMCH, IICl, IDR2 ,ICC2 ,IIC2 , ILC) */ */ void OPTM(int IDRl, int ICCl, int ISMCH, int IICl, int IDR2, int ICC2, int IIC2, int ILC) int i; FM = FX; ICLRM = ICR; PRICEM- PRICE;

IDR1M = IDRl; ICC1M - ICCl; ISMCHM= ISMCH; IIC1M - IICl; IDR2M = IDR2; ICC2M = ICC2; IIC2M - IIC2; ILCM = ILC; for(i-l;i<-10;i++)

{

SLFM[i] «= SLFT[i]

SMM [i] - SMT [i]

SRDM[i] = SRDTfi]

ST0M[i] ■ ST0T[ij

SLNM[i) - SLNTfi]

SPBM[i] = SPBT[i]

>

*/

SUBROUTINE OTPUT */

LN=(int) (SLNX*32.0f+0.5); if (LG > 10 I I LG < 2) printf("*CLINT* LG outside range - LG = %d\n",LG); if(LN > 37 I I LN < 29) printf("*CLINT* LN outside range - LN = %d\n",LN); PR»IPRICE[ICR-ll][LG-2] [LN-29]; PRICE=PR/100.0f+BPRICE;

/* PRICE is set to -99 if it is not in range of data. */ if (PRICE > 0) return(PRICE*STOX/100.0f); else return(-99. f);

/* SUBROUTINE 0PTM( IDRl, ICCl , ISMCH, IICl, IDR2, ICC2,IIC2 , ILC) */

void OPTM(int IDRl, int ICCl, int ISMCH, int IICl, int IDR2, int ICC2, int IIC2, int ILC) int i; FM = FX; ICLRM - ICR; PRICEM= PRICE;

IDR1M = IDRl; ICC1M » ICCl; ISMCHM= ISMCH; IIC1M - IICl; IDR2M = IDR2; ICC2M = ICC2; IIC2M - IIC2; ILCM = ILC; for(i- l;i<-10;i++) {

SLFM[i] SLFTfi]; SMM [i] SMT [i]; SRDMJi] SRDT{i]; ST0M[i] STOT[ij; SLNM[iJ SLNT[i]; SPBM[i] SPBT[i];

} * SUBROUTINE OTPUT */

void OTPUT(void)

{ int leaf, length; printf ("\n O P T I M U M G I N N I N G D E C I S I O N

S\n\n^M); printf (" I N P U T S T A T E S\n"); printf ( " \n" ) ; printf (" OPR DEC SLF SM SRD STO SLN SPB\n"); if (DR1) printf(" %6s %4d %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n" , "DR 1", IDRlM,SLFM[l],SMM[l],SRDM[l],STOM[l],SLNM[l],SPBM[l]); else printf(" %6s *\n","DR 1"); if (CCl) printfC %6s %4d %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f \n" , "CC 1",ICC1M,SLFM[2],SMM[2],SRDM[2],ST0M[2],SLNM[2],SPBM[2]); else print (" %6s *\n", CC 1"); if(SMCH) printf(" *6s %4d %8.2f %8.2f %8.2f %8.2f 8.2f %8.2f\n", "STMCH" ,

ISMCHM,SLFM[3] ,SMM[3] ,SRDM[ 3 ] ,STOM[3 ] ,SLNM[3 ] ,SPBM[ 3 ] ) ; else printf(" %6s *\n" , "STMCH") ; if(ICl) printf{" %6s %4d %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n", "IC 1",

IIClM,SLFM[4],SMM[4],SRDM[4],STOM[4],SLNM[4],SPBM[4]); else printf (" %6s *\n" ,"IC 1"); i (DR2) printfC *6s %4d %8.2f %β.2f %8.2f %8.2f %8.2f %8.2f \n" , "DR 2",

IDR2M,SLFM[5],SMM[5],SRDM[5],STOM[5),SLNM[5],SPBM[5]); else printfC *6β *\n" ,"DR 2"); i (CC2) printfC %6s %4d %8.2f %8.2f %8.2f %B.2f %8.2f %8.2f \n" , "CC 2",

ICC2M , SLFM [ 6 ] , SM [ 6 ] , SRDM [ 6 ] , STOM [ 6 ] , SLNM [ 6 ] , SPBM [ 6 ] ) f also printfC *6s *\n" , "CC 2" ) ;

if (IC1) printf(" %6s 4d %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n","IC 2",

IIC2M,SLFM[7],SMM[7],SRDM[7],STOM[7],SLNM[7],SPBM[7]) ; else printf(" %6s *\n","IC 2"); printfC *6s %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n" , "GINSTD" , SLFM [ 8 ] , SMM [ 8 ] , SRDM { 8 ] , STOM [ 8 ] , SLNM [ 8 ] , SPBM[ 8 ] ) ; if (LC) printf(" %6s %4d %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n" , "LC" ,

ILCM, SLFM[9] ,SMM[9],SRDM[9] ,STOM[9] ,SLNM[9] ,SPBM[9] ) ; else printfC %6s *\n" , "LC" ) ; printf(" %6s %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n" , "OUTPUT" ,

SLFM[10],SMM[10],SRDM[10],STOM[10],SLNM[10],SPBM[10]); leaf -(int) (SLFM[10]+0.5) ; length-(int) (SLNM[ 10 ] *32.Of+0.5) ; printf("\n Final Color =%3d Final Leaf =%3d Final Length = %3d" "\n Selling price=$%5.2f Final value =$%5.2f\n", ICLRM, leaf, length,PRICEM,FM); if (IDRl || ICCl || ISMCH || IICl || 1DR2 || !CC2 || IIC2 || ILC) printf ("\n* This operation was not included in configuration. \n" ) ;

}

/* SUBROUTINE TABL12 */

float TABLI2(float *ARRAY, float *X, float *Y, float XARG, float YARG, int NDIMX, int NDIMY) { float RATIO, RAYI50]; int i, ii, MD, N; if(XARG > X[NDIMX] || XARG < X[l]) printfC TABLI2 XARG - %10.4e X(l) = %10.4e X(NDIMX) =

%10.4e\n", XARG, X[l], X[NDIMX] ); if(YARG > Y[NDIMY] || YARG < Y[l]) printfC TABLI2 YARG = %10.4e Y(l) = %10.4e Y(NDIMY) =

%10.4θ\n", YARG, [1],Y[ DIMY)) ;

II«=0; MD=NDIMX*NDIMY; if ( FIND (Y, YARG, &N, DIMY) == 0)

for( i=N;i<-MD; i=i+NDIMY)

RAY[++II ]=ARRAY[ i] ; else

{

RATIO=(YARG-Y[N])/<Y[N+l]-Y[N]); for(i-N;i<-MD; i=i+NDIMY)

RAY[++II ]=ARRAY[i]+RATIO*(ARRAY[ i+1 ] -ARRAY[i ] ) ;

} return(TABLI(RAY,X,XARG, DIM ) ) ;

/* FUNCTION TABLI(VAL,ARG,DUMMY,K) */

/* This table lookup function was translated from that by FORDYN */ float TABLI( float *VAL, float *ARG, float DUMMY, int K)

{ int i; if(DUMMY > ARG[KJ)

DUMMY = ARG[K]; if(DUMMY < ARG[1])

DUMMY - ARG[1]; for(i=2;i<=K;i++) if (DUMMY <- ARG[i]) return ( (DUMMY-ARG[ i-1 ] )*(VAL[i]-VAL[ i-1] )/(ARG[i]-ARG[i-1] )+

VAL[i-l]);

}

/* SUBROUTINE FIND(X,ARG,N,KEY,NDIM) _ */

int FIND(float *X, float ARG, int *N, int NDIM)

{ int i, KEY, IX, IARG; if(ARG > (X[NDIM]+0.05) | | ARG < X[l]) printfC FIND ARG = %10.4f X(l) - %10.4f X(NDIM) =

%10.4f",ARG, X[l], X[NDIM])j KEY=1; IARG^β (int) (100.0f*ARG+0..^r,f ); for(i=l;i<-NDIM;i++)

{

IX-(int)(100.0f*X[i]+0.5f)>

if(IARG > IX) continue; if(IARG == IX) KEY-0; *N=i-KEY; goto exit;

} exit: return(KEY);

}

/* Clears the results between runs of the system */

void clear_results(void)

{ int i; for(i-0;i<-10;i++)

{ SLFM[i]-SMM[i]=SRDM[i]=STOM[i]=SLNM[i]=SPBM[i]-0;

}

ICLRM=0;

}

COTTONL.C

*/

/* */

/* Program Has Different Main Routine with Looping on Parameters */

/* Functions from COTTON.C that were not needed were deleted. */

/* */

/* The input file names were hardcoded */

/* (and assumed to be in current directory) they are. */

/* Drier data j drier.dat */

/* Price data : greene.ccc */

/* Grading data: uplndcol */

/* */

/* The output file name was hardcoded */

/* (and assumed to be in current directory), it is» */

/* Output data : output.dat */

/* */ = */

/* GINCOM */

*/

#include <stdio.h>

#include <string.h>

#include <stdlib.h> /* Required for abort() functions */

#define TRUE 1 #define FALSE 0

FILE *output; /* File for storing output data */ int DR1 CCl SMCH IC1 DR2 CC2 IC2, LC; int IDR1M, ICC1M, ISMCHM, IIC1M , IDR2M, ICC2M, IIC2M, ILCM;

/* COMMON DD(O«4),TM(36),TMX(4),TMY(9),GASUSD(0:4) */

/* If the indice does not start at 0, then need to add */

/* one to the array size to account for C starting at 0 */ /* instead of 1. */ float DD[5], TM[37], TMX[5], TMY[10], GASUSD[5]; float SLF SM SRD STO SLN SPB; float SLFL SML SRDL STOL SLNL SPBL; float SLFINT SMINT SRDINT STOINT SLNINT SPBINT; float SLFT[11] SMT [11] SRDT[11] STOT[ll] SLNT[11] SPBT[11]; float SLFM[11] SMM[11] SRDM[11] STOM[ll] SLNMfll] SPBM[11]; float SLFLOW SMLOW SRDLOW STOLOW SLNLOW SPBLOW; float SLFMAX SMMAX SRDMAX STOMAX SLNMAX SPBMAX ;

/* COMMON PRC(0.30,Oι30),ICLR(0$30,0«30) */ float PRC[31][31]; int ICLR[31][31]; COTTONL.C

/+ COMMON ICOLOR(40:85,40:181),IPRICE( 11 :95, 2:10,29:38) int ICOLOR[46][142J; int IPRICE[85][9][10]; float FX, FM, BPRICE, PRICE, PRICEM; int ICR, ICLRM, IPDR, IPGS;

/* .== */

/* Forward Declarations of functions */ /* (Given in order of appearance in the listing below) */ /* .== */ void READfile(char FILENM[50], float XA[10], float YA[10], float ARRAY[37] int NDIMX, int NDIMY) ; void PRTSYS(void); void CHGSYS(void); void OP (void); void RECORD(int ); void UPDATE(int Jc); void DRIER(int IDR); void CC(int ICC); void STMCH(int ISMCH); void IC(int IIC); void GINSTD(int IDRl, int IDR2); void lint_cleaner(int ILC); float CLINT(float SLFX, float SMX, float SRDX, float STOX, float SLNX, float SPBX); void OPTM(int IDRl, int ICCl, int ISMCH, int IICl, int IDR2, int ICC2, int IIC2, int ILC); void GINOUT(int *NDDR1, int *NDSMCH, int +NDIC1, int *NDDR2 , int

*NDLC, char *drier_file, char *price_file, char *grade_file, int lower_bound, int upper_bound) ; float TABLI2(float *ARRAY, float *X, float *Y, float XARG, float YARG, int NDIMX, int NDIMY); int FIND( float *X, float ARG, int *N, int NDIM) float TABLI(float *VAL, float *ARG, float DUMMY, int K) void σlear_ cesult3 (void) ;

==================as===r«β^-*=-β-s=a .--.... ^

/* MAIN

void main (void)

],NDLC[31]; COTTONL.C int check; int IC, LG, LN; int IRD, IPLUSB; int ISLF, ISM, IPB, ISRD; int ISLFint, ISLFmax, ISMint, ISMmax, IPBint, IPBmax, ISRDint, ISRDmax;

/* Data for driers */ DD[0]= 0; DD[1]-150; DD[2]=200; DD[3]=250; DD[4]-300;

/* Reading drier data */

READfile(drier_file,TMX,TMY,TM,4,9);

/* */

/* Initialize Array */ or( C=0; IC<=8 ; IC++) for(LG=0;LG<=8;LG++) for( N-0; N<-9 ;LN++)

/* if use -99999 then need to use different type of integer */

IPRICE[IC][LG][LN]--29999;

/* Reading pricing data */ if ((price_data - fopen(price_file, "r" )) == NULL ) printf("*** The current directory does not contain the price datafile: %s\n", price_file) ; abort( ) ; ^*" } while( fscanf(price_data, "%2d%lβ%ld", tic, &junk, SLG) 1= EOF) for( N-0 ; N<9 ;LN++) fscanf (price_data, "%d", &IPRICE[IC-11] [LG-2] [LN] ) ;

/* Reading grading data */ if((grade_data = fopen(grade_flie, "r" )) ^« NULL ) printfC*** The current directory does not contain the grading datafile: %s\n", graάe_file) ; abort ( ) ;

} do check - fscanf (grade data, "%2d%3d%2d%ls",

&IRD, &IPLUSB, fiICOLOR[IRD-40][IPLUSB-4O],ϊ.junk); while (check I- EOF); COTTONL.C

/* Close input files */ if( fclose( price_data ) ) printf( "The price datafile was not closed: %s\n", price_file ) ; if( fclose( grade_data ) ) printf( "The grading datafile was not closed: %s\n", grade_file ) ;

/* Open file for storing results */ if((output - fopenCoutput.dat", "w" )) === NULL ) printf("*** The file OUTPUT.DAT could not be opened ***\n")

SLFL0W= 2. Of; SLFMAX-lO.Of; SMLOW = O.Of; SMMAX =20.0f; SRDLOW=50.0f; SRDMAX-80.0f; STOLOW=35.0f; STOMAX-40.0f; SLNLOW= l.Of; SLNMAX- 1.16f; SPBL0W= 5.5f; SPBMAX=13.5f;

/* Variable value ranges used */

ISLFint*4; ISLFmax=16 /* Actual Range is 2-8 */

ISMint -6; ISMmax -18 /* Actual Range is 3-9 */

IPBint ^βiO IPBmax -30 /* Actual Range is 5-15 */

ISRDint-50; ISRDmax-80; /* Actual Range is 50-80 */ printf("Currently evaluating variable values :\n");

CHGSYS ( ) ; for(ISLF-ISLFint; ISLF<=ISLFmax;ISLF++)

SLFINT- ((float) ISLF)/2.f; for(ISM-ISMint> ISM<=ISMmax; ISM++)

{

SMINT=( (float) ISM)/2.f; COTTONL.C for ( IPB=IPBint ; IPB<=IPBmax ; IPB++ )

SPBINT=( (float) IPB)/2.f; for(ISRD-ISRDint;ISRD<=ISRDmax; ISRD++)

{

SRDINT=(float) ISRD; printf(" Leaf =%5.2f Moisture=%5.2f "Plus B -%5.2f Reflect.=%5.2f\r", SLFINT,SMINT,SPBINT,SRDINT) ;

/* Main program loop */ FM = -9; clear_results ( ) ; OPT();

NDDRl[ISRD-50] =IDR1M; NDSMCH[ ISRD-50]-ISMCHM; NDICl[ISRD-50] -IIC1M; NDDR2 [ ISRD-50] =IDR2M; NDLC[ISRD-50] -ILCM;

}

GIN0UT(NDDR1,NDSMCH,NDIC1 ,NDDR2 ,NDLC,drier_file, price_file ,grade_file,ISRDint, ISRDmax) ;

} } } if( fclose( output ) ) printf ( "The output datafile was not closed" ); }_# _

/* The procedures which are the same as those in COTTON.C are */ /* omitted. */

^ =»__==_==_.= ««=_-=»===

// //

/* SUBROUTINE GINOUT */ void GINOU (int *NDDR1, int *NDSMCH, int *NDIC1, int *NDDR2, int *NDLC, char *drier file, char *price_file, char *grade_file, int Tower_bound, int upper_bound) int i, last; static key «= TRUE; if (key) fprintf(output, "Drier Data File i %s\n" ,drier_filo) ; fprintf(output, "Pricing Data File: %s\n" ,price_file) ; fprintf(output, "Grading Data File: s\n" ,grade_file) ; print (output,"\n\n");

COTTONL.C for ( IPB-IPBint ; IPB<=IPBmax ; IPB++ )

{

SPBINT= ( ( float) IPB) /2. f ; for(ISRD-ISRDint; ISRD<=ISRDmax; ISRD++)

{

SRDINT=( float) ISRD; printf(" Leaf =%5.2f Moisture=%5.2f "Plus B =%5.2f Reflect.=%5.2f\r", SLFINT,SMINT, SPBIN ,SRDINT) ;

/* Main program loop */ FM = -9; clear_reaults ( ) ; OPT();

NDDRl[ISRD-50] =IDR1M; NDSMCH[ISRD-50]-ISMCHM; NDICl[ISRD-50] -IIC1M; NDDR2 [ ISRD-50 ] «IDR2M; NDLC[ISRD-50] -ILCM;

GINOUT(NDDR1, DSMCH, DIC1,NDDR2,NDLC,drier_file, price_file,grade_file, ISRDint, ISRDmax) ;

} } > if( fclose( output ) ) printf( "The output datafile was not closed" );

/* The procedures which are the same as those in COTTON.C are */ /* omitted. */

^ =__=.=-»=- «=

// //

/* SUBROUTINE GINOUT */ void GINOUT(int *NDDR1, int *NDSMCH, int *NDΪC1, int *NDDR2, int *NDLC, char *drier_file, char *price_file, char *grade_file, int lower_bound, int upper_bound)

; ; ;

COTTONL.C fprintf(output, "Base Prices - %5.2f\n" ,BPRICE) ; fprintf(output, "Turnout = %5.1f Length - %5.2f\n",STOINT,SLNINT); fprintf(output, "\n\n "); fprintf(output," Leaf %%M Reflectance\n" ) ; fprintf(output, " ^M ) ; for(i-lower_bound;i<=upper_bound; i++) fprintf(output, "%3d",i); key = FALSE;

} else

LFINT,SMINT) ;

// End of COTTON.C

// This collection of procedures relates to color calibration based on

// the five tile procedure, the color measurement and measurement of

// other variables using the A/D converter. All readings of the A/D

// converter are made in this collection of procedures. In addition,

// the color code is obtained from the Rd and +b readings in this

// section.

// ColorF.c

#include "cainc.h" // all includes #include "cadef.h" // all defines #include "caext.h" // #include "caproto.h" // prototypes of all functions

// ColorF.c // // program color.c // calibate color, calculate color from // one of several cameras and save to RAM // // // // color calibration // This section is code takes readings // of five standard color tiles, compares the readings of the A/D // converter to the Rd and +b of each tile and calculates conversion // constants based on the readings. void color cal (int cthead)

{ int σx; // dummy get ch for wait for reading output float ycolor, zcolor; float rd_dif, b_dif; float s_wht__rd, s_wht_b, s_yel_rd, s_yel_b,

053

float fwht_z, fbrn_y, fbrn_z, fyel_y, fyel_z, fgray_y, fgray_z, fσen_y, fcen_z; double ysum, zsum, stdysum, stdzsum, ysumsq, zsumsq, stdysumcq, stdzsumsq; double prodl, pro 2, prod3, prod4, prod5, yavg, zavg, ystdavg, zstdavg; double sy, sz, systd, szstd, rl2y, rl3y, r23y, rl2z, rl3z, r23z; double str_tol, el_tol, rd_tol, pb_tol; int key_quit; in.t i; FILE *fptr; time t ltime; // //

_clearscreen (_GCLEARSCREEN) ; σcal_err=0; setup_vid(cthead) ; if( chdir("c:\\init"))

{ _settextposition(3,18) ; print ( "Unable to locate the directory: ctWinit" ); exit(0) ; } if((fptr « fopen("ct__ιtile.dat", "r")) «== NULL) { _settextposition(4,18); printf("CAN'T OPEN FILE CT_TILE.DAT" ) ; exit(O);

} fscanf (fptr, "%f %f, &s_wht_rd, ϊrs whtj ); fscanf (fptr, "%f %f", &s_brn_rd, &s_brn_b) ; fscanf (fptr, "%f %f", &s_yel_rd, &s_yel_b) ; fscanf (fptr, "%f *f", &s_gray_rd, &s_gray_b); fscanf (fptr, "%f If", 6s_cen_rd, &s_cen_b) ; fclose(fptr) ; if ((fptr «= fopen("cal tol.dat", "r")) « NULL)

{

_ββttextposition(5,18) ; printf("CAN'T OPEN FILE C:\\lNIT\\CAL_TOL.DAT" ) ', exit(l); ) fscanf (fptr, " %lf %lf %lf %lf",

&str_tol, Sel_tol, &rd_tol, &pb_tol); fσlose(fρtr) ; βettextposition(4,l ) ; printf ( "rd_tol«%8.31f pb_tol-%8.31 ",rd_tol,pb_tol ); if( chdirCotWhvi")) {

_settextposition(2, 18) ; print ( "Unable to locate the directory: c:\\hvi" ); exit(O) ; } s_wht_y=s_wht_rd*20.0; s_yel_y-s_yel_rd*20.0 ; s_gray_y=s_gray_rd*20.0 ; s_brn_y=s_brn_rd*20.0; s_cen__y=s_cen_rd*20.0 ;

(l+0.2*s_wht_rd) /(749.7+7.14

(l+0.2*s_yel_rd) /(749.7+7.14*s

( 1+0.2*s_gray_rd) / (749.7+7.14*s

(l+0.2*s_brn_rd) /(749.7+7.14*s

(l+0.2*s_cen_rd) /(749.7+7.14*s

__settextposition(l,20) ; printf ( "Press Esc key to exit " );

_settextposition(2,2) ; printf( "Please Place White Tile and Press 1 " ); rl ; key__quit=getch{ ) ; if (key_quit-=KEY_ESC) goto cal_exit; if (key_quit1-0x31) goto rl; delay(200); fwht y-( float) 0.0 ; f ht_z=(float)0.0 ; for(ι=0; i<10; I++)

{ adσ_mns (Y_CHANL[cthead ] , fiiwht_y, &iwht_z ) ; fwht_y+-iwht_ ; fwht z+=iwht z; } fwht_y=fwht_y/10.0 ; fwht_z=fwht_z/10.0;

_^βottextposition(3,2); printf ( "Please Place Brown Tile and Press 2 " ) ; r2 i key_quit-getch( ) ; i (koy_quit«=KEYJESC) goto cal_exit; if ( koy_quit 1 -0x32 ) goto r2 ;

,&ibrn_z) ;

_settextposition(4,2) ; ");

;

_eettextposition(5,2); printf( "Please Place Gray Tile and Press 4 "); r : key_quit-getch( ) ; if (key_quit==KEY_ESC) goto cal_exit; if (key_quitl=0x34) goto r4; delay(200); fgray_y=(float)0.0; fgray z=(float)0.0; for(i-0; i<10; I++) ^"~

{ adα_mns( CHANL[cthead] ,&igray_y,&igray_z) ; fgray_y+-ϊgray_y; fgray z+-igray z;

} fgray_y=fgray_y/10.0; gray_z-fgray_z/10.0 ;

_βettθXtpoβition(6 , 2 ) ; printf( "Please Place Central Tile and Press 5 "); r5 J key_quit«=getch( ) ; if(key_quit—KEY ESC) goto cal_exit; if (koy_quiti-0x3^"5) goto r5; delay(200); cen v-(float)0.0; fcon_z=( float)0.0; for(I-0 ; i<10 ; I++ ) 6053

, &icen_y,£icen_z) ;

_settextposition(6, 2) ; printf ( sgl) ;

// Start doing the calculations here. ysum=fwht_y+fbrn_y+fyel_y+fgray_y+fcen_y; zsum=fwht_z+fbrn_z+fyel_z+fgray_z+fcen_z; 3tdy8um-s_wht_y+s_bm_y+s_gray__y+s_yel_ y+s__cen_y; stdzsum=s_wht_z+s_brn_z+s_gray_z+s_yβl_z+s_cen_z; ysumsq- (fwht_y*fwht_y)+fbrn_y*fbrn__y+f ye l_y*fyel_y+fgray_y*fgray_y+fc n_y*fcen_y; zsumsq-fwht_z*fwht_z+fbrn_z*fbrn_z+fyel_z*fyel_z+fgray_z*fgray_z+fcen z*fcen_z; s tdy sumsq-s_wh t__y * s_wh t_y +s_brn_y * s_brn_y +s_gray_ * s_gray_y +s_yel_y * s y β l_y +s_ce n_y *s_cen_y ; stdzsumsq-s_wht_z*s_wht_z+s_brn_z*s_brn_z+s_gray_z*s_gray_z+s_ el_z*s yel_z+s_cen_z *s_cen_z ; prod 1 - f wh t_y * a_wh t_y+f brn_y *s_brn_y+f yβl_y * s_ye l_j y+f gray_y * s_gray__y+f e n_y * s_ce n__ ; prod2-fwht_y*s_wht_z+fbrn_y*s_brn_z+fyel_y*s__yel_z+fgray_y*s_gray_z+f en_y*s_cen_z ; prod3-fwht_z*β_Wht_y+fbrn_z*8_brn_y+fyel_z*s_yel_y+fgray_z*s_gray_y+f en_z * s cen y ; prod4-fwht_z*s_wht_z+fbrn_z*s_brn_z+fyel_z*s_yel_z+fgray_z*8_gray_z+f

prod5=fwht_y*fwht_z+fbrn_y*fbrn_z+fyel_y*fyel_z+fgray_y*fgray_z+fcen_ *fcen_z;

tcmp-(yβumsq/5-yavg*yavg) ;

sy-sqrt(temp) ;

l l fl d l 2 ( l 3 ) if( ohdir("oι\\init"))

{

_settextposition(2,18); printf("Unable to locate the directory! ciWinit" ); exit(0) ; if (cthead—0) fptr = fopen("ctcal0.dat", "w" ) ; _settextposition(22,20);printf("Opened file ctcal0.dat "); else if (cthead==l) fptr - fopenC'ctcall.dat", "w" ) ;

_settextposition(22, 20) ;printf ("Opened file ctcall.dat " ) ; else if (cthead«2) fptr - fopen( "ctcal2.dat", "w" ) ;

_settextposition(22,20); printf ("Opened file ctcal2.dat "); fprintf (fptr, "%f %f %f\n", y_cal.σl, y cal.c2, y_cal.σ3) ; fprintf (fptr, "%f %f %f\n", z_cal.cl, z_cal.c2, z_cal.c3); fcloso(fptr) ;

if( chdir("cι\\hvi"))

{

_settextposition(2,18); printf ( "Unable to locate the direetorys hvi" ); exit(0) ; }

// white tile ycolor=y_cal.cl+(fwht_y*y_cal.c2)+(fwht_z*y_cal.c3 ) ; zcolor=z_cal.cl+( fwht_y*z_cal.c2 )+(fwht_z*z_cal.c3 ) ; rd=ycolor/20.0; plus_b=((rd/100.0)-(0.847*zcolor/2000.0))*(35.7*(21+0.2*rd)/

(l+0.2*rd)); rd_dif-rd-s wht_rd; b_dif=plus_b-s_wht_b; settextposTtion(4,1); printf(" White Tile : Rd %4.1f +B %4.1f Rd %4.1f +B %4.1f Rd

%4.1f +B %4.1f ", s_wht_rd, s_wht_b, rd, plus_b, rd_dif, b dif ); Tf (fabs(rd_dif) > rd_tol)

{

_settextposition( 4, 37); printf( "Rd %4.1f",rd); if(fabs(rd_dif) > rd_tol*3.0 ) ccal_err++;

} if(fabs(b_dif ) > pb_tol )

{

_settextposition(4, 46); printf( "+B %4.1f",plU3_b); if (fabs(b_di ) > pb_tol*3.0) ccal_err++; >

// brown tile ycolor=y_cal .cl+(fbrn_y*y_cal.c2)+(fbrn_z*y_cal.c3) ; zcolor=z_cal.cl+(fbrn_y*z_cal.c2)+(fbrn_z*z_cal.c3) ; rd=ycolor/20.0;

Rd ;

_βettextpoaition(6, 46); printf("+B %4.1f",plus_b); if(fabs(b_dif ) > pb_tol*3.0) ccal err++; }

// yelow tile ycolor=y_cal.cl+(fyel_y*y_cal.c2 )+(fyel_z*y_cal .c3 ) ; zcolor=z_cal.cl+(fyel_y*z_cal.c2)+(fyel_z*z_cal.c3) ; rd=ycolor/20.0; plus_b=((rd/100.0)-(0.847*zcolor/2000.0))*(35.7*(21+0.2*rd)/

(l+0.2*rd)); rd_dif-rd-s__ι_yel_rd; b_dif-plus_b-s_yel_b; _settextposxtion(8,l) ; printf(" Yellow Tile : Rd %4.1f +B %4.1f Rd %4.1f +B %4.1f Rd

%4.1f +B %4.1f ", s_yel_rd,s_yel_b,rd,ρlus_b, rd_dif,b_dif); if(fabs(rd_dif ) > rd_tol)

{

_settextposition(8, 37); printf("Rd %4.1f",rd); if(fabs(rd_di ) > rd_tol*3.0 ) ccal_err++; } if(fabs(b_dif) > pb_tol)

{

_βettextposition(8, 46); printf C+B %4.1f ",plus_b) ; if (fabs(b_dif ) > pb_tol*3.0) σcal_err++; }

// gray tile ycolor=y_cal.cl+(fgray_y*y_cal.c2)+(fgray_z*y_cal.c3) ; zcolor=z_cal .cl+( fgray_y*z_cal .c2 )+( gray_z*z_cal .c3 ) ; rd-ycolor/20.0» plus_b=((rd/100.0)-(0.847*zcolor/2000.0))*(35.7*(21+0.2*rd)/

(l+0.2*rd)); - — -, _ ._ . rd_dif-rd-s gray_rd; b_dif=plus_b-s_gray_b;

_βettextposTtion( 10 , 1 ) ; printfC Gray Tile t Rd "44. If +B %4.1f Rd %4.1f +B %4.1f Rd

%4.1f +B %4.1f ", s_gray_rd,s gray_b,rd,plus b,rd_dif, b_dif); if(fabs(rd cfif) > rd tol) ^*"

{

_βettextposition(10, 37); printf("Rd %4.1f" ,rd); if (fabs(rd_dif) > rd_tol*3.0 ) cσal_err++; if(fabs(b dif) > pb tol)

_settextposition(10, 46); printf C+B %4. If " ,pluβ_b); if (fabs(b_dif ) > pb_tol*3.0) ccal_err++; }

// Central tile ycolor=y_cal . cl+ ( f cen__y*y_cal ,c2 ) + ( f cen_z*y_cal . c3 ) ; zcolor=z_ι cal.σl+(fcen y*z σal.c2)+(fcen z*z_cal.c3) ; rd=ycolor / 20.0; plus_b=((rd/100.0)-(0.847*zcolor/2000.0))*(35.7*(21+0.2*rd)/

(l+0.2*rd)); rd_dif=rd-s cen_rd; b_dif=plus_b-s_cen_b; _set textposXtio (12,1); printfC Central Tile j Rd %4.1f +B %4.1f Rd %4.1f +B %4.1f Rd

%4.1f +_B %4.1f " ,ε_cen_rd,s_cen_b,rd,plus_b,rd_dif, b_dif); if (fabs(rd_dif ) > rd_tol)

{

_settextposition(12, 37); printf("Rd %4.1f",rd); if(fabs(rd_dif) > rd_tol*3.0 ) ccal_err++;

} if(fabs(b_dif) > pb_tol)

{

_βettextposition( 12, 46); printf("+B %4.1f",plus_b); i (fabs(b_dif) > pb_tol*3.0) ccal_err++;

} if (σσal_errl=0)

{

_settextposition(16, 1); printf(msg3) ;

_settextposition(20, 1); printf(msg3) ;

_βettextpθβition(21, 1); printf(msg2) ;

_settβxtposition(22, 1); printf(msg3) ;

_settextposition(23, 1); printf (msg2) ;

_βettextpoaition(24, 1); printf(msg3) ;

} dsk_colcal (cthead) ; if (ccal_err—0) {time(&ltimβ) ;

} cal__exitt int [ctheadJ-0.0; intz[cthead]=0.0; slpy[ctheadJ-1.0; slpz[ctheadj-1.0;

_sottoxtposition(17,20);printf(" ");

_settextposition(18, 20); rintfC Press any key to exit ");

_sottoxtposition(19,20)ιprintf(" "); cx=gotch( ) ;

} // end color_cal

// ColorF.c

// This code takes one reading of one A/D channel. void adc_value(int adch, int adgain, int* valuep)

{ int lb, hb, crd, rep=-30000, val; outp(ADBase+2,adch) ; delay(2); // settling time ?? outp(ADBase,0); do { crd « inp(ADStat); rep++;} while (((crd & 0x80) =- 0x80)&&rep<300) ; lb - inp(ADBasβ)»4; hb = inp(ADBase+l)«4; val = hb; val += lb;

*valuep = val; } // end adc value //

// ColorF.c

// This code is written to read the extra moisture sensor behind the // gin stand. It takes an average of eight readings of the one channel // when it is called. It then converts the raw A/D value to a real // number of moisture content (wet basis). void get_sjm( void )

{ int j, tmp; double sum; sum=0.0; for (j=0;j<8;3++)

{ adσ_yalue(07,l,&tmp); // channel, gain, data sum +- tmp;

}

SJ_dat[ll]_*(iπt)( (sum+4.0)/8.0); // mean of 8 readings rSJ_dat[ 11 ]-((βum+4.0)/8.0-2048.0)*10.0/2047.0/1.98*1.29+2.1;

} // end get elm //

// ColorF.c

// This piece of code reads several different analog inputs. It can

// readily be modified by one of skill in the relevent art to

// accomodate the exact hardware in the system.

// It reads

// the appropriate analog input channel, takes a mean of the analog

// value, and converts it to a real number value. The variables

// that it roads have to do with analog moisture values and

// analog temperature data that is available in the system.

.213, 1.216};

only 4 readings ;

only 4 readings

outp( OBase+3 , i) ; sum-0; for (j=0;j<4;j++)

{ adc_value(15,1, &tmp) ; sum +- tmp;

}

SJ_dat[i]=(int) ( (sum+2.0)/4.0) ; // mean of only 4 readings

} } // end get mc

//

// This section of code gets

// the mean of 16 readings of one channel and the adjacent channel.

// The way the hardware has been connected the channel for

// the Y of the color of one of the stations and Z of the color will

// be located in the next higher analog channel. Therefore, when this

// procedure is called IS readings of the Y and 16 readings of the Z

// of an individual measurement station are taken and the resulting

// means are passed back to the calling procedure. A slight delay is

// added to the program so that the 16 values are spread out over

// approximately l/60th of a second which is the common noise

// frequency due to the power system in this country. void adσ_mns(int adch, int* yvp, int* zvp)

{ int i, lb, hb, crd, rep; unsigned ysum, zsum; ysum-0 ; zsum=0; for

delay(3);

}

*yvp = (ysum+8)»4;

*zvp = (zsum+8)»4;

} // end adc mns

//

// This procedure takes one reading of one channel of the A/D // converter. void εhowad(int ch) { int val; adc_value(ch,0x8,&val) ;

}

// end showad

//

// This section of code addresses the

// data translation video multiplexer card and changes the input

// channel used for the frame grabber to measure trash from the video

// cable running from station one, two, or three. It also instructs

// the frame grabber card to go live which means it. starts viewing the

// video coming from the camera. void setup vid(int ch)

{ // if (ch==0)

{ outp(DT2859,0); } // switch Video MUX here if (ch~l)

{ outp(DT2859,l); } // switch Video MUX here if (ch—2)

{ outp(DT2859,2); } // switch Video MUX here

HRTlive(HRTseg);

} // end setup_ id

//

// This is the moisture content measurement manager software. It

// controls data collection of the resistance moisture sensors at the

// three locations.

// void mcmgr(int cthead) // camera # int i, vail , val2; float si , 82 ;

CompOK ( ) ;

adc_mns (Y_CHAN [cthead ]+2 , S,vall , S,val2 ) ; SJ_dat[5+cthead] - vail; if (cthβad==0) last_read[cthead) .m=( ( (float) (vall-2048)*10.0/2047.0)

/0.1429+4.0);

6lS6 / / Ctl βdd —⁼ 1 or 2 last_read[cthead] .m=( ( (float) (vall-2048)*10.0/2047.0) /

0.1429+4.0) ; if (cthead==0)

{

SJ_dat[10] = val2; rSJ dat[10] = val2*0.01515-29.75; }

//

// set these logically

1 st_read[cthead) .mok = 0;

// out of range resistance moisture readings if ( last_read[cthead) ,m< 4.7)

{ last_read[cthead] .mok - 1; last_read[cthead ] .m=0.0; } if ( last_read[cthead] .m>10.2)

{ last_read[cthead] .mok = 1; last_read[cthead) .m-0.0; } // get the temperatures all three each time sl>=0.0; 82-0.0; for (i=0;i<4;i++) // average of 16*4-64 readings

{ adc_mns(12,&vall,&val2); // TI at 12, T2 at 13 si += vail; s2 += val2;

}

SJ_dat[0] = (int)((sl+2.0)/4.0); SJ_dat[l] - (int)((s2+2.0)/4.0); rSJ_dat[0]=( 1910.0 -sl/4.0*0.894-5.0); rSJ_dat[l]=( 1929.0 -s2/4.0*0.903-5.0) ; sl-0.0; s2-0.0; for (i-0;i<4;i++) // average of 16*4-64 readings

{ adc_mns(14,&vall,&val2); // Tl at 12, T2 at 13 si += vail; s2 +- val2;

}

SJ_dat[2) - (int)((sl+2.0)/4.0); rSJ_dat[ 2 ]=( 1929.0 -sl/ .0*0.903-5.0);

}

//

// This code iβ the basic color measurement manger code.

// It reads the Y and Z of an analog channel. It

// calls the code which calculates the Rd value, the +b value and from

// that, the color code for the sample. int colrmgr(int cthoad) // camera #

CompOK( ) ; y_v=( float) 0.0; z_v-(float)0.0; for(i=0; i<10; I++)

{ adc_mns(Y_CHANL[camera] ,£ry_clr,-iz_clr) ; y_v+=y_clr; z v+-z_clr;

} y_v=y_v/10.0; z_v=z_v/10.0;

CompOK( ) ; if (compute_color(y_v, z__v)==PASS)

{ color_step=20;

} else

{ rd=( loat) 0.0; plua_b-(float)0.0; colr-1; // bad color_step=20;

} color_step=0; return(PASS) ;

}

//

// This section of code initializes the color measurement software by // reading the six coefficients for each of the color cameras that // have been most recently calculated with the calibration software. // These values are read from the hard disk of the controlling // computer. void color_init(void) int jnk;

FILE *ccal; if ((ccal = fopen("ct\\init\\ctcal0.dat", "r"))== NULL) {

_s e ttextpos ition (6,18); printf ("Can't open file σι\\init\\ctcal0.dat\n" ) ; printf ("press any key to continue"); jnk-gotch( ) ; olβo

{ fscanf(ccal, "%f %f %f", 4ccf[0)[0], Sccf[0][l],

&ccf[0][2]); fscanf(ccal, "%f %f %f", &ccf[0][3], &ccf[0][4],

&ccf[0][5]); fclose(ccal) ; } if ((ccal = fopen( "csWinitWctcall.dat", "r" ) }==NULL)

{

_settextposition (6,18); printf("Can't open file c»\\init\\ctcall .dat\n" ); printf("press any key to continue"); jnk-getch( ) ; else fscanf(ccal, "%f %f %f", &ccf[l][0], &ccf[l][l),

&ccf[l][2]); fscanf{ccal, "%f %f %f", 4ccf[l][3], &ccf[l][4], iccf[l][5]); fclose(ccal) ;

if ((ccal = fopenCcA\initWctcal2.dat", "r"))—NULL)

{

_settextposition(6,18); printf("Can't open file c:\\init\\ctcal2.dat\n" ) printf("press any key to continue"); jnk-getch( ) ;

} else

{ fscanf(ccal, "%f %f %f", &ccf[2][0], &ccf[2][l],

4ccf[2][2]); fscanf(ccal, "%f %f %f", -.σef[2][3], ϊ,cσf[2][4), ϊ,ccf[2][5]); fclose(ccal) ;

}

//

// The purpose of this code is to

// calculate the color code and quandrant biaed on the Y and 2 value

// measured from the frame grabber. Before the color code can be

// calculated, the RD and +b are calculatod and corrections are made

// to the Rd and +b value based on the autocalibration procβduro. int computo_color( float y_volt, float z_volt) βta iσ float g_f[10][5] =

{85.0, 31.468, 9.9655, -2.2792, 0.081001},

{80.0, 38.582, 5.9261, -1.024, 0.015288},

{75.0, 58.991, -0.7551, -0.046587, -0.016945},

{70.0, 74.096, -3.8331, 0.27064, -0.020759},

{65.0, 79.435,-3.2229,0.16912,-0.012738},

{60.0, 82.639,-1.8565,0.012919,-0.0055395},

{55.0, 86.638,-1.1747,-0.023637,-0.0040528},

{50.0, 92.997,-1.4781,0.03876,-0.0055587},

{45.0, 111.89,-4.8327,0.3288,-0.012375},

{40.0, 112.67,-1.0446,-0.07925,0.0006209};

} static float σ f[10][5) =

{

{85.0, -31.367,2.2224,0.32192,-0.0079989},

{80.0, -12.954,-2.4711,0.8563,-0.025021),

{75.0, -26.445,1.9071,0.5813,-0.019579},

{70.0, -35.051,5.1083,0.38343,-0.01612},

{65.0, -41.948,8.0383,0.15654,-0.01036),

{60.0, -41.597,8.6814,0.12265,-0.009735},

{55.0, -44.486,9.8471,0.04466,-0.0078969},

{50.0, -42.888,9.513,0.093693,-0.0092473},

{45.0, -49.896,11.552,-0.089758,-0.0032186},

{40.0, -54.457,12.609,-0.1676,-0.00075985};

} static int grange[17] = {0,15,20,25,30,35,40,45,50,55,60,65,70,

75,80,85,100}; static int crange[10] = {10,20,30,37,40,50,60,70,80,100}; static int grtbl[17] (10) =

{ {111,111,113,121,121,131,133,241,243,251}, {111,111,113,121,121,131,133,241,243,251}, {112,112,114,122,122,132,134,241,243,251}, {211,211,213,221,221,231,233,242,244,252}, {212,212,214,222,222,232,234,242,244,252}, {311,311,313,321,321,331,333,341,343,351}, {312,312,314,322,322,332,334,342,344,352}, {411,411,413,421,421,431,433,441,443,851}, {412,412,414,422,422,432,434,442,444,852}, {511,511,513,521,521,531,533,541,543,853}, {512,512,514,522,522,532,534,542,544,854}, {611,611,613,621,621,631,633,841,841,855}, {612,612,614,622,622,632,634,842,842,855}, {711,711,713,713,821,831,831,843,843,855}, {712,712,714,714,822,832,832,844,844,855}, {811,811,811,811,833,833,833,845,845,855}, {812,812,812,812,833,833,833,845,845,855}; static float p m=-1.4091; static float p^"b[6] » {86.3183,83.9183,81.2183,78.4183,75.1183,

71.8183};

static float p_of[6] = {14.0, 13.8, 13.6, 13.4, 13.2, 13.0}; float gh, gl, gx, ch, cl, ex, temp; float grade, colour, ycolor, zcolor, yσlr, zclr; int dk, dm, i, /*j,*/ return_flg; float plus__b_2, plus__b_3; return_flg-PASS;

} for(i=0; i<=9; i++) if(colour < crange[i))

{ dm=i; break;

> if((dk >=0 && dk <=16) && (dm >=0 && dm <=9)) colr=grtbl[dk] [dm] ; else return_flg-FAIL; break; case ON: for(i=0; i<=5; I++)

{ temp=plus_b*p_m+p b[i]; if(rd > temp) Ereak;

> colr-i+1 ; if(plus_b > p of[i]) colr=colr+l;

} last_read[camera] .y = yclr; last_read[camera] .z = zclr; last_read[camera] .rd - rd; last_read[camer ] .pb = plus b; last_read{camera] .cc = colr7l0; last_read[camera] .eg - colr%10; if (return_flg) last_read[camera) .cok=0; else last_read[camer ] .cok=l; return( return flg) ;

}

//

// end compute color

//

// end program

// This is the section of code in which the calculations are made on // the number of lint cleaners or seed cotton cleaners to use.

// ContDecF.C

//

#include "cainc.h" // all includes

#include "cadef.h" // all defines

#include "caext.h" //

#include "caproto.h" // prototypes of all functions

// ContDecF.C

// This procedure opens the decision matrix file for read.

// int open_deσision_matrix_ ile( void )

{ lc_decision_file = fopen( "cι\\init\\lcdec95a.out" , "r"); if (lc_decision_file == NULL)

{ display_error{ " Unable to open file lcdec95a.outl " ); return(O) ;

} scc_decision_file - fopen( "c:\\init\\sccd95a.out", "r"); if (sec decision file -- NULL)

{ display_error( " Unable to open file sccd95a.outl " ); return(O) ; } return(l) ;

} //

// ContDecF.C

// This procedure initializes the decision matrix

// void initialize_dec_matrix( void )

/* initializes decision matrix to all decisions = ' ' (blank) */

/* and all predicted values to 0 */ int rdindx, // Rd subscript pbindx, // +b subscript mindx, // moisture subscript lindx; // leaf subscript for ( dindx-0;rdindx<31 ;rdindx++) for (pbindx-0; bindx<21 ;pbindx++) for (mindx=0;mindx<13;mindx++) for (lindx-0;lindx<13;lindx++)

{ lσ_dec_rkb[ rdindx] [pbind ][mindx][ lindx ]=(byto) 3; sec dec rkb[rdindx] [pbindx] [mindx] [ lindx ]=(byto )4;

} roturn;

}

//

// ContDecF.C

// This procedure reads the lint cleaner decision file

// into the decision matrix

// int read_lc_deσ_file( void )

/* reads decision matrix file into decision matrix variable */

{ int i, j, rdindx, // Rd subscript pbindx, // +b subscript mindx, // moisture subscript lindx; // leaf subscript float r , rl, rpb; char c[40];

_settextposition(21,l) ; printf("Reading lc_decision_file" ) ; rewind ( lc_decision_file ); for (i=0;i<3549 i++)

{ fscanf(lc_deciβion_file," %f *f",&rl,&rm) ; for ( j=0; j<31?j++) fscanf(lc decision_file, " %σ",&c[j]); fscanf(lc_decision_file, " %f\n",&rpb) ; pbindx = (int) (rpb*2.0-10.0) ; // for 5.0 to 15.0 by 0.5 mindx = (int) (rm*2.0-6.0) ; // for 3.0 to 9.0 b 0.5 lindx - (int) (rl*2.0-4.0); // for 2.0 for (rdindx=0 ;rdindx<31 ;rdindx++) if ((rdindx =0) &£. (rdindx<31) &&

(pbindx>-0) && (pbindx<21) it

(mindx >=0) && (mindx <13) &4

(lindx >-0) &£, (lindx <13)

) lc_deσ_rkb[rdindx] [pbindx] [mindx] [lindx] = (byte ) { [rdindxJ-0x30 ) ;

} return(l);

>

// — ContDecF.C

// This procedure reads the seed cotton cleaner decision file

// into the decision matrix

// int read_scc dβe_ ilβ( void )

/* reads decTsion matrix file into decision matrix variable */

{ int i, j, rdindx, // Rd subscript pbindx, // +b subscript mindx, // moisture subscript lindx; // leaf subscript float rm,

rl, rpb; char c(40]; εettextposition(21 l) ; printf( 'Reading scσ_decision_file" ) ; rewind( βσc_deciβion_file ); for (i=0;i<3549;i++) fscanf (εcσ_decision_file," %f %f",&rl,&rm) ; for ( j-0; j<31; j++) fscanf(sec deciβion_file, %c",&c[j]); fscanf(sec deσision_file, " %f\n",&rpb); pbindx = (Int) (rpb*2.0-10.0) ; // for 5.0 to 15, by 0.5 mindx - (int) (rm*2.0-6.0); // for 3.0 to 9. by 0.5 lindx = (int)(rl*2.0-4.0); // for 2.0 to 8.0 by 0.5 for (rdindx=0;rdindx<31;rdindx++) if ((rdindx>-0) && (rdindx<31) fiSr // for 50.0 80.0

(pbindx>=0) && (pbindx<21) && // for 5.0 15.0 (mindx >-0) && (mindx <13) // for 3.0 9.0 (lindx >-0) && (lindx <13) // for 2.0 8.0 βcc_deσ_rkb[rdindx] [pbindx] [mindx] [lindx] * (byte) (c[rdindx)-0x30) ;

} return(l) ; }

// — ContDecF.C

// This procedure converts a color index to a color code,

// used in the microqin.

// int index__to color( int index )

/* converts Tndex( 0 - 14 ) to color and returns color */

{ switch( index )

{ case 0 return( 31 case 1 retur ( 32 case 2 return( 33 case 3 return( 41 case 4 return( 42 case 5 return( 43 case 6 return( 51 case 7 return( 52 case 8 return( 53 case 9 return( 61 case 10 return( 62 case 11 return( 63 case 12 return( 71 case 13 return( 72 case 14 return( 73 default return( 0 ); } roturn( 0 );

}

// ContDecF.C

//

// This code converts the color code to a color index,

// used in the microgin. int σolor_to_index( int color )

// converts color to index( 0 - 14 ) and returns color index

ContDecF.C

// This procedure was used to check the decision made based on // measurements made behind the gin stand and using the prediction // method. It uses data from the measurements after // the lint cleaners.

// int lc check( int code, double areapc ) switch( code ) { case 0 i return( 2 );

// try to get at least leaf 2 in this section

// try to get at least leaf 3 in this section case 12 i case 22 case 24 case 32 case 33 case 34 if ((areapc<0.55)£«,(areapc>0.35)) return(2); else return(l)? // try to got at least leaf 4 in this section caso 11 t

reapc<0.85)iJ<(areapc>0.55)) return(2) ; else return(l) get at least leaf 5 in this section

if ((areapc<l , 25) &&(areapoO. 85)) return(2 ) ; else return(l) // try to get at least leaf 6 in this section case €1 i case 62 i case 63 : if ( (areapc<2.35)&&(areapc>l. .25)) return(2) ; else return(l); // try to get at least leaf 7 in this section case 71 : if ( (areapc>2.35) ) return(2); else return(l); default : return( 2 );

} }

// ContDecF.C —

// Converts color code to price based restricted color codes.

// int color_ unction( int code )

// converts color code from color/trash meter to allowable color codes

//

{ switch( code )

{

ContDecF.C

int moist_to_index( float mo st )

// converts molβt( integer value 256.0 times real moisture ) to

// index( 0 - 28 ) */ float real_index; int index; real_index <= (float) (( moist - 3.0) *4.0 ); index - (int) ( real_indβx +0.5); if (index < 0) return( 0 ) ϊ if (index > 26) return( 26 ); return( index ) ;

}

// ContDecF.C

// Converts the trash to an index which points into the decision

// matrix file.

// int trash_to_index( float trash )

// converts trash( 72 to 100 by 2 ) to index( 0 - 14 )

// and returns index

{ float real_index; int index; real_index - (float) (( trash - T2.0 ) / 2.0); index = (int)( real_index +0.5); if (index < 0) return( 0 ); if (index > 14) return( 14 ); return( index );

}

// ContDecF.C

// Round color index for use with the matrix.

// int round_color( float real_color )

// returns integer value index which is rounded value

// of real_color index

{ int color; if (real_color »= (float) -1.00) return( 0 ); if (real_color > (float) 14.00) color = 14; else color - (int)( real_color +0.5); return( index to color( color ));

} ^{" "}

// _-_ > ContDecF.C

// Rounds trash index.

// int round_trash( float real trash )

// returns integer value whTch is rounded value of real_trash rβturn( 72 + 2 * (int)( (real_trash - 71.5) / 2.0 ));

}

// ContDecF.C

// Converts trash readings to a trash index.

// int trash_function( int sa, int βσ )

// converts area and count from color/trash meter to trash code

{ float real_trash; int area, count ; aroa - sa/10 ; count - so ; real trash - ( float) ( 109.78 - 0.33 * area - 0.37 + count ^"~ + 0.00146 * aroa * aroa + 0.0015 * count * count) ;

return ( (int)( real_trash+0.5 ) );

}

// ContDecF.C

// Used to round and smooth the data for control.

// void RKB_measurement_process( int sta )

// gets raw data and filters it

{ static float f_cσ[3]= {(float)O.O, (float)O.O, (float)O.O }, f_ta[3]« {(float)200.0, (float)200.0, (float)200.0 }, f_tct[3]={(float)50.0, (float)50.0, (float)50.0 }, f_mc[3]= {(float)7.0, (float)7.0, (float)7.0 };

/* there is new mc data each time */ CompOK{ ) ; if (last_read[sta] .mok==0)

{ f_mc[ sta ] - (float)0.8*f_mc[ sta ] + 0.2*las _read[ sta ) .m; l_read_data[ sta ].fmc = f_mσ[ sta ];

} return;

}

// ContDecF.C

// Used to conert the percent area measured by the trash meter to an

// estimated leaf value, used in the procing of cotton.

// int parea_to_clgr( double pa)

{

0.15) return(2);

0.35) return(3)

0.55) return(4)

0.85) return(5);

1.25) return(6);

2.35) retum{7); re urn ) ; } // end parea_to_clgr( )

// ContDecF.C

// Seed cotton cleaner lookup, uses the values of Rd, +b, moisture and // percent area to look up the optimum seed cotton cleaner use based // on the ColorL program output. int scc_lookup( int rdc, double pbc, double mσ, double pac) { int rdindx, pbindx, mindx, lindx; int βcclu;

// for out of bounds conditions if ( rdσ < 50 ) roturn(O); // beyond the tablo limits

if ( pbc >13.0 ) return(O); // beyond the table limits if ( pac <0.41 ) return(O); // perhaps rdindx = rde-50; if (rdindx < 0) rdindx = 0; // 0 .. 30 if (rdindx > 30) rdindx = 30; pbindx = (int) (pbc*2.0-10.0) ; // for 5.0 to 15.0 by 0.5 if (pbindx<0) pbindx-0; // 0 .. 20 if (pbindx>20) pbindx=20; mindx = (int) (mc*2.0-6.0) ; // for 3.0 to 9.0 by 0.5 if (mindx < 0) mindx - 0; // 0 .. 12 if (mindx > 12) mindx - 12;

// convert percent area to leaf index leaf=2 -> index-0 if (pac<0.10) lindx - 0; else if (pac<0.15) lindx = 0; // leaf 2 else if (pac<0.25) lindx - 1; else if (pac<0.35) lindx - 2; // leaf 3 else if (pac<0.45) lindx - 3; else if (pac<0.55) lindx = 4; // leaf 4 else if (pac<0.70) lindx - 5; else if (pac<0.85) lindx « 6; // leaf 5 else if (pac<1.05) lindx - 7; else if <pac<1.25) lindx - 8; // leaf 6 else if (pac<1.80) lindx = 9; else if (pac<2.35) lindx -10; // leaf 7 else if (pac<2.90) lindx -11; else lindx = 12; scclu » scc_dβc_rkb[rdindx] [pbindx] [mindx] [lindx] } return( acσlu) ; } // end sec looku ()

// ~ ContDecF.C

// Lint cleaner recommendation based on Rd, +b, moisture content and // percent area based on the output of the colorL program. int lc_lookup( int rdc, double pbc, double mσ, double pac) // pao^* = peccent srea trash { int rdindx, pbindx, mindx, lindx; int lcluj

// for out of bounds conditions if ( rdc < 50 ) return(l); // beyond the table limits if ( pbc >13.0 ) return(l); // beyond the table limits if { pac <0.41 ) return(l); // never need leaf below 3

// always have at least one lint cleaner

// convert values to table indiciea, and be sure they are in range rdindx - rdc-50; if (rdindx < 0) rdindx - 0; // 0 .. 30

if (rdindx > 30) rdindx - 30; pbindx - (int) (pbc*2.0-10.0); if (pbindx<0) pbindx=0; if (pbindx>20) pbindx=20; mindx - (int)(mc*2.0-6.0); if (mindx < 0) mindx « 0; if (mindx > 12) mindx = 12; // convert percent area to le

if (pac<0.10) lindx - 0; else if (pac<0.15) lindx = 0; // leaf 2 else if (pac<0.25) lindx - 1; else if (pac<0.35) lindx = 2; // leaf 3 else if (pac<0.45) lindx « 3; elae if (pac<0.55) lindx - 4; // leaf 4 else if (pac<0.70) lindx «= 5; else if (pac<0.85) lindx - 6; // leaf 5 else if (pac<1.05) lindx - 7; else if (pac<1.25) lindx = 8; // leaf 6 else if (pac<1.80) lindx - 9; else if (pac<2.35) lindx -10; // leaf 7 else if (pac<2.90) lindx -11; else lindx = 12; lclu - lc_dec_rkb[rdindx] [pbindx) [mindx] [lindx] ; return(lclu) ;

} // end lc_looku ( )

// ContDecF.C

// Rules of how many lint cleaners to use based on estimates.

// int rule_of_thumb( int color, double pa)

{ static int ltime=6, dir=0; if (cnlcl>=2) { switch (color)

{ case 51 i if (pa < 1.0) return(l); else return(2); case lit case 21: case 31 i case 12 i case 22i case 41s case 42 t if (pa < 0.7) return(l); else return(2); case 52 t if (pa < 0.5) return(l)} else return(2); turn(2);

olβo if (cnlc2>-2)

{ switch (color) { case 51 i if (pa < 0.7) return(l); else return(2); case lit case 21 t case 31t case 12 t case 22t case 41: case 42s if (pa 0.5) return(l); else return(2); case 52 t if (pa 0.3) return(l); else return(2); defaults return(2); } else return( 99 ); // not opperating normally

)

// ——_- ContDecF.C —

// Adjust the color index, when used as a pointer into the decision

// matrix.

// int fix_color index( int color index )

// temporary Junction to map allowable color indexes to

// ones in which data

// has been filled in for in decision matrix

{ switch( color__index ) { case 0 return( ); case 1 return! ); case 2 return! >; case 3 return! ); case 4 return! )ι case 5 return! ); case 6 return! ); case 7 return! )> case 8 return! ); case 9 return! )ι case 10 retur ( 8 ); case 11 return! 8 ) case 12 return! 8 ) ι caso 13 return! 8 ); case 14 return! 8 ); default return! color_index ) ;

}

// ContDecF.C

// End ContDecF.C

// This code

// relates to digital input and output. The main portion is for

// bitwise communication with the PLC, control of the samplers, and

// reading of the position sensors in the system. In addition,

// there is software to read files on the local area network for

// communication with other computers that are measuring things

// associated with the gin system.

// DigitallOF.C

#inσludβ "cainc.h" // all includes #include "cadef.h" // all defines /include "caβxt.h" // #include "caproto.h' // prototypes of all functions

// DigitallOF.C

// This iβ declaration of a local function that is only available // within this section of code. // local use function void doio(byte, int);

// DigitallOF.C

// This is the code for getting one byte of data from the digital I/O // board. There are two boards each of them has three bytes of data, // the addresses are not contiguous and this code reads one of the // first six eight bit bytes of digital input data. byte i_get(byte pt) { switch (pt)

{ // if port case Ot return (byte)inp(0x310) ; break; case It return !byte)inp!θx311) ; break; case 2ι return !byte)inp!θx312); break; case 3t return !byte)inp!θx314) ; break; case 4: return !byte)inp!θx315) ; break; case 5t return (byte) inp!0x316) ; break; defaults return !byte) (OxFF) ;

}

} // DigitallOF.C

// This code allows the program to change one bit of the data at a // time. void o_set(bytθ mode, byte βw )

( if ((mode«0) || (mode—1)) doio(mode,βw) ; }

// DigitallOF.C

//This code alternately switches one bit between high and low and is // attached to a monostable multi-vibrator. If the code iβ operating // properly, it will reset this switch so that the monostable stays in // the computer OK state at all times. If the software in tho computer // for βomo reason stops operation, this switch will chango to error

// condition which can be sensed by other computers or components in // the system to determine that the computer has lost control of the // process. This is a safety feature. void CompOK(void) { static byte lt-0; if (It) {lt=0;doio(0,20);} else (lt-l;doio(l,20);}

} //

// DigitallOF.C

// This section keeps a record of each bit of the six bytes of digital

// output that are possible with the digital input and output

// hardware. It allows software to change one bit at a time, turning

// it either to one or zero and then output the resulting value to

// the appropriate port to implement the change. This code allows

// the other software to be relatively transparent to the

// actual hardware but functions to switch individual bits in a

// controlled manner. void doio(byte func, int value)

{ static byte psβt[6)={0xFF,OxFF,0xFF,0xFF,OxFF,0xFF}; // for func=l - turn switch on // for func-0 - turn switch off // switches numbered 1 .. 48 // output ports are 0, 1, 2, 3, 4, 5 int prt> byte a; prt = (value-l)/8; value - l«((value-l)%8); if (prt<0) prt«=0; if (prt>5) prt-5; a»pset[prt] ; // 1 -> switch off, 0 -> switch on if (func»l) // turn switch or switches on if func=-l

{ psettprt] &β -value; \ else if (func»0) // else turn switch or switches off

{ psβt[prt] |- value; } if (prt<3) outp(0x310+prt,pβet[ r ) ) ; else if (prt<6) outp(0x314+prt-3,pset[prt] ) ;

//

// DigitallOF.C

// code to make PLC seed cotton cleaner control untrue,

// to set the PLC seed cotton cleaner control to rsσc, and then

// to make PLC seed cotton cleaner control true

//

// This code is used to control the signal sent to the PLC determining

// tho request for seed cotton cleaning equipment. It can either,

// depending on the function passed to it, be set to untrue, meaning // the value is invalid and no change should be made or it can be set // for 0, 1, 2, or 3 seed cotton cleaners and then can be set to true // to indicate the proper data is available on the bits that signal // how many seed cotton cleaners should be used. void PLC_scc(int func)

{ switch ( func)

{

// set false case Oi doio(l,19); break;

// set two bits to control number of seec cotton cleaners case It

// on rβcc 2-uβe stick machine, 1-use impact cleaner switch (rscc) // rscc - recommended number of seed cotton cleaners { case 0s doio(l,30); doio(l,31); break; case 1: doio!θ,30); doio!l,31); break; case 2t doio!l,30); doio!θ,31); break; case 3s doio!θ,30); doio!θ,31); break; break;

// set true case 2 i doio(0,19); break;

} }

// // DigitallOF.C // code to make PLC lint cleaner control untrue, // to set the PLC lint cleaner control to rnlc, and then // to make PLC lint cleaner control true void PLC_lc(int func)

// This code iβ used to control the signal sent to the PLC determining

// the request for lint cleaning equipment. It can either, depending

// on the function passed to it, be set to untrue, meaning the value

// is invalid and no change should be made or it can be set for 0, 1,

II 2 , or 3 lint cleaners and then can be set to true to indicate the

// proper data is available on the bits that signal how many lint

// cleaners should be used.

{ switch ( unc ) {

// set false case Oi doio(l,19); break; // set two bits to control number of lint cleaners case It if (rnlcl-l) // rnlc - recommended number of lint cleaners

{ doio(0,17); doio(0,18); } // set both bits high // use. two unless specifically one lint cleaner else { doio(0,17); doio(l,18); } // set one bit high break; // set true case 2t doio(0,19); break;

)

//

// DigitallOF.C

// This code implements switches of the bits which control the sample

// flappers. It allows one command to open or close all the

// flappers or open and close individual flappers in the pattern that

// is used under normal operation of ginning. Additional code

// allows opening and closing of the extra sampler and allows closing

// individual flappers one at a time. void flapper(int nextch)

{ switch (nextch) { // extra sampler controlled at 32 case 3t o_βet(0,9); o_βet(0,12); o_set(0,25); break; // open 0, 1, 2

defaults o_set(0,9) ;o_set(0,12) ;o_set(0,25) ;

// open 0, 1, 2 >

}

// DigitallOF.C

// This section controls movement of the calibration flappers. It

// allows opening and closing of individual calibration flappers at

// all three stations. It includes special code for station two to

// switch moro than ono lino so that tho dual stroke valvo will bo

// properly used.

// void calflap( int setup )

// close and open the correct calibration flappers based on setup //

{ switch (setup) case 10s doio(0,10) ;break; // open calibration flapper 1 case 20s doio(l,13); doio(0,14); doio(0,15); doio(l,16); delay(100) ;doio(0,13) ; break; // calibration

//flapper 2 to no tile // extend long, retract short case 30: doio(0,26); break; // open calibration flapper 3 case lit doio!l,10); break; // close calibration flapperl case 21s doio!θ,13); doio(0,14); doio{0,15); doio(0,16); break; // no use of this for 2 case 31s doio(l,26); break; // close calibration flapper 3 case 12s doio(0,ll); break; // calibration flapper 1 to color case 22s doio(0,13); doio(l,14) doio(0,15); doio(0,16); delay(lOO) ;doio(0,14) ; break; // calibration flapper 2 to color case 32s doio(0,27); break; // calibration flapper 3 to color case 13s doio(l,ll); break; // calibration flapper 1 to trash case 23s doio!l,13); doio(0,14); doio(l,15); doio(0,16); delay( 100) ;doio( 0,13); break; // calibration flapper to trash case 33 t doio(l,27); break; // calibration flapper to trash defaults break;

} } // end calflap

// // DigitallOF.C

// This code checks for a new tag message. This tag message is created II by & computer that reads the bar code tag that has been attached to // the bale. The message contains the bale weight. // If a new tag message is

// available it first renames the file, then reads, and then erases // the file on the network. The data iβ then used by the program, void chk tagmsg (void ) { int f;

FILE *fptr; int renval; renval^»rename Cgι \\data002\\tag.msgV*gι \\data002\\yyy.msg" ) ; if (renval— 0 )

{ // file exists fptr ^« fopen( "gt\\data002\\yyy.msg" , "r" ) ; // read the data for (i=0; i<60; i++) fscanf ( fptr, "%α" ,fitag_msg[ i ] ) ; tag_msg[60 )«0x00j // null - end of string

a he at the

n // added so that extraneous bales are not counted. void chk_bc( void ) { static int l_bc-0; static time_t l_bctime; static bcβtαte ~ 0; int c_bc; timβ__t c bctime;

FILE *fptr; long int locbn, dif; int lwt; int renval; int i, j, ns, tmp; float sum; renval«rename("g_t\.\data002\\bale.msg","gs\\data002\\xxx.msg"); if (renval^β-0) fptr - fopen("gt\\data002\\xxx.msg","r");

// read the data f scanf (fptr, " %ld %d" ,&locbn, &lwt) ; fσlose!fptr) ;

// erase the file remove( ^Mgt\\dαta002\\xxx.msg" ) ;

rS_J_dat[ 12]=(SJ_dat[ 12 ]-2047)*20.0/4095.0*1.44+0.0; bdat[0] .b =!int) (rSJ_dat[ 12]*10.0+0.5) ; //save data to permanent data balm_dsk_save ( ) ;

;

time(&c_bctime) ; it 6 - D7 / / / / / C i {

else

{ // 0 if (difftime(c_bctime, l_bctime)>2) { bcstate = 1; inc_bn(2); if (lbn++>4) lbn=4; return;

} else return;

} else // bcstate »» 1

// read the bale moisture meter return;

} else return;

} else

{ l_bc-l; // 1 0 1 l_bctime-c_bctime; } } pi a _Q

{ if (c_bc—0) // 1 1 0

{ l_bc-0; l_bctime«c_bctime; return; else return; // 1 1 1

} >

// DigitallOF.C

// This code reads the current number of lint cleaners for each of the // gin stands and the number of seed cotton cleaners being used a^β // transmitted to the control computer by the PLC. void ohk leu(void) // need to revise // looks OK

int wait_samp_open ((iinιt fl)

{ time_t inittime, c<time;, byte fladd[4] - { 16, 32, 2, 1 }; // bit for flapper open input byte flprt[4) = { 2, 4, 5, 2 }; // port for flapper input int dtf l = - {/ R8,. ft8,. 10, 8 }; // max wait for flapper to open, seconds byte flnopen; int done; int ret; done-0; time( &inittime) ;

;

olse rot-0; // low bit is signal that sample not open

if (done1-0) ret+-128; // Fl pressed return(ret) ;

}

// end wait_samp_open

// DigitallOF.C

// This code waits for a calibration paddle to close as measured by // the proximity switches. It operates just as the previous procedure. int wait_cal closed(int fl) { time_t inTttime, ctime; byte fladd[4] - {128,128, 4, 1 }; // bit for flapper open input byte flprt[4] - { 2, 4, 5, 2 ); // port for flapper input int dt[4] = { 8, 8, 10, 8 }; // max wait for flapper to open, seconds byte flnopen; int done; int ret; done=0; time( &inittime) ; if <fl«l) return(O); // temporary, no sensors at sta 2 do

{ chk_bc( ) ; time(&ctime) ; flnopen - (byte) (-(byte)i_get(flprt[ fl] ) & fladd[fl]); done»do_freq( ) ; while ( (ctime-inittime<dt[fl)) && (flnopen ) && (done l-l) ) ; delay(100); // wait another 0.1 second if (flnopen ) ret-8; else ret«=0; // low bit is signal that sample not open if (donel-0) ret+-128; // Fl pressed return(ret) ;

// end wait_cαl closed

// -..„—T— DigitallOF.C

// This code waits for calibration flapper to open as determined by // the proximity switches attached to the calibration flapper. It // operates in the same manner as the wait_samp_open procedure. int wαit_cαl open(int fl) { time t inTttime, ctime;

// ^"

// byte fladd[4] «= { 64, // bit for flapper open input byte flprt[4] - { 2, // port for flapper input int dt[4] - { 8,

// max wait for flapper to open, seconds byte flnopen; int done; int rot;

dif

fread(od,sizeof(od[0] ) ,8,kpdat) ; // data not needed fread(od,sizeof!od[0] ) ,5,kpdat) ; // data not needed fread!tag_msg,sizeof(char) ,60,kpdat); // needed

} if (kpdat 1- NULL) fclose( pdat) ;

// DigitallOF.C

//

// This code displays information on the operation of the machinery, // the control decisions, how the decisions are reached, the data, and // the bale averages for the past 10 bales on the screen in the gin.

//

// DisplayF.c

//

/include "cainc.h" // all includes

/include "cadef.h" // all defines

/include "caext.h" //

/include "caproto.h" // prototypes of all functions

//

// DisplayF.c void display_message( message ) char message[ ] ;

{ int i; static int nrow=24, ncol=0; _settextposition(nrow,ncol) ; for (i=0; ( (i<40)&&(message[i] 1=0x00) ) ;i++)

{ printf{ "%c" ,message[i]);

} if (ncoll-0) {nσol-0; nrow++;} else ncol-40; if !nrow>25) nrow=24;

} //

// DisplayF.c

// displays error message in the error message area // keeps error messages n order, does not write // outside message area, 30 char. Message ending in 0x00 // void display_error( error_message ) char error message! ];

{ int i; static int nrow-13; return; // testing

//

// DisplayF.c

//

// Prints the display headings , only, on the computer screen. void print_diβplay_heading3 ( void )

_βetbkcolor ( 0 ) ; ^"βettextcolor ( 3 ) ;

_sottoxtposition( l _f 1 ) ; printf C Fl»Main Menu; F2=Bale N. vs . " ,

" Data- F4=BA/Cal"); _settextposition( 2 , 7 ) ; printf(" Color %% Area Moisture "); _settextposition(3,35); printf("Seed Cot."); _βettextposition!4,35); printf("Before LC"); _settextposition(5,35); printf("After LC" ) ;

> //

// — — DisplayF.c

// Displays color, trash, moisture contents, current decisions,

// current operating conditions (how many lint cleaners operating,

// etc.

// void showCT( int camera ) // camera — 0, 1, 2

{ int RBln /*, i*/ , cnlc; long dt; char string[80]; time t ltime, oldtime; doubϊe dtcall, dtcal2, msb; βhowCalBa(); // every time βhowCT is called if (camera—1)

{

_ββtbkcolo {0 ) ;

_clearscreen(_GCLEARSCREEN) ; print display headings ( ) ; showcτ(θ); /7 recursive, keep #0 data on screen longer showCT(2); // recursive, keep /2 data on screen longer

_settextcolor(7); // for all three displays switch (camera)

{ case Ot RBln-3;_setbkcolor(l);break; case It RBln«4;_setbkcolor!5);break; case 21 RBln_*5;^"~setbkcolor!4 ) ;break;

> settextposition(RBln,45) s^"printf(string," %3d %4.1f \0x00" lαβt_reαd[camera] .rd,last_read[camera] .pb, last_read[camera] .cc, last_read[camera] .areapc) ; _outtβxt(string) ; _settextposition!RBln,61) ; sprintf(string," %5.1f %\0x00" , last_read[camera] . ) ; _outtext( strin ) ; _βetbkcolor( 0 ) ;_settextcolor(3 ) ; _βettextpositlon{9,2) ;_outtext!tag_msg) ; _8θttextposition!l0,8) ; time/iltime) ; oldtime - ccαltime[l];

if(tcaltime[l]<oldtime) oldtime = tcaltime[l]; dtcall-(ltime-oldtime) /3600.0; oldtime = ccaltime[2]; if(tcaltime[2]<oldtime) oldtime - tcaltime[2]; dtcal2=(ltime-oldtime) /3600.0 ; sprintf!string," hours since calibration %5.1f sta.2 %5.1f sta.3 \0x00", dtcall,dtcαl2);

_outtext( string) ;

" ,camβra+l ,cnlc) ; " ,camera+l,cnlσ) ;

break; case 1 :

_setbkcolor(4); // It blue _outtext{ "Working on Ch 3"); break; case 2t // was case 2t

_setbkcolor(l) ; // red _outtext("Working on Ch 1"); break;

_setbkcolor(0) ; // black _settextcolor(3) ; settextposition(9,30) ;

// DisplayF.c

//

// Displays data on the last 10 bales on the screen.

//

// void showBA( void )

{ int i; char st[30] ;

sprintf(st, " %2d %ld \0x00", ba[l][i].color, ba[ 1 ) [i] .leaf) ; _outtext(βt) ; _setbkcolor( ) ; settextcolor( 7 ) ; sprintf(st," %2d %ld \0x00", ba[2][i]-color,ba[2][i].leaf); _outtex (s ) ; _setbkcolor(0) ; settextcolo ( 3 ) ; sprintf(st," %4.1f %4.1f %4.1f ", ba[l] [i] .me, ba[2] [i] .mc, bdat_rate[i] ) ; _outtext(st) ;

} } else showCalBa();

}

// DisplayF.c

// Displays calibration and other data in the same area where the bale

// average data is normally displayed.

//

// void showCalBα( void )

{ int i, j; char st[80]; if (sbas=0) showBAOr else

{

_setbkcolo (5 ) ; _settextcolor(0) ; _εettextposition( 11,22); _outtext ( " Calibration and Temperature Data

");

_settβxtcolor(7 ) ;

_settextposition(12,22) ; . sprintf(st," %7.3f %7.3f %7.3f *7.3f \ inty[l], slpy[l], intz[l], slpz[l]); outtext(st) ; for ( j=0; j<3; j++)

{

1-0;

{

_BQttextposition( 13+j*2+i , 22 ) ; sprint (st, "%10.2f %10.2f %10.2f II / ctile[i][i].rd,ctile[i][j].pb,ctilβ[i][ ].areapc)

_outtext(BX);

) ;

// This is the main part of the program, where the processing starts.

// The first external file that is included

// in this file is "cainc.h", this file has all the included extra

// files most of which are part of the Microsoft "C" package. The next

// included file is "cadef.h" which has most of the defines of

// variables with defined values. Most of them are related to the

// color software but a few of them are related to the trash software.

// There are defines elsewhere also. The next statement defines this

// piece of code, "Lcadvl.C" as the main section which is used by the

// "c" compiler in the following piece of code "caext.h" which is the

// declaration of the global variables. This program uses many global

// variables through which most of the data is passed.

// The final include in this program is "caproto.h" which

// is a prototype of all functions that are used and has a list of

// included files. There is one *.h" file for each of the "C"

// source code files.

//

// LCADVl.C

/include "cainc.h" // all includes /include "cadef.h" // all defines /define MAIN_SECTION // this is the main section /include "caext.h" II /include "caproto.h" II prototypes of all functions

// LCADVl.C

// The processing starts and ends in this section. It records the

// current values of the computer screen setup, runs a setup

// procedure, runs the open menu procedure, and when the program

// returns from open menu, puts the screen back into the mode it was

// in when the program was called and exits the program. void main(void)

{ long oldbgd; short oldfgd; oldfgd - _gettextcolor( ) ; oldbgd - _getbkcolor( ) ; error-0 ; βetvideomode(_TEXTC80) ; _setbkcolor(0 ) ; βettextcolor(3) ;

openmenu( ) ; ^k _^f _write ( ) ; // write the keep data file σleαrβcreen(__GCLEARSCREEN) ; ^βotvidoomodoT_^DEFAULTMODE) ;

setbkcolor(oldbgd) ; settextcolor(oldfgd) ; } // end main

// LCADVl.C

// The sections of "o_set" are setting up output control lines

// to be either high or low depending on which is safest for the gin.

// Files and variables are set to initial conditions, O's and l's.

// void setup(void)

{ int fo=0, fr-0, i, j; time_t ltime; done -0; // not ready to exit yet if (read_tcal() 1=0) error=l;

// setup CIO_DI024 in CI0-DAS16/F Low 24 bits of PIA

// 1-8 Input, 9-16 output, 17-20 output, 21-24 input outp(0x313,0x98) ;

// setup CIO-DI024 High 24 bits of PIA

// 1-8 Output, 9-16 Input, 17-20 Input, 21-24 Input outp(0x317 ,0x8B) ;

// set all outputs to low o_set(0, 9); o set(0,10); o_set!θ,ll); o~set!θ,12) o_set(0,13); o_βet!θ,14); o_set!θ,15) o_set!l,16) ; o_set!l,17); o_set!l,18) o_set!θ,19); o_set!θ,20) o_βet!θ,25); o_set!θ,26) o_set!θ,27); o_set!θ,28) o_set(0,29) ; o_set!θ,30); o_βet!θ,31) o_set!θ,32);

PLC_lc(0); // set pic control to untrue _clearβcreen(_GCLEARSCREEN) ;

;}

tag_msg[0]=' ' ;tag_msg[l)='T' ;tag_msg[2]-'a' ; tag_msg[3]= 'g* ;tag_msg[4 ]= ' . ' ;tag_msg[5)='m' ; tag_msg[6]-*s' ;tag_msg[7]-*g* ;tag_msg[8]-' ' ; tag_msg[60]=0x00;

// If thoy press a 3, tho program outputs a vary ng βor os of b te to

// the output data lines so that they can be checked. If they press a // 5, the code to calibrate station 1 is entered, if they press a 6, // the code to calibrate station 2 is entered, and if they press a 7, // the code to calibrate station 3 is entered. If they press an b, // autocal for station 3 is switched on or off and the setting is // displayed on the menu. If they press a 9, station 3 is calibrated // by using autocal. If they press a small letter "a", station 1 is // calibrated for trash; "b" , station 2 iβ calibrated for trash; "c", // station 3 iβ calibrated for trash; "d", seed cotton cleaner // selection is changed. The bits that are passed to the PLC which // does the actual seed cotton switching so that those bits can be // debugged. If they press α "e", the values from the analog converter // are displayed so the analog inputs could be checked. If they press // " f , a measurement of color and trash iβ immediately obtained from // one of the stations and displayed on the screen. If they press "g", // the system requests the PLC to switch to one lint cleaner. If they // press "h" , the system requests that the PLC switch to two lint // cleaners. If they press an "I", all the sample flappers are // switched between open and closed with repeated pressings. If they // press "j", the system will cycle the calibration tiles for stations // 2 and 3, between open, color, open, trash. Pressing a "k" causes // the tag message to be checked. The tag message is a message the // computer at the bale press which reads the bar coded tag of the // bale sends to this controlling program over the network. If they // press a "1", the samplers cycle between station 1, station 2, and // station 3 as they normally would during a data collection phase. // When they press "m" , the extra sampler which is used for infrared // moisture measurements behind the gin stand is alternately opened // and closed. If they press "x" or a "X", the program will exit // to the operating system. void openmen (void)

{ int cx,cc-0; int io_ctr«l, ia, ib, i, sum, j, tmp, ii-O, ij=0; double volt; unsigned short PortX-O, Stat; unsigned char cl; static int recce, flcy, efl, mice; time_t ltime; // temp menulOs clearβcreen( GCLEARSCKEEN) ; time ( 6ltime)^"•^"

_βettextpoβition(24, 2) ; rintf ("%81d " , ltime);

_βettextpoβition( 4 ,26) ;printf CM A I N M E N U");

_ββttextposition( 6,26);print ("0. Self Calibrate Station 2 Now" ) > βettextposi ion( 7,26) ; rintf("1. Run Color/Trash CalcuTαtionβ" ) ;

_βottoxtpoβition ( 8,26);printf ("2. Ro d Digital Inputs");

"); "); "); Now" "); "); "); menu

; }

delay(200); camera — cc; getdata( ) ;

_settextposition(1 ,1 ) ; printfC for camera *2d area=%5.1f percent area= 5.2f

T/US97/13553

{ // cycle calibration flappers if (ij—0) { calflap(20); calflap(30); // open color calflap(32);

_8βttextposition(3,9); printf(" cal. fl. open color 0"); } if (ij—1) { calflap(23); cαlflαp(31); // close trash calflap!33);

_βettextposition(3,9); printf(" cαl. fl. closed tr sh 1");

} if (ij—2)

{ calflap(30); // open trash cal lap(33);

_βettextposition(3,9) ; printf(" cal. fl. open trash 2");

} if (ij—3)

{ calflap(22); cαlflαp(31); // close color calflap(32);

_βettextpoβition(3,9); printf(" cαl. fl. closed color 3");

} if (++ij>3) ij-0; goto menu20;

} if(ex —'k') { chk_tαgmsg(); goto menu20; } if(ex =='1' )

{ if (flcy>2) flcy«0; if (flcy<0) flcy=0; flapper(fley) ; flcy++; goto menu20;

Lf( («ex --'m') // toggle extra sampler open/closed

{ if (βfll-0) { efl-0;flαpper(β);} // close else {e l=l; flapper(9);) //open goto menu20;

} if (ex — 'f)

{ _βettext osition( 22 , 1 ) ; printf("%101d %101d %101d", ccaltime[0) ,ccaltime[ 1 ] ,ccaltime[2 ] ) ; printfC%101d %101d %101d", tcaltime[ 0] ,tcaltime[l] ,tcaltime[2 ] ) ; goto menu20;

) if (ex BB ' X ' ) return; if (ex — 'X ' ) return;

//missed j printf ( "\a" ) ;

goto menulO; // bell } // end openmenu //

// This is the main procedure for data collection and control. This // procedure starts by clearing the screen and initializing α few of // the variables and then cycles continuously until a function key is // pressed to exit this cycling software. It sets up the frame grabber // which is used in the trash measurement, checks for the function key // being pressed, and then measures some of the analog inputs not // related to color or trash. It checks the last moisture readings and // if they are within α reasonable range, leaves them unchanged, if // they are not within a reasonable range, it sets them to values // which are obviously extreme and so that the other software can // detect that they were incorrect readings. It then starts with // camera one, sets the flappers to collect α sample of flapper one, // adds the most recent readings from station three to the running // total so that the averages can be calculated, checks for a message // from the computer at the bale press, computes some of the factors // needed for automated control, and then does a wait closure one. The // wait closure waits for α certain period of time or for closure of // the sample flapper whichever comes first. There is nothing in this // program that waits infinitely long, every procedure exits in a // relatively short period of time so that if something malfunctions // the rest of the program will .continue to function. Once the flapper // has closed or has timed out, "getdata" collects the data for // station one. Similar procedures are repeated for station two and // then for station three. Every other cycle through this code, the // sampler behind the gin stand which collects samples for infrared // moisture readings is opened for a short time and then closed again. // Just before it is opened, a reading of the moisture content from // the infrared meter is taken and recorded. Next, the recommended // number of lint cleaners based on the readings of station two are // calculated and the recommended number of lint cleaners based on the // readings of station three are calculated. Also, the recommended // seed cotton cleaner settings are calculated. In all of these // calculations -in this code, the recommendations are based on // measured rd, measure +b, the measured percent area of trash, but 5% // moisture content is used. When adequate measures of moisture // content are available, the actual moisture content will be used in // these function. The next portion of code basically counts up and // down within rather narrow limits and when it reaches the upper // limit it uses two lint cleaners and when it reaches the lower one, // it uses one lint cleaner. This approach provides a hyβterβis into // the decisions so that the change from one to two lint cleaners is // never made immediately based on one set of readings and the amount // of hystereis can easily be changed in the software. There are two // counters, one for the decision at station 2 and one for the // decision at station 3. The counter for station 2 is run only if gin // stand 2 is "in" because otherwise there was no cotton for a valid // reading. If the decision based on the two totals agrees it is uβod. //

// If station 3 calls for 1 lint cleaner, only one is

// used. This section of code checks the time of day and if it is just

// past midnight, it switches to a new file. It keeps track of the

// next time for autocalibration and if autocalibration is turned on

// and it is time for a new autocalibration, it calls the autocal

// function. Finally, it goes back to the beginning of this procedure

// and repeats again.

// void getdata2(void)

{ int done, nlcn»0, nlcnl, nlcn2; static int ntb=4, nt3=4; static int phour; time_^t ctime; βtruc^"t doβdate_t ddate; struct doatime_t dtime; unsigned char cday; unsigned char cmo; unsigned int cyr; cday-0; cmo"0; cyr»0; cloarscreen(_GCLEARSCREEN) ; Hone=0; color_init( ) ; if (read_tcαl( ) 1-0 ) error-1 ; runscreen( ) ; flapper(8); // close SJ sampler _dos_gettimβ(fidti e) ; phour=dtime.hour;

// don't do autocalibration of station 3 immediately regetdatat

nc_bt(0); // add observed values to bale totals

nlcnl = lc_lookup( (int)last_read[l] .rd, last_read[ 1 ] . b, 5.0, // l_reαd__dαtα[1 } . f e lαst_reαd[l ] .αreαpc) ; rscc =scc_lookup( (int)last_readlOJ .rd, last_read[0) .pb, 5.0, // l_read__dαta[1) . f σ last_read[θ .areape) ; // correct for conditions at lint flue nlcn2 = lc__check(last__readt2) .cc,last_read[2) .areαpσ) ;

delay(200);

} // end getdatα2

//

// This section initializes the most recent measurements of

// color trash.

// void runscreen(void)

{ int i;

/* zero the readin array */

// LCADVl.C

// This procedure controls the actual color and trash data collection.

// There are three sets of code based on the camera count with camera

// counts being 0 1, and 2. It first sets up the frame grabber

// channel by switching the multiplexer between the three channels. It

// con switch up to eight channels with the current hardware. Next, it

// does a trash and color measurement, checks the measurements and if

// the readings are within a reasonable range it leaves them

// unchanged. Otherwise, it changes the readings to extreme values so

// that the other parts of the code can detect that the reading iβ

// incorrect.

// void getdata(void) int i-=0; int α_βtatus[4];

CompOK() ; setup_trash(camera) ; last_read[camera] .tok-0; switch (camera)

{ // wait a little and get traβh case O t delay( 400 ) ; do_a_frame ( camera ) ; break; case I t delay(400) ; do_a_frame ( camera ) ; break; case 2 ι delay( 400 ) ; do_a~frame ( camera ) ; break;

} colr= 0 ; c_status[i]= 1; c_βtatus[i]- colrmgr(camera) ; if ( last_read[camera] .pb<( float)4.0) las _rea [camera] .pb=(floa )0.1 ; if (last read[camera] .pb>( float) 17.0) last_rea3[cameraJ .pb-(float)99.9; if (last_read[camera].rd<(float) 45.0) last_read[camera] .rd=(float) 0.1; if (last_reαd[camera] ,rd>(float)86.0) last_read(camera] .rd=(float)99.9; if (last_read[camera] ,area<(float) 1.0) { last_read[camera] .area-(float)1.0; last_read[earnera] .tok—1;

} if ( last_read[camera].αreα (float)9999.0) last read[camera].areα=(float)9999.0; if (Tast__read[camera] .count<(float)1.0) { last_read[camera] .count*(float) 1.0; last_read(camera] .tok-1;

} if (last_read[camera].count>(float)999.0) ( last_read[camera] ,count-(float)999.0; last_read(camera] ,tok=l;

} if (last_read[camera) .leaf<(float)1.0) last_read[camera] .leaf=(float) 1.0 ; if ( laet_read[camera] .leaf>( float)9.9 ) last_read[camera) . leaf-(float)9.9; if (last read[camera].cc>88) last_read[camera] .cc= 99; if (last~~read[camera].cc<10) last~read(camera] .cc= 1? last__read^~[camera] .ctsn-sample_^no; last^""read[camera] .cmpg-2 j if (last_reαd[cam ra].cmpg>88) last_read[camera) .cmpg-999; if ( last_hread[camera] .cmpg<10) last_read[camer ] .cmpg» 1; last_read[camera] . b-(float)0.0; } // end getdata

// LCADV.C

// This section of code runs automatic calibrations at

// station two or three. The code is divided into two

// large sections, one dealing with one type of calibration

// reference tile presentation and the other dealing with

// the other kind of tile presentation. The procedure

// begins by opening and closing the calibration tile

// flappers a few times because dust tends to settle

// on the calibration tiles especially at station two when the

// calibrator iβ not being used. Moving them while ginning

// removes most of the dust. When calibration is finished the flappers

// aro opened and closed quickly several times to help dislodge any // cotton that may have been caught on the flappers,

// void autocal(int sta)

// station 1, 2

flapper position 0, 1 and rep. t me_t ct mer for (i-0;i<6;i++)

{ ctile[i][βta].rd - 0.0; ctile[i][sta] .pb = 0.0; ctile[i][sta] .y = 0.0; ctile[i][sta) ,z ^s 0.0; ctile[i)[sta].areapc = 0.0;

} stao = sta*10+10; outp(DT2859,sta) ; // switch to Video input calibrating cf_ok[βta)-0; // set all bits low flapper(99); // open the sample flappers jnk = start fg(); // reset frame grabber

// divided Into two separate secions for station 1 and station 2 if (sta«l)

{ delay(200); // to allow time for cotton sampler to open // "jiggle" the flappers here, try to clear off dust for (i=0;i<3ji++) { _βettβxtposition(24,l); printf("Cαl. sta%ld stp %2d clear ",βtα+l,i); // trash position calflap(23)> delay(100), flαpper(l+stαo); delay(500); delay(500); dβlay(SOO); flapper(99); delay(400); delay(400); // color position calflap{22); delay(100); flapper(l+stao); delay(SOO); delay(500); delay(500); flapper(99); delay(400); delay(400);

// open position cal lap(20); delay(lOO); flapper{l+stao) ; delay(500); dela (500);

;

do a_frαme(cαm) ; do the tr s measuremen

ctile[cf os ] [cam] .areape » last_read[cam] .areape;

} flapper(99) ; // open all sample flappers outp(DT2859,sta) ; // switch to Video input "sta* delay(500); delay(500); delay(500);

// time to open 1 sec. too little calflap(30);

// open calibration flapper delay(500);

} // for all positions

// open calibration flappers calflap(30) ; delay(800 ) ; { calflap(32) ;

// be sure flappers are in color position

} delay(500); // wait a little

// check that cal flapper is in open position

// jiggle the flappers here calflap(stao+0) ; // start open calflap(βtao+2); // start color delay(500); calflap(8tao+l ) ; // close calflap(βtao+3); // trash delay(100); calflap(stao+0); // open calflap(stao+3) ; // trash delay(500); calflap(βtao+l) ; // close calflap(stao+2) ; // color delay(100); calflap(stao+0) j // open calflαp(stαo+2) ; // color delay(500); cαlflap(βtao+l) j // close calfla (βtao+3 ) ; // trash delay(100); calflap(stao+0) ; // open calflap(stao+3) ; // trash delay(SOO); calflap(βtao+2) ; // end color calflap(stao+0 \ ; // end open

// end autocal station -

// restore the regular readings last_read[cam] .rd rdkp[cam]; last_read[cam) .pb 3 pbkp[cam] ; last_read[cam] .cc = cckp[camj laβt~rcad[cam] .area areakp[cam] ; last^hread[cam] .areape arpckp[cam]; laβt_read[cam] .count countkp[cam] ;

last_read[cam] .leaf - leafkp[cam]; time(&ctime) ; cctime[sta]=ctime+3600;

// eetime is next time to check calc_ctmean(βta) ; dsk_save_cal_tile( sta ); // save readings to file // record the calibration check data to disk rec_ctile(st ) ; if (++sample_no>9999) βample_no=0;

// show missing sample no's due to calibration _βettextposition(24,l); printf("Cal sta %ld done ",βta+l); } // end autocal //

// LCADV.C

// This procedure waits for a predetermined period of time for an

// individual flapper to close. At the beginning of the procedure the

// location of the bit signaling whether the flapper is closed or not

// is entered as well as how many seconds the maximum wait for the

// closure is to be. The code checks whether the flapper is closed and

// also calls another procedure to do some items that need to be done

// frequently during running, checks to see if the maximum time for

// that flapper is exceeded and if either the flapper is closed or the

// maximum time has exceeded the procedure returns to the calling

// program. It passes back a flag telling whether the flapper was

// indeed closed.

// int wait_closure(int fl)

( time_t inittime, ctime; byte fladd[4] - { 16, 16, 1, 2 }; // bit for flapper input byte flprt[4] - { 2, 4, 5, 2 }j

// port for flapper input int dt[4] - { 3, 4, 4, 6 };

// max. wait for flapper to close, seconds // should be at least as great as min wait byte fInclosed; int done; done-0 ; flnclosed-1; time(&inittime); do

{ time ( &ctime) ; f Inclosed - (byte ) (-(byte) i_get( flprt[ fl ] ) & fladd [ fl ] ) ; done=«do_f req( ) ; while ((ctimβ-inittime<dt[fl]) && (fInclosed) 6& (doneJ=>1 ) ) ; do

{ // wait a minimum of ?? seconds timo(&ctime) ; dono ^β do__froq();

} while ( (ctime-inittime<l) && (donel-1)); last_read[f1] .flok = flnclosed ; delay(100); // wait another 1.0 seconds after closure indicated delay(100); // wait return (done);

} // end wait closure

//

// LCADVl.C

// This piece of code is several different things that are to be done // relatively frequently during the running of the program. It reads // the clock, prints the current date and time at the top of the // screen, and checks for an entering of an "F" key at the keyboard. // It will respond to several different "F" keys. The most important // of which or the most common would be Fl which indicates that the // operator wishes to exit the data collection portion of the program. int do_freq(void) { int done=0; int ex; struct dosdate_t date; struct dostime_t clock;

_dos_getd te(&date) ;

_dos_gettime(£clock) ;

_settextposition(1 ,1 ) j printf("%2.2u/%2.2u ",date.month, date.day); printf("%2.2u:%2.2u«%2.2u",clock.hour, clock.minute, clock.second) ; chk_bc( ); if (kbhit()) cx= getch(); else cx=32; if (cx—0) // two byte key

{ cx= getch( ) ; if (ox*=59) done9=l; done=l; // Fl if (ex—60) lbn—; // F2 if (cx«62) { if (sba==0) sba«=l; else sba=0; // F4 showCalBa( ) ;

) if (cx«=63) autoeal(l); // F5 if (ex—64) autocal(2); // F6

) CompOK( ) ; return(done) ; ) //

// LCADVl.C

// This procedure does not do anything, void βample_cτ(int fl)

}

// LCADV.C

// This procedure is used to increment the count of a particular

// channel between bale press changes. The totals of observations and

// numbers of observations are kept of variables including Rd and +b

// so that they αan be averaged when the bale is finished and other

// data iβ kept on color code so that the mode can be calculated of

// the color because color codes can not be averaged.

// void inc_bt(int ch)

{ int i,~ccf, ccs;

void calc bafvoid)

( int T, j, k, ccpf, ccps/*, cc*/; int ctn; struct dostime_t dti e; double dt;

// delta time for rate calculation int dtp; // pointer to data for dt // calculate the means and mode values for disk storage

_dos_gettime(£dtime); // time of bale change

// save the old values for ba matrix for (j=39;j>0;j~) { ba[0][j] _* ba[0][j-l); ba[l][j) - ba[l)[j-l]; ba[2][j] - ba(2][j-l); ba[0][0).rd - 0.0; ba(0][0].pb = O.Oj ba[0][0].y = O.Oj

] ;

jj;

lee

balo_m_bn - 0 ; // chaged from bale_tot_bn ; not used now // balo numbers come from^""tho scalo lator RKB

[k] )

];

// get new entries for (i=0;i<3;i++)

{ bale_av__net[i] [0] = bale_m_nct[i] ; bale_av~no[i] [ 0 ] « bale_m_no[ i] ; bale_av_lcu r i ] 10 ] - bαle_m_lcu[i] ; bαle_αv__co [ i ] [ 0 ] = bαle_m_cc [ i ) ; bale~av] > ^ιrβaiⁱπ⁰] ^e baTe_m_pa[i] ; bαle_αv_mc[ i ] [ 0 ] - bαlβ_m_mc[i] ; ba[ij[0] .color « bale_m_cc[i] ; ba[i)[0]. reape - bale~m_pa.[i); ba[ij[0].mc - bale_m_mc[i]; ba[i] [0] .leaf = parea__to_clgr(bale_m_pa[i] ) ; ba[0][0].omσ - rSJ_dαt[10]; // Sam Jackson Big J mc ba[l][0].omc β rSJ_dat[ll]; // NIR mc ba[2][0].omo ■ rSJ~dat[12]; // microwave mc balo_av_lcu[3][0] - bale m_lcu[3]; bale_av[0].fce β bale m.fco ; bale_av[0].ftcd = bale~m.ftcd; bale__a [ 0 ] . fmc - bale_m. £mσ ; balo_av_bn[0] β 0; balo_av~wt[0] - 0;

menu30 i

( βettQXtposition(23,40);print ("Bale #...7 ");

Tf(bale_n >0) bx- bale_n; else bx- 0;

_βettextposition(23,46);ρrintf (" %71d ",balβ_n); menu40ι hx- gβtch(); // get α digit if(hx «KEY_ESC) return; // they changed thoir minds

if(hx —OxOd) goto menu60; // 'enter', they're thru if(hx =-0) goto menu30; // start over if(hx ==0x08) // backspace, delete the last digit bx- bx/10; // subtract it

_settextposition(23,46);printf(" %71d ",bx); goto menu40; hx= hx-48; // make it 0-9 if(hx <0) goto menυ50; // not a number if(hx >9) goto menu50; if( ((bx*10)+hx) >99999999)

{ printf("\07"); // bell goto menu30; bx- (bx*10) +hx; // add it in _settextposi ion(23,46); printf(" % 1d ",bx); goto menu40; menuSOt printf("\07"); // beep if(bx >0)

{ _settextposition(23,46);printf(" %71d ",bx);

} else ( _settextposition(23,46);printf(" %71d ",bale_n);

} goto menu40; menuβO i if (bx i-0 ) bale_n- bx; else bale_n= -1 ; sample_no= -1 ; } // end getbalen // // LCADVl .C

// This code logs data to the hard disk and to the LAN. It also opens

// the files under unique names based on the date and the files which

// have already been opened on that date.

// Most of the procedures determine if a file is

// available on the LAN as well as on the hard disk of the control

// computer, if they are, the data iβ written to both locations.

// LogDataF.C

#include "cainc.h" // all includes

#include "cadef.h" // all defines

#include "caext.h" //

#include "caproto.h" // prototypes of all functions

// LogDataF.C

// save the mean/mode data to the average data file

// void dsk_save_av( void )

{ struct dosdate_t date; struct do8time_t time; int i, n=0 ; double lcus=0.0, lcum; if(dsk_dat_flg >0)

{ ctdat2 = fopen(sumfilename, "at" ) ; if (ctdat2 1- NULL)

{

_dos_getdate(&date) ; _dos_gettime(&tune) ; fprintf(ctdat2,"M%2u %2u %2u", date.month, date.day, date.year); fprintf(ctdat2, "%2u %2u %2u", time.hour, time.minute, time.second) ; fprintf(σtdat2," %71d",bale_m_bn) ; for (i-0;i<3;i++)

{ fprintf ( ctdat2 , " %ld %4 . 1f %4 . 1f %2d %4 . 0f

%4.0f %4 .1f %4.1f" , i , bale_m_rd [ i ] , bale_m_pb[i] , bale_m_cc[i] , bale_m_a[i] , bale_m_c[i] , bale_m_pa[i ] , bale m_mσ[i] ) ;

> fo

if (n>0) lcum = lcus/n; else lcum=0.0; fprintf (ctdat2," %3.1f" ,lcum) ; for (i=0; i<3; i++) if ( (bale_m_nct[i]<9999) && (bale_m_no[i]<9999) ) fprintf(ctdat2 ," %4d%4d" ,bale_m_nct [i] ,bale_m_no[i] ) ; else fprintf(ctdat2," %4d%4d" ,9999,9999) ; fprintf(ctdat, "\n" ) ; fclose(ctdat2 ) ; // close file } // end — if (ctdat2 != NULL) } // end — dsk_dat_flg >0 } // end -- dsk save av

// ^"

// LogDataF.C

// save the raw data to the raw data file

// void dsk_save( void )

( struct dosdate_t date; struct dostime_t time;

FILE *ndt; int i, fct; long file_size; unsigned int iy; int iαpc, pv; if(dsk_dat_flg >0)

{ ctdat <= fopen(datfilename, "at" ) ; netdat ■ fopen(ndatfname, "at") ; for (fct-0;fct<2;fct++) // send data to two output files

{ if (fct==0) ndtβctdat; else ndt-nctdat; if ( ndt 1= NULL)

{ // record data for color/crash for (I-0 i<3;i++) // number of color/trash measure.

else fprintf(ndt, "N");

; ; ; ;

can't bo larger than 99 or βmaller than 0

fprintf(ndt, "\n"); } } } for (fct=0;fct<2;fct++)

{ if (fct—0) ndt=ctdat; else ndt=nctdat; if ( ndt 1- NULL)

{ for (i-0;i<3;i++) // 0, 1, 2 the CTM meter

{ fprintf(ndt, "20%2u%2u%2u" ,iy,date.month, date.day) ; fprintf(ndt, "%2u%2u%2u" ,time.hour, time. inute, time.second) ; fprintf(ndt, "%2u",4); // record the RB moisture data fprintf(ndt, "%lu",i); pv «= (int)(last_read[i].m*10.0+0.5); if (pv>999) pv-999;else if(pv<0)pv=0; fprintf(ndt,"%3d",pv); fprintf(ndt,"\n" ) ;

}

// 5 the SJ seed cotton sensor in the feed control

// 7 the microwave bale moisture

// 8 the SJ sensor behind the gin stand

II 9 the NIR meter behind the gin stand i=5;

( fprintf (ndt, "20%2u%2u*2u",iy,date.month, date.day) ; f rintf (ndt, "*2u%2u%2u" ,time.hour, time.minute, time.second) ; fprintf (ndt, "%2u%lu" ,4 ,i); // record the data pv - (int)(rSJ_dat[i]*10.0+0.5); // if (pv>999) pv-999; else if(pv<0) pv-0; fprintf(ndt, "%3d" ,pv) ; fprintf(ndt,"\n");

} i=7;

{ fprint (ndt, "20%2u%2u%2u",iy,date.month, date.day) ; fprintf (ndt,"%2u%2u 2u",time.hour, time.minute, time.second) ; fprintf (ndt,"%2u%lu", 4,i); // record the data pv = (int)(rSJ_dat[12]*10.0+0.5); // if (pv>999) pv-999; else if(pv<0) pv-0; fprintf (ndt, "%3d" ,pv) ; fprintf(ndt," \n");

} } for ( fet-0 ; fct<2 ; fct++)

{ if (fct==0) ndt=ctdat; else ndt-nctdαt; if ( ndt != NULL) { { fprintf(ndt,"20%2u%2u%2u",iy,date.month, date.day) ; fprintf(ndt, "%2u%2u%2u" ,time.hour, time. inute, time.second) ; fprintf(ndt, "%2u",4); // record the IR moisture data fprintf(ndt, "%lu" ,9) ; pv = (int)(rSJ_dat[ll)*10.0+0.5); if (pv>999) pv-999;else if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; fprintf(ndt,"\n"); } } } for (fct-0;fct<2;fct++)

{ if (fct==0) ndt=ctdat; else ndt=nctdat; if ( ndt I- NULL)

{ for ( i>=0;i<3 ;i++)

{ fprintf (ndt, "21%2u%2u%2u",iy,date.month, date.day) ; fprintf (ndt, "%2u%2u%2u",time,hour, time.minute, time.second) ; fprintf (ndt, "%2u%2u" ,5,i) ; // record the temperatures pv - (int)(rSJ_dat[i]+0.5); if (pv>999) pv-999;βlse if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; fprintf(ndt,"\n"); > } } if (nctdat 1= NULL) fclose(nctdαt) ; if ( ctdat 1- NULL)

{ file_βize » filelength(fileno(ctdαt)); fclose (ctdat); if(file size > max_file_βize) // check file size

{ open data_save_f ile (date, day, date, month, date , year) ; /* alT files reopened and closed*/

} } // end — if (ctdat i= NULL) } // end — if (dsk_dat_flag>0) end — dsk save

//

// — LogDataF.C

// save the cal tile data to the raw data file

// void dsk_save eal_tile( int eta )

{ struct dosdate_t date; struct dostime_t time;

FILE *ndt; int i, fσt; long file_si2e; unsigned int iy; int iapc, pv; if(dsk dat_flg >0)

{ ctdat = fopen(datfilename, "at") ; nctdat - fopen(ndatfname, "at") ; for (fct-0; fct<2 ; fct++) // send data to two output files

{ if (fct—0) ndt-ctdat; else ndt-nctdat;

e

}

//

// ___ _-»»—.. LogDataF.C — — —

// save press turn data to the raw data file

// void pt_dsk_save( void )

( struct dosdate__t date; struct dostime_t time; FILE *ndt; int fct; unsigned int iy; if(dsk_dat_flg >0)

{ ctdat = fopen(datfilename,"at"); nctdat - fopen(ndatfname, "at"); for (fct-0;fct<2;fct++)

{ if (fct—0) ndt-ctdat; else ndt=nctdat; if ( ndt 1- NULL) { _dos_getdate(&date) ; dos_gettime(£time) ; Xy - date.yeαr-1900; if (iy>100) iy—100; fprintf(ndt, "16%2u 2u%2u" , iy,date.month, date.day) ; fprintf (ndt,"%2u%2u%2u",time.hour, time. inute, time.second) ; fprintf (ndt, "%2u",6) ; // press turn code fprintf(ndt,"\n"); } } if (nctdat 1= NULL) fclose(nctdat) ; if ( ctdat !« NULL) fclose( ctdat); } // end — if (dsk_dat_flag>0) } // end — pt_dsk__save

//

// —_»_ „.. »_ LogDataF.C—

// save the bale moisture data to the raw data file // microwave meter void balm_dsk save( void ) ( struct dos5ate_t date; struct dostime_t time;

FILE *ndt> int imc , fct; unsigned int iy; if(dsk_dat fig >0)

{ ctdat - f open (dat filename , "at" ) ; nctdat - fopen ( ndat name, "at" ) ; doe gotdato ( &date ) ; dos gettime( &time) ; Iy -^"dato .yβar-1900 ; If (Ty>100 ) iy--100 ;

imc - (int) (bdat[lj.bm) ; if (imc<0) imc=0; if (imc>999) imc=999; for (fc -0;fct<2;fct++)

{ if (fct==0) ndt=ctdat; else ndt=nctdαt; if ( ndt 1= NULL)

{ fprintf(ndt,"19%2u%2u%2u",iy,date.month, date.day) ; fprintf(ndt, "%2u%2u%2u",time.hour, time. inute, time.second) ; fprintf(ndt, " 2u", 12); // bale scale data fprintf(ndt, "%3d",imc); // bale moisture content fprintf(ndt,"\n"); } } if (nctdat I- NULL) fclose(nctdat) ; if ( ctdat != NULL) fclose( ctdat); } // end — if (dsk_dat_flag>0) } // end — balm_dsk_save

//

// LogDataF.C

// log the tag_msg to the data file void tm dsk_save( void )

{ struct dosdαte_t date; struct dostime_t time; FILE *pdt; int i, k, imc; unsigned int iy; dos_getdate(&date) ; dos gettime(&time) ;

ate.day) ; nute, time.second) ; tag_msg

//

LogDataF.C data to the network file ss ( void )

izeof( bdat[0] ); for (k=0;k<2;k++) if (k—0) pdt - fopen("P:\\ginstand\\bdatf.dat","w+b" ) ; else pdt - fopen( "C:\\INIT\\bdatf.dat" , "w+b" ) ; if (pdt 1= NULL) rite(bdat,size,20,pdt); if (pdt 1- NULL) fclose(pdt);

> } // end — bdat_dsk_pass

//

// LogDataF.C

// pass the bale average data to the network file, and local file

// void ba_dsk_pass ( void )

{

FILE *pdt; int i, j, k; si2β_t size- sizeof( ba[0][0] ); for (k=0;k<2;k++) if (k—0) pdt - fopen( "PjWginstandWba.dat", -w+b"); else pdt = fopen( "C: \\INITWba.dat" , "w+b") ; if (pdt I- NULL)

{ for(i=0;i<20;i++) for (j-0;j<3; j++) fwrite(&ba[j][i],size,l,pdt);

> if (pdt !- NULL) fclose(pdt);

} // end — ba_dsk_pass

//

// LogDataF.C

// pass the other data to the network file, and local file

// void other_dβkj?ass ( void )

FILE *pdt; int i, k; int od[ 10 ] ;

for (k=0;k<2;k++) if (k—0) pdt = fopen("P:\\ginstand\\other.dat","w+b")j else pdt = fopen( "C: WlNITWother.dat" , "w+b" ) ; if (pdt J- NULL) fwrite(ccaltime,sizeof(ccaltime[0 ] ) ,3 , dt) ; fwrite(tcaltime,sizβof(tealtime[0] ),3,pdt) ; od[0] = rnlc; // rec. number lint cleaners od[l] = (int) (rscc/2) ; // rec. stick machine od[2] - (int) (rscc%2) ; // rec. impact cleaner od[3] - lcu(O); // no. lc's used gin 1 od[4] = lcu[l]; // no. lc's used gin 2 od[5] - lcu[2]; // no. lc's used gin 3 od[6] - scu[l]£0x01; // stick machine 1 used od[7) = (scu[l]&0x02)»l; // stick machine 2 used od[8] » 0} // od[9] - 0; fwrite(od,βizeof(od[0] ),8,pdt); od[0] - scu[0]£0x01; // impact cleaner 1 in use od[l] - (scu[0]&0x02)»l; // impact cleaner 2 in use for (i=0;i<3;i++) if (last_read[i].gsuse«0) od[2+i] - 0; // GS in else od[2+i] = 1; II GS not in

} od[5] = 0; fwrite(od,βizeof(od[0] ) ,5,pdt) ; fwrite(tag_msg,sizeof(char) ,60,pdt) ;

} if (pdt I- NULL) fclose(pdt); > } // end — other_dsk_pass

//

// LogDataF.C

// save the bale scale data to the raw data file

// void bs_dsk_save( long int bnp, int wtp ) struct dosdate_t date; struct dostime_t time; FILE *ndt; int fct; unsigned int iy; if(dsk_dat_flg >0) ctdat " fopen(datfilename, ^Hat" ) ; nctdat - fopen (ndatf name, "at" ) ; for ( fot-0;fct<2 ; fct++)

// //

/* DCFIO.C */

// save the calibration check tile data to the raw data file // autocalibration data void rec ctile( int ch )

( struct dosdate_t date; struct dostime_t ti«ne; unsigned int iy; int i,/* j,*/ pv, fct; FILE *ndt;

fprintf(ndt, "%2u%2u%2u",time.hour, time.minute, time.second) ; fprintf(ndt, "%2u",50); // Trash Auto Calibration fprintf(ndt, "%ld",i); pv - (int) (ctilβ[0][i).areapc*10.0+0.5); if (pv 999) pv=999;olse if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv = (int)(ctile[l][i].areapc*10.0+0.5); if (pv 999) pv=999;else if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv B (int)(fareaoff[i]+0.5); if (pv>999) pv-999;else if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv - (int)(fareaslp[i]*1000.0+0.5); if (pv>9999) pv=9999;elβe if(pv<0)pv=0; fprintf(ndt, "%4d",pv); switch (i)

{ case Oi pv = lut0[255); break; case 1* pv - lutl[255]; break; case 2 i pv - lut2[255]; break;} if (pv 999) pv=999;elee if(pv<0)pv=0; fprintf(ndt, "%3d",pv); fprintf(ndt,"\n");

} i=ch; // number of color autocalibrate

{ f rintf(ndt, "41%2u%2u%2u" ,iy,date.month, date.day) ; fprintf (ndt,"%2u%2u%2u",time,hour, time.minute, time.second) ; fprintf(ndt,"%2u",51); // Color Auto Calibration fprintf(ndt,"%ld",i); pv - (int)(ctile[0][i].rd*10.0+0.5); if (pv>999) pv=999;else if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv - (int)(ctilθ[0][i].pb*10.0+0.5); if (pv>999) pv-999;elβe if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv - (int)(ctile[l][i].rd*10.0+0.5); if (pv 999) pv=999;else if(pv<0)pv=0; fprint (ndt, "%3d" ,pv) ; pv - (int)(ctile[l][i].pb*10.0+0.5); if (pv 999) pv-999;elβe if(pv<0)pv=0; fprintf(ndt,"*3d",pv); pv - (int)(inty[i]+0.5); if (pv>999) pv-999;elβe if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv - (int)(slpy[i]*100.0+0.5); Jf (pv>999) pv-999»elβθ if(pv<0)pv=0; fprintf (ndt, "%3d" ,pv) ;

pv - (int)(intz[i)+0.5); if (pv>999) pv=999;else i (pv<0)pv=0; fprintf(ndt,"%3d",pv); pv - (int)(slpz[i]*100.0+0.5); if (pv>999) pv=999;else if(pv<0)pv=0; fprintf(ndt, "%3d",pv); fprintf(ndt,"\n"); } // end i= } // end ndt 1= NULL } // end ~ fct- if (nctdat l» NULL) fclose(nctdat) ; if ( ctdat 1- NULL) fclose( ctdat); } // end — if (dsk_dat_flag>0)

} // end — rec_ctile()

//

/* DCFIO.C */

// save trash calibration data to the raw data file

// void dsk_trβeal( int chd )

{ struct dosdate_t date; struct doβ ime_t time; unsigned int iy; int pv;

FILE *ndt; int fct; if(dsk_dat fig >0) { ctdat B fopen(datfilename,"at" ) ; nctdat B open(ndatfname, "at" ) ;

_dos_getdate(&date) ; dos_gettine( &time) ;

Iy - date.year-1900; if (iy>100) iy-=100; for ( fct-0; fct<2 » fct++)

{ if (fct==0) ndt=ctdat; else ndt=nctdat; if ( ndt 1= NULL)

{ , date.day); .minute, l Calibration

pv - (int) (cal_count); if (pv>999) pv=999;βlβe if(pv<0)pv=0; fprintf(ndt, "%3d" ,pv) ; pv = (int)(thresh*10000.0+0.5); if (pv>9999) pv=9999;else if(pv<0)pv=0; fprintf(ndt, "%4d",pv); fprintf(ndt,"\n"); } } if (nctdat 1= NULL) fclose(nctda ) ; if ( ctdat 1= NULL) fclose( ctdat); } // end — if (dsk_dat_flαg>0) } // end — dsk_trscal

II II

/* DCFIO.C

// save the color calibration data to the raw data file

// void dsk_colcal(int chd )

{ struct dosdate_t date; struct dostime_t time; unsigned int iy; int pv; FILE *ndt; int fct; if (dsk_dat fig >0)

{ ctdat = fopen(datfilename,"at") ; nctdat - fopen(ndat name, "at" ) ; _dos_getdate(&date) ; doβ_gettime(&time) ; Iy - date.year-1900; if (iy>100) iy-=100; or (fct-0; fct<2;fct++)

( if (fct«Bθ) ndt-ctdat_f-else ndt-nctdat; if ( ndt is NULL)

{ fprintf(ndt, "61%2u%2u%2u",iy,date.month, date.day) ; fprintf(ndt, "*2u%2u%2u",time.hour, time.minute, time.second) ; fprintf(ndt,"%2u",53)j // Color Manual Calibration fprintf(ndt, "%Id" ,chd) ; fprintf(ndt, "%7.If",y cal.el); fprintf(ndt, "%7.3f",y cal.c2); fprintf(ndt, "%7.3f",y cal.c3); fprintf(ndt,"%7. If",z^""cal.el); fprintf(ndt,"%7.3f",z~cal.c2) ;

fprintf(ndt, "%7.3f" , z eal.c3 ) ; pv - ccal_err; if (pv 99) pv-*99; else if (pv<0) pv=0; fprintf (ndt, "*2d",pv); // always prints 0 ?? fprintf(ndt, "\n");

}

} if (nctdat 1= NULL) fclose(nctdat) ; if ( ctdat 1= NULL) fclose( ctdat); } // end — if (dsk_dαt_flαg>0) } // end — dskjcolcal

// //

/* DCFIO.C */

// open the raw data and bale average data files void open_data_βave_file(int day, int month, int year)

//int chret; int nfle, i; int f handle /* , f_handle2*/; char fmsg(14) - "disk full !\0"; char cemβg[18] ="cannot open file\0"; char nmsg[18] - "no new file names\0"; fcloseall( ) ; // be sure all files are released fileday-(unsigned char)day; filemo -(unsigned char)month; fileyr = (unsigned int )year; datfilenαme[18] - (char) 48 ; // start name search at 0 ndatf ame[18] — (ch r) 48 ; sumfilename[18] = (char) 48 ; if (day>31) day - 31; if (day<0) day ' 0; datfilename[13] _*'(char) (day/10+48); ndatfname[13] *>(char)_(day/10+48); sumfilenαme[ 13 ] ^' «'(char) (day/10+48); day %= 10; datfilename[14] -(char) (day+48), ndatfname[14] -(char) (day+48); sumfilename[14] =(char) (day+48); if (month>12) month-12 if (month<0) month* 0; datfilename[15] =(char) (month/10+48); ndatfname[15) -(char) (month/10+48); βumfilenαme[15] -(char) (month/10+48); month %=10; datfilename[16) «(char) (month 48); ndαtfnαmo[16] -(char) (month 48);

sumfilename[16] =(ehar) (month + 48); if (year<0) year=0; year %= 10; /* 0..9 */ datfilenamβ[17] -(char) (year+48); ndatfname[17] -(char) (year+48); sumfilename[17] -(_Char) (year+48); settextposition(25,02) ; for (i-0;i<23;i++)printf("%c",dαtfilenαme[i]),- settextposition(25,30); for (i=0;i<23;i++) printf("%c" ,ndatfname[i] ) ; settextposition(25,57); for (i-0;i<23;i++) printf("%c" ,sumfilename[i] ) ;

// open raw data file on control computer nfle-0; do

{ if (access (datfilename, 0) 1=0)

{ nfle = 1; if ((f_handle - open(datfilename,

0_WRONLYI 0_TEXT| 0_CREAT) ) -= -1 )

_settextposition(25, 2) ;printf(cemsg, "0") ; /* give up */

) else /* - found it, new file open, give R/W attrib */ chmod(datfilename,S_I RITE | S_IREAD) ; else

{ close(f_handle) ; datfilename[18]++; if (datfilename[18]—58) datfilename[18]=(char) 65; sottoxtposition(25,02); ϊor (i-0,i<23ji++) printf("%c",datfilename[i]);

} while (nfle—0); setmode(f handle,0 TEXT); ctdat = fdopenff handle, "wt" ) ; // open raw data file on networked computer nfle=0; do { if (access (ndatfname, 0) 1=0) nfle - 1; if ((f_handle - open(ndatfname,

0 WRONLYlO EXTIO CREAT)) — -1)

{ ^"

_βottoxtposition ( 25 , 30 ) prin ( cemsg , " 0 " ) >

*/

// This section of code deals mostly with measurements of trash.

// TRASHF.C

#include "cainc.h" // all includes

#include "cadef.h" // all defines

#include "caext.h" //

#include "caproto.h" // prototypes of all functions

// TRASHF.C void do_trash(int ch)

{ delay(100); do_a rame(ch) ;

HRTlIve(HRTseg) ; ) // end do trash //

// TRASHF.C

// process a frame of data

// This section of code takes a reading from an individual frame of

// the channel being pointed to by the video multiplexer. It

// determines whether an individual pixel should be considered trash

// or not. It counts the number of pixels that are trash in the

// complete image and then converts that reading to the percent of the

// total number of pixels that are tr sh in the image.

// Because of the problem of the

// camera seeing the frame around the sample, this code does

// not include the at edges of the picture from the camera. It

// uses the autocalibration parameters.

// void do_a frame(int chan)

{ static int areaoff[3] - { 0, 0, 0}; // offset /10 in area measurement static int countoff[3] =( 0, 0, 0); // offset in area measurement int i;

ount;

)) *np_lut;

areaoff[chan] - (int) (fareaofffchan]+0.5) ; if (areaoff[chan]<0) areaoff[chan]»0; switch (chan) {

bu - bf[indx]; asm

MOV AX, [hiref] ; LOAD THE HIREF THRESHOLD... CMP AX,buff ; COMPARE DATA IN MEM. TO REF... JBE CENH_HI ; NOT A DARK SPOT, GO PAINT IT WHITE. MOV BX,np lut ; POINT TO THE START OF THE TABLE.. ADD BX, [hiref] ; INDEX TO THE RIGHT TABLE ENTRY... add bx, [hiref] MOV AX,[BX] ; GET THE ENTRY.. CMP AX, uff ; IS IT 'tresh'% ?.. JB CENH HI ; call it white ...

;xor al,αl

;mov buff_sav,al ; make it black MOV [wht_flg],01 mov ax,l add [raw_area] ,ax JMP SHORT CENH3 NEXT MEMORY POSITION

CENH-Hit

;mov al,bu±ι

; call it white

CENH2 I

AND AX,7FFFH

MOV [hiref],AX ; SAVE THE NEW REF... CENH2aι

CENH3 t

} // bottom of _asm

} // bottom of 'indx* — columns

{ by to hugo *baddr;

baddr= MAKE_FP(HRTseg) ; *(baddr + CNTL_REG)= 0x99;

} //

// TRASHF.C

// This procedure simply waits for a given amount of time

// void delay(unsigned int dlay)

{ static int cal_factor= 0; int i, j; do_freq( ) ; if( lcal_factor)

{ char far *t- (char far *) 0x0000046CL;

// timer tick address j- *t; while(j —*t); j= *t; while(j —*t)

{

CompOK( ) ; cal_factor++; for(i-0; K100 ; i++) ;

} cal_factor- cal_factor/55;

} while(dlay—)

{ for( j-0 ; <cαl_factor; j++)

} /

//

TRASHF.C

// void setup_trash ( int ch ) if (ch— 0 ) thresh- threshO ; // for calibration Ti if (ch— 1 ) thresh* throshl ; // trash first . . .

} if (ch==2) thresh- thresh2; // trash first...

}

} //

// TRASHF.C

// This procedure takes the mean of several readings of Rd, +b, or // percent area and stores it in a matrix. Used to check the correct // readings of the autocalibration tiles.

// void cale_ctmean(int sta) // calc means

{ ctm[0][sta] .rd - (ctile[0][βta].rd+ctile[2][sta].rd+ctile[4][sta].rd)/3.0; ctm[l ] [sta] .rd - ₍ctile[l][sta_].rd+ctile[3_][sta].rd+ctile[5][sta].rd)/3.0; ctm[0] [sta] .pb ^s

(ctile[0][βta].pb+ctile[2][βta).pb+ctile[4][sta].pb)/3.0; ctm[l] [sta] .pb B (ctile[l][βta].pb+ctile[3)[sta].pb+ctile[5][sta].pb)/3.0; ctm[0][stα] .y -

(ctilβ[0][stα].y +ctile[2] [sta] .y +ctile[4] [sta] .y )/3.0; ctm[l] [eta] .y =

(ctile[l][βta].y +ctile[3] [sta] .y +ctile[5] [sta] .y )/3.0; ctm[0] [sta] .z -

(etile[0][sta].z +ctile[2] [sta] .z +ctile[ ) [sta] .z )/3.0; ctm[l) [sta] .z -

(ctile[l][sta].z +ctile[3] [sta] .z +ctile[5] [sta] .z )/3.0; ctm[0) [sta] .areape =

(ctile[0] [sta] .areape +ctile[2] [sta] ,areapc+ctile[4 ] [sta] . reape) /3.0; ctm[l] [sta] .areape -

(ctile[l][8ta].areapc +ctile[3][sta] .areape+ctile[5] [sta] .areape) /3.0; ) // end calc ct ean //

// TRASHF.C

// This is the software calculates the

// adjustments to the Y,Z, and percent area readings based on the

// calibration tiles that are presented automatically at stations two

// and three. The procedure is a linear fit for Y, α linear fit for Z,

// but it'β a nonlinear approach for the percent area.

// void cαlc ctile adj (int camera) // adjust for tiles

{ int i;~ double ex, sy, βxy, sxs , don; double yc[3 ] (2 ) ; double zσ[3 ] [2 ] ; doublo cal_chk_aroapσ[ 3 ] - {2.04 , 1.76, 2.05} ;

double fslpy, fslpz, finty, fintz, ffareaoff, ffareaslp;

// yc[station] [tile] tile=0->trash, tile=l->color yc[0][0]=1305.0; yc[0][lj- 947.0; yc[l][0]-1305.0; // trash yc[lj[l]= 947.0; // color yc[2][0]=1418.0; yc[2][l)-1025.0;

// trash // color

βx-0.0; sy-0.0; βxy-0.0; sxs=0.0; for (i=0;i<6;i++)

{ sx +«ctile[i] [camera] .y; sy +-yc[camera] [i%2]; sxy+=ctile[i] [camera] .y*yc[camera] [i%2 ] ; sxs+=ctile[i_{] [}camer _] „y*ctile_[i_] [camera] .y;

) _settextposition(10+camera,5) ; printfC'cam %2d sx %6.2f sy %6.2f sxy %6.2f sxs %6.2f " ,camera, sx,sy,βxy,sxs) ; den = sxs - sx*sx/6.0; if (den>0.01) fslpy - (sxy - βx*βy/6.0)/den; else slpy[camera) = 1.0; finty - sy/6.0 - slpy[camera]*sx/6.0;

.z ;

f ntz - βy 6.0 - slpz[camera]*sx . ;

// correct for offset, based on color tile ffareaoff +B (ctilβ[ 1] [camera] .areapc-0.1

+ctile[3] [camera] .areape-0.1

+ctile[ 5) [cameraJ .arβapc-0.1)*2.0; // was 10.0 if (ffareαoff<0.0) ffareαoff-0.0;

// correct for slope based on trash tile ffareaslp += (cal_chk_areapc[camera]*3.0 -ctile[ 0] [camera] .areape -ctile[2 ] [camera] .areape -ctile[4 ) [camera] .areape) *0.01 ; // 0.05 works // 0.01 works

_settextposition(2 ,2 ) ; printfC* %2d %6.3 %6.4 %6.3 %6.4 %6.4 %6.4 ", camera, finty, fslpy, fintz, fslpz, ffareaoff, ffareaslp); switch(camera)

{ case 0> for (i-0;i<256;i++) lut0[i) = (int)(i*thresh0*fareaslp[0]+0.5); break; case 1: for (i=0;i<256;i++) lutl[i) - (int)(i*threshl*fareaslp[l]+0.5); break; case 2 i for (i-0;i<256;i++) lut2[i) - (int)(i*thresh2*fαreαslp[2)+0.5); break; default! break; }

} // end calo ctile adj // ^~

// TRASHF.C

// This procedure is the calibration of the trash reading based on a

// properly presented trash tile. his procedure calls "trash_^calOOO,

// trash_eall00, for trash_cal200," depending on whether calibration

// is at station one, two or three. These procedures determine a

// new threshold which determines what the new lookup table will be

// for whether a pixel is considered trash or not based on successive

// approximations. The threshold is stored in a file on the hard disk

// after the calibration is complete.

// int trsh_cal(int ch)

FILE *tcal; // trash calibration int ex, hx, ix, i; int iarea, icount; float farea, fdif , rx, pacal; float chg coeff-(float)0.00008; time__t ltime ; cal l σloarβσrβen(_GCLEARSCREEN) ; faroaoff (ch) = o . O ;

fαreaslp[ch] •= 1.0; settextpcsition(12,31);printf( "TRASH CALIBRATION"); If(tcret ==0) { _settextposition(13,31) ;printf("CAMERA #1") ;} else if (tcretj—1) { settextposition(13, 31) ;printf( "CAMERA #2" ) else { _βettextpositϊon(13,31);printf("CAMERA #3");} _settextposition(15,34 ) ;printf( "TILE VALUES" ) ;

_Bettextposition(16,29) ; printf(" " ) ; pαcαl - cαl_αreα; // needs to be float pacal B pacal*pacal/205040.0;

_settextposition(17,29) ; printf(" Area Count");

_βettextposition(19,29) ; printf(" %4d %3d", cal_area,cal__count) ; _settextposition(22,29) ; printf(" Percent area«%6.2f ",pacal); _βettextpoβition(05,14); printf("Fit F5» ESCJ")

_settextposition(06, 14); printf( "Change Tile Values Calibrate Quit" ) ; cal90: cx= getch(); if(ex —0) cx= getch(); if(ex —59) goto callOO; if(ex =-KEY_ESC) return(ll); if(ex ==63 )~^" goto re__cal;

printf("\07"); // bell goto cal90; callOOt // get a new area value

goto cαlllO; call20: printf("\07"); // beep if(ix >0)

{ _settextposition(20,29);printf(" %d ", ix); } else

{ _settextposition(20,29);printf{" %d ", cal_area); } goto call10; cal200ι // get a new count value if(ix 1-0) cal_area= ix; // save 'cal_area' first... goto cal; // added

_settextposition(20,29);printf( "Area Count" ) ;

_βettextposition( 19,29) ;printf{" Count");

_settextposition(19,29);printf("%d %d" , cal_area, cal_count) ; _settextposition( 19 ,47 ) ;printf( "Count" ) ;

cal202ι

_settextposition(20,29) ;print (" td ", cal count); ix- 0; ca!210x

if(ix 1=0) cal_count= ix; _settextposition(17,47) ;printf( "Count ); _settextposition(15,49);printf(" %d " cal_count) ; goto cal; re_calt

_clearscreen( GCLEARSCREEN) ; _settextposit!on( 4,31) ;printf("TRASH CALIBRATION' ^"settextpoβition( 7,3 ) print ( "TILE VALUES"); _aettextposition( 8,29) ; rintf( ) _settextposition( 9,29) ;print ( Area Count" ) ; _settextposition(ll,29) ;printf( %4d %d ", cal_area,cal_count) _settextpoβition(16,35) ;printf( SCAN RESULTS"); _settextposition(17, 8);printf( _setteκtposition(18,28) ;printf( Area Count Threshold¹ _settextposition(22,29) ;printf( CALIBRATION STARTING"); _settextposition(23,29) printf( (Esc to quit)");

re_call0ι

rea tion area ange

iarea. icount, thresh);

_settextposition(22,29);printf( "CALIBRATION CONTINUING..."); _settextposition(23, 29);printf(" (Esc to quit)");

iarea, icount, thresh); _sβttextposition(22, 29) ;printf("CALIBRATION COMPLETE... " ) ; _settextposition(23,29);printf(" (Esc to quit)"); delay(3000); // wait a while

if( kbhit() ) // see if they want to quit

{ cx= getch( ) ; if(ex ==KEY ESC) return(ll);

} if( (teals fopen("c:\\init\\TRSHCAL.DAT", "wb")) --NULL ) // guess not, βave 'em

{ printf ("\n open error, TRSHCAL.DAT"); return(10) ;

} else

{ fprintf(tcαl,"%d\t d\t%f\n", cal_αreα,cal_count,thresh) ; fclose(teal) ;

} dsk_trscal( ch ); if(tcret =»0) // see where we came from return(O); // finish up camera #1 else return(0) ; // camera #2 } // end trsh cal // // TRASHF.C

// void traβh_cal000(void) // camera #0 trash int i, ix; float rx;

FILE *tcal; // trash calibration flappor(l) ; // open sampler at 0, close 1, 2

outp(DT2859,0) ; // switch to video input 0

// changed for plunger sampler at 0 flapper(l); // oppn sampler at 0, close 1, 2 out (DT2859,1) ; // change to video input 1 if( (teal- fopen("ct\\init\\trshcall.dat","rb")) —NULL )

_βettextposition(16,55); printf("open error, trshcall.dat"); trcret-12; fscanf (teal, "%d\t%d\t%f\n" , &cal_αrea,&cal_count,& thresh) ; foloso(tcal) ; for(i-O) i<256> I++) // look-up table

it\\trshcall.dat>nul") ;

// TRASHF.C

// void trash_cal200(void) // camera #2 trash

{ int i, ix; float rx;

FILE *tcal; // trash calibration

// changed for plunger sampler at 0 flapper(l); // open sampler at 0, close 1, 2 outp(DT2859,2) ; // change to video input 2

) ;

tcret- 2; trcret = trβh_cal(2); if (trcret<10) ix- syβtem("copy ctWinitWtrshcal.dat oi \\lnitWtrshcal2.dat>nul") J // in case thoy didn't } // end trash cal200 //

// TRASHF.C

// This procedure reads the trash calibration data from the hard dis_k

// and calculates the lookup table for the three trash heads, station

// one, two, and three

// int reαd_tcαl(void)

{ int i; float rx;

FILE *tcal; // trash calibration if( (tcal= fopen("c:\\init\\trshcal0.dat","rb") ) —NULL )

// camera #0

{

_βettextposition(13,55); printf("open error, trshcal0.dat"); return(10) ; } else

( fscanf(tcal,"%d\t%d\t%f\n", Sea _area0,&cal_count0 , &threshO ) ; fclose(teal) ;

} for(i-0; i<256; i++)

{ rx» (i*thresh0) +0.5; // round up lut0[i]= (int)rx;

} if( (teal- fopen("ct\\initWtrshcall.dat","rb") ) —NULL ) // camera #1

{

_settextposition(14,55) ; printf("open error, trshcall.dat"); retur (10) ;

} else

{ fscanf(tcal,"%d\t%d\t%f\n",

£cal_areal , ϋcal_count 1 , & thresh 1 ) ; fclose (teal) ; > for(i=0; i<256; i++) rx- (i*threshl) +0.5; // round up lutl[i]- (int)rx; } if( ftcal- fopen("ct\\init\\trshcal2.dat","rb")) ==NULL ) // camera #2 {

_sextextposition( 14 , 55 ) ; print ("open error, trshcal2.dat"); return(10) ; else fscanf(tcal,"%d\t%d\t%f\n",

&cal_area2 ,&cal_count2 ,&thresh2 ) ; fclose(tcal) ; for( -0; i<256; i++) rx= (i*threβh2) +0.5; // round up lut2[i]^« (int)rx; return(O) ;

} // end read teal

//

// TRASHF.C

// This file contains many of the "defines" used in the program. They // are addresses and unchanging variable values that can be used in // the file.

// cadef.h

//

// from ColorF.c

#define ADBase 0x300

#define ADStat ADBase+8

#define DT2859 0x2E3

#define KEY_ESC 27

#define byte unsigned char

#define PASS 1

^define FAIL 0

#define OK 1

// end from ColorF.c

// from trashF.C

#define Y_REG 0x2002

#define CNTL_REG 0x2000

#define lfl -0.01785

#define lf2 0.00815

#define If3 0.0915

#define If4 0.000003575

#define If5 0.000367

// end from trashF.C

// cadef.h

// This file contains declarations for all the global variables that // are used int he program. This program uses a lot of global // variables for passing data from one procedure to the other.

//

// caext.h

//

// A/D vars

#ifdef MAIN_SECTION

// Frame grabber is memory mapped unsigned HRTseg=0xD800; #else extern unsigned HRTβeg ;

#endif //

// Color vars —— — — —— ——

#ifdef MAIN_SECTION int Y CHANL[3] = {0,4,8};

/7 in ut, Z_CHANNEL[nJ=Y_CHANNEL[n]+l

#ifdθf MAIN SECTION #define EXTERN

#else

#deflne EXTERN extern

#ondif II calibration tile check data

EXTERN double fareaoff[3];

EXTERN double fareaslp[3J;

EXTERN double slpy[3], slpz[3], inty[3]. intz [ 3 ] ;

II storage for last manual calibration time

EXTERN time_t ccaltime[3], tcaltime[3], e time[3];

EXTERN struct RB ctdat ctile[6][3); // thiree readings of each

// of the 2 tiles per each of 3 C/T heads ctile[read] [sta]

EXTERN struct RB_ctdat ctm[2 ] [3 ] ; // mean of tvo tiles, three stations

// ctm[tile] [sta]

II

EXTERN float ccf[3][6]; // color conversioi: constants

EXTERN int color_step;

EXTERN float plus_b, rd;

EXTERN struct color_const y_cal;

EXTERN struct color_const z_cal;

EXTERN int coir, pima_flg;

EXTERN int ccal_err; // count of errors in color mαnυαl cal ,

// Trash vars

EXTERN float chg_coeff;

EXTERN double area;

EXTERN double count;

EXTERN double leaf;

EXTERN int lut0[256], lutl[256), lut2[256], lut[256];

EXTERN int *p_lut; // to point to the current lut EXTERN float thresh; EXTERN float threshO; EXTERN float threshl ; EXTERN float thresh2 ; EXTERN int cal_area; EXTERN int cal_area0 ; EXTERN int cal_areal; EXTERN int cal_area2 ; EXTERN int cal__count; EXTERN int cal~countl ; EXTERN int cal_count2; EXTERN int treret; EXTERN int tcret;

//

// Color and Trash vars

EXTERN int camera ;

EXTERN unsigned HRTseg;

EXTERN struct RB_data last_read[ 3 ] ;

// Overall variables struct RBbaledat { long bn; int bw; long btime; int bm; } ;

for last 40 bales

EXTERN struct RBbadat ba[3][40]; // bale average rd, pb, y, z, areape, leaf, color, mc

EXTERN int bale_tot_ct_n[3] , // number of obs. added for color/trash means bale_tot_o_n[3] , // number of times in sum sub. bale_tot_ct_nra[3] , // number of good obs. of moisture bale_av_nct[3 ] [ 10] , bale_ay_no[3 J [ 10] , bale_m_nct[3 j , bale_av_wt[10] , // the bale weight from scale bale_m__no[3] ;

EXTERN double bale_tot_rd[3] ,

leu of gin 0..3, sum., number of obs

EXTERN double bale_αv_time[10] ;

EXTERN float bdat rate[40];

EXTERN int lbn; ~~ // the last bale number received

EXTERN

EXTERN struct RB_fldat bale_tot, // total number of obs of indices used bale_av[10], // .fee, .ftcd, . fmc bale_m;

EXTERN int bale tot_cc[9) [6] [3 ] ;

EXTERN int bale~av_cσ[3][10);

EXTERN int bale m_co[3);

EXTERN int lcu[4~]; // current LC in use, 4 gin stands 0..3

EXTERN int scu[2); // current SCC in use, 2 machines

// 0 = none; 1, 2 = one; 3 = two EXTERN int cnlcl; // current number of gin stands with setting 1 EXTERN int cnlc2 ; // current number of gin stands with setting 2

EXTERN float bvolt[6]; // to hold voltage going to the bulbs EXTERN int sba; // show bale averages, or self calibration data EXTERN FILE *lc_decision_file; EXTERN FILE *scc_decision_file; struct dec matrix_entry { char fIret_atage_machine_sequence; char dryer_sequence; unsigned int predicted_moist_station_2; unsigned char predicted_trash_station_2 ; unsigned char predicted_color_βtation_2 ; char sec_stage_machine_sequence; unsigned int predicted_moist station_3; unsigned char predicted_trash^*_βtation_3; unsigned char predicted color station_3;

};

EXTERN byte huge lc_dec_rkb[31][21 ] [13] [13] ;

// [Rd][+B][%M][leaf] EXTERN byte huge scc_dec_rkb[31] [21] [13] [13] ;

// [Rd][+b^')[%M][leaf]

EXTERN struct dβo_matrix_entry current_decision[ 2 ];

EXTERN struct moist_color_trash_entry predicted_data[ 2 ] ; EXTERN struct moist_color_trash_entry lu_d[2];

EXTERN int rnlc; // recommended number of lint cleaners EXTERN int rscc; // recommended number of seed cotton cleaners EXTERN float p stl; // recommended gin stand moisture content EXTERN int flok[3); // flapper has timed out EXTERN int done9; // Fl pressed EXTERN long bale n; EXTERN int βampTe_no; EXTERN int error; EXTERN int us3 ; // switch to use station 3 EXTERN long max_file size; EXTERN unsigned char flleday; EXTERN unsigned char filemo; EXTERN unsigned int fileyr; EXTERN int dsk dat_flg; // =0 not log data, =1 log data EXTERN FILE *ct3at; // file to hold all data EXTERN FILE *nctdat; // network file to hold all data EXTERN FILE *ctdat2; // file for summary data EXTERN struct RB_fldat 1 read_data[3) ;

EXTERN int SJ_dat[15J; // data from temperature and other moisture devices EXTERN double rSJ_dat(15]; EXTERN char tag_msg[65]; // tag label from net

#ifdef MAIN_SECTION

/* prototype name for the all data file, change code if it is changed*/ char datfilename[25) = "C: \\DATA002WSVOOOOOO.DAT\0\0" ;

/* prototype name for the network data file, change code if it is changed*/ char ndatfname[25] = "Pt\\DATA002WSV000000.DAT\0\0";

/* prototype name for the summary data file, change code if changed*/ char sumfilename[25] = "C: \\BGlDATA\\SM000O00.DAT\O\0" ;

extern char datfilename[25] extern char ndatfname[25] extern char sumfilename[25] #endif // caext.h

// This file has many of the external "includes" in it. The three

// files "vicdefs.h, vicfcts.h, and vicerror.h" are part of the Victor

// Software Library that came with the frame grabber card. The three

// files, "hviconst.h, hvimain.h, and driver.h" are part of the MCI

// package that came with the color and trash measurement cameras.

// The rest of the files are all part of the basic Microsoft "C

II package. These are all files that contain drivers and software for

// doing many of the things that have to do with hardware in the

// system including the operating system.

//

// cainc.h

#include <time.h>

#include <sys\types ,h>

// from color .c

#include "vicdefs .h"

#include "vicfcts.h"

#include "vicerror.h"

#include "hviconst.h"

#include "hvimain.h"

#include <stdlib.h>

#include <stdio.h>

#include <math.h>

#include <time.h>

#include <process.h>

#include <dos.h>

#include <io.h>

#includo <SYS\TYPES.H>

#include <SYS\STAT.H>

#include <ERRNO.H>

#include <FCNTL.H>

#include <conio.h>

#inclu-lβ <graph.h>

#inelude <strlng.h>

#include <direct.h>

#include "driver.h"

// end from colorf.c

//

// cainc.h

// This file contains the seven "include" files that have the

// declaration of the types for each of the procedures. They are

// located in separate files that correspond to the source code files

// that contain the "C" source code.

// caproto . h

/include "ColorPrt.h" /include "TrashPrt.h" /include "DgtIIPrt.h" /include "DispLPrt.h" /include ^••ContDPrt.h" /include "LogDaPrt.h" /include "LcadvPrt.h" // caproto . h

// These are the declarations of the procedures that are in the

// "eolor .C" program. They mostly have to do with color measurement

// and color calibration but also include declarations of all the

// analog data collection that's used in the system.

//

// - ColorPrt.h

// void runcolor( oid) ; int colrmgr(int) ; void mcmgr(int) ; void delay(unβigned int); int system(const char*); void _dos_gβtdate(struct dosdate_t*) ; void _dos_gettime(struct dostimβ_t*) ; int compύte_color(float, float) ; void color_cal(int) ; void color_init (void) ; void adc_value(int, int, int*); // don't use for rd or +b void adc_mns(int, int* , int*) ;

// mean of 8 readings 2 consec. chan. void showed (int ) ; void showadp(int) ; void setup_vid ( int ) ; void get_bvolt( void ) ; void get_mc ( void ) ; void get_sjm( void ) ;

//

// - ColorPrt.h

// These are declarations of procedures used in the control process in

// the control computer.

//

// ContdPrt.h

// int open_decision_matrix_file( void ); void initialize_dec_matrix( void ); int read_lc_dec_file( void ) ; int read_βcc_dec_file( void ) ; int index_to_color( int ); int color_to__index( int ); int moiβt_to^"index( float ); int trash_to_index( float ); int round_color( float ); int round_trash( float ); void RKB_measurement_proceBs( int ); int color_function ( int ) ; int traβh_function( int, int ); int rule_of_thumb( int, double ); int fix_color_index( int ); int parea_to_clgr( double ); int lc_lookup ( int, double, double, double); int scc_lookup( int, double, double, double); int lc_check( int, double) ;

// ContdPrt.h

// This file contains declarations of all the procedures used for

// digital input and output having to do with opening and closing

// flappers for sample collection as well as the bitwise data transfer

// between the PLC and the control computer signaling how many lint

// cleaners should be used, how many are being used, and the like.

// - DgtliPrt.h

// void o_set ( byte, byte); byte i_get ( byte ) void CompOK ( void ) void flapper ( int ) void chk_lcu ( void ) void chk_bc ( void ) void calflap ( int ) int wait_samp_open ( int ) ; int wait~cal_closed ( int ) ; int wait_cal_open ( int ) ; void PLC_lc ( int ) ; void PLC_scc ( int ) ; void chk_tagmsg( void ) ; void kp_f_read( void ) ;

// DgtliPrt.h

// This file has declarations of procedures used to display data on // the screen in the gin which is the computer that is being used for // control .

//

// DisplPrt.h

// void βhowCT ( int ) ; void print_display_headings ( void ) ; void display_error ( char error_message[ ] ) ; void display_message ( char message [ ] ) ; void showBA ( void ) ; void showCalBa ( void ) ;

//

// DisplPrt.h

II

II -HVICONST.H-

If

#define ON 1 #define OFF 0 struct color_const

( float cl; float c2; float c3;

); struct cal_const

{ float slope; float offset;

}; struct RB data

{ int flok; // flapper error codes int cok; // color in reasonable range int tok; // trash in reasonable range int mok; // moisture in reasonable range long ctsn; float m; // moisture reading float y; // color y float z; // color z float rd; // color Rd float pb; // color +b int cc; // color code int cq; // color quad. float area; // trash area - raw float count; // trash count float leaf; // trash leaf code float areape; // percent area of trash int empg; int gsuse; // code for which gin stands are running int llight; // reading of intensity of one light int rlight; // reading of intensity of other light

};

struct moiβt_color_trash_entry

{ int moist; int color; int trash;

};

//

// HVICONST.H

// This file is a declaration of procedures used in the main program.

// These procedures mostly have to do with getting the program started

// and doing the basic control of data collection. It also has

// procedures having to do with calculating means and nodes of the

// data that has been collected and running autocalibration.

// - IcadvPrt.h

// void getbalen ( void void setup ( void void openmenu ( void void getdata ( void void getdata2 ( void int wait_closure (int ) ; void εample_CT ( int void runscreen ( void void getdata ( void void inc_bt ( int void calo ba ( void void inc_En ( int void dec_bn ( int void autocal ( int int do_freq ( void

// IcadvPrt.h

// These procedures have to do with

// logging data to either the hard disk on the computer thats being

// used to control or on a network so that the data is available on a

// separate computer in the office of the gin. // // LogDaPrt.h void open_data_save_file ( int, int, int) ; void dsk_save ( void ) ; void dsk_colcal ( int ) ; void dsk_#_trscal ( int ) ; void dsk~βave_av ( void ) ; void dsk_βave_cal_tile( int ) ; void rec_ctile int ) ; void bs_dsk_save long int. int ) ; void balm_dsk_save ( void ) ; void tm_dsk_βave ( void ) ; void bdat_dsk_pass ( void ) ; void ba_dsk pass ( void ) ; void other dsk_pass ( void ) ; void pt_dsl _βave ( void ) ;

// // — LogDaPrt . h

// This file contains declarations of procedures in "trashf.c" and are

// related to the frame grabber and trash measurements.

//

// TrashPrt.h

// void setup_trash(int) ; int β tart_f g ( void ) ; void f reeze_f rame ( void ) ; void do a_f rame { int ) ; void delay (unsigned int) ; int system (const char*) ; void _dos_getdate (struct dosdate_t* ) ; void _dos_gβttime(βtruct dostime_t*) ; int trsh_cal (int) ; void trash_cal000(vold) ; void trash_cαll00(void) ; void trash_cal200(voJ d) ; int read__tcal(void) ; void do trash (int) ; void caTc_ctile_ad j (int) ; void calc_ctmean( int ) ;

//

// - TrashPrt.h

GREENCCCDAT

51-7 -1235 -1235 -1235 -1235 -1085 -1085 -1085 -1085 -1085 61-2 -1215 -1215 -1215 -1215 -1065 -1065 -1065 -1065 -1065 61-3 -1215 -1215 -1215 -1215 -1065 -1065 -1065 -1065 -1065 61-4 -1215 -1215 -1215 -1215 -1065 -1065 -1065 -1065 -1065 61-5 -1230 -1230 -1230 -1230 -1080 -1080 -1080 -1080 -1080 61-6 -1230 -1230 -1230 -1230 -1080 -1080 -1080 -1080 -1080 61-7 -1505 -1505 -1480 -1480 -1330 -1330 -1330 -1330 -1330 71-2 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 71-3 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 71-4 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 71-5 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 71-6 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 71-7 -1515 -1515 -1500 -1500 -1350 -1350 -1350 -1350 -1350 12-2 -530 -530 -375 -280 -130 0 0 0 0 2-3 -535 -535 -380 -290 -140 -10 -10 -10 -10

12-7 -1355 -1355 -1355 -1350 -1200 - 2 - - -

22-2 -530 -530 -375 -280 -130 0 0 0 0

22-3 -535 -535 -380 -290 -140 -10 -10 -10 -10

22-4 -600 -600 -445 -350 -200 -75 -75 -75 -75 GREENCCCDAT

22-5 -695 -695 -560 -530 -380 -290 -290 -290 -290 22-6 -970 -970 -895 -895 -745 -745 -745 -745 -745 22-7 -1355 -1355 -1355 -1350 -1200 -1200 -1200 -1200 -1200

42-7 -1355 -1355 -1355 -1355 -1205 -1205 -1205 -1205 -1205

52-2 -755 -755 -595 -595 -445 -430 -430 -430 -430

52-3 -760 -760 -600 -600 -450 -440 -440 -440 -440

52-4 -945 -945 -880 -880 -730 -730 -730 -730 -730

52-5 -960 -960 -885 -885 -735 -735 -735 -735 -735

52-6 -1365 -1365 -1365 -1365 -1215 -1215 -1215 -1215 -1215

52-7 -1370 -1370 -1370 -1370 -1220 -1220 -1220 -1220 -1220

62-2 -1330 -1330 -1310 -1310 -1160 -1160 -1160 -1160 -1160

62-3 -1330 -1330 -1310 -1310 -1160 -1160 -1160 -1160 -1160

62-4 -1330 -1330 -1310 -1310 -1160 -1160 -1160 -1160 -1160

62-5 -1380 -1380 -1380 -1380 -1230 -1230 -1230 -1230 -1230

62-6 -1380 -1380 -1380 -1380 -1230 -1230 -1230 -1230 -1230

13-2 -850 -850 -740 -710 -560 -560 -560 -560 -560

13-3 -930 -930 -820 -820 -670 -670 -670 -670 -670

13-4 _94o -940 -830 -830 -680 -680 -680 -680 -680

13-5 -1185 -1185 -1150 -1135 -985 -985 -985 -985 -985

13-6 -1420 -1420 -1410 -1410 -1260 -1260..-1260 -1260 -1260

13-7 -1625 -1625 -1595 -1595 -1445 -1445 -1445 -1445 -1445

23-2 -850 -850 -740 -710 -560 -560 -560 -560 -560

23-3 -930 -930 -820 -820 -670 -670 -670 -670 -670

23-4 -940 -940 -830 -830 -680 -680 -680 -680 -680

23-5 -1185 -1185 -1150 -1135 -985 -985 -985 -985 -985

23-6 -1420 -1420 -1410 -1410 -1260 -1260 -1260 -1260 -1260

23-7 -1625 -1625 -1595 -1595 -1445 -1445 -1445 -1445 -1445

33-2 -930 -930 -820 -820 -670 -670 -670 -670 -670

33-3 -930 -930 -820 -820 -670 -670 -670 -670 -670

33-4 -1175 -1175 -1135 -1130 -980 -980 -980 -980 -980

33-5 -1185 -1185 -1150 -1135 -985 -985 -985 -985 -985

33-6 -1420 -1420 -1410 -1410 -1260 -1260 -1260 -1260 -1260

33-7 -1625 -1625 -1595 -1595 -1445 -1445 -1445 -1445 -1445

43-2 -940 -940 -905 -905 -755 -755 -755 -755 -755

43-3 -1190 -1190 -1190 -1190 -1040 -1040 -1040 -1040 -1040

43-4 -1190 -1190 -1190 -1190 -1040 -1040 -1040 -1040 -1040

43-5 -1455 -1455 -1455 -1455 -1305 -1305 -1305 -1305 -1305

43-6 -1460 -1460 -1460 -1460 -1310 -1310 -1310 -1310 -1310

43-7 -1630 -1630 -1620 -1620 -1470 -1470 -1470 -1470 -1470

53-2 -1210 -1210 -1210 -1210 -1060 -1060 -1060 -1060 -1060 GREENCCCDAT

UPLNDCOL.DAT

40040812

40041812

40042812

40043812

40044812

40045812

40046812

40047812

40048812

40049812

40050812

40051812

40052812

40053812

40054812

40055812

40056812

40057812

40058812

40059812

40060812

40061812

40062812

40063812

40064812

40065812

40066812

40067812

40068812

40069812

40070812

40071812

40072812

40073812

40074812

40075812

40076812

40077812

40078812

40079812

40080812

40081812

40082833

40083833

40084833

40085833

40086833

40087833

40088833 40089833

40090833

40091833

40092833

40093833

40094833

40095833

40096833

40097833

40098833

40099833

40100833

40101833

40102833

40103833

40104833

40105833

40106833

40107845

40108845

40109845

40110845

40111845

40112845

40113845

40114845

40115845

40116845

40117845

40118845

40119845

40120845

40121845

40122845

40123845

40124845

40125845

40126845

40127845

40128845

40129845

40130845

40131855

40132855

40133855

40134855

40135855

40136855

40137855

40138855

40139855 40140855 40141855 40142855 40143855 40144855 40145855 40146855 40147855 40148855 40149855 40150855 40151855 40152855 40153855 40154855 40155855 40156855 40157855 40158855 40159855 40160855 40161855 40162855 40163855 40164855 40165855 40166855 40167855 40168855 40169855 40170855 40171855 40172855 40173855 40174855 40175855 40176855 40177855 40178855 40179855 40180855 41040812 41041812 41042812 41043812 41044812 41045812 41046812 41047812 41048812 41049812 41050812

41051812

41052812

41053812

41054812

41055812

41056812

41057812

410.58812

41059812

41060812

41061812

41062812

41063812

41064812

41065812

41066812

41067812

41068812

41069812

41070812

41071812

41072812

41073812

41074812

41075812

41076812

41077812

41078812

41079812

41080812

41081812

41082833

41083833

41084833

41085833

41086833

41087833

41088833

41089833

41090833

41091833

41092833

41093833

41094833

41095833

41096833

41097833

41098833

41099833

41100833 41101833 41102833 41103833 41104833 41105833 41106833 41107845 41108845 41109845 41110845 41111845 41112845 41113845 41114845 41115845 41116845 41117845 41118845 41119845 41120845 41121845 41122845 41123845 41124845 41125845 41126845 41127845 41128845 41129845 41130845 41131845 41132855 41133855 41134855 41135855 41136855 41137855 41138855 41139855 41140855 41141855 41142855 41143855 41144855 41145855 41146855 41147855 41148855 41149855 41150855 41151855 41152855

41153855

41154855

41155855

41156855

41157855

41158855

41159855

41160855

41161855

41162855

41163855

41164855

41165855

41166855

41167855

41168855

41169855

41170855

41171855

41172855

41173855

41174855

41175855

41176855

41177855

41178855

41179855

41180855

42040812

42041812

42042812

42043812

42044812

42045812

42046812

42047812

42048812

42049812

42050812

42051812

42052812

42053812

42054812

42055812

42056812

42057812

42058812

42059812

42060812

42061812 42062812

42063812

42064812

42065812

42066812

42067812

42068812

42069812

42070812

42071812

42072812

42073812

42074812

42075812

42076812

42077812

42078812

42079812

42080812

42081812

42082833

42083833

42084833

42085833

42086833

42087833

42088833

42089833

42090833

42091833

42092833

42093833

42094833

42095833

42096833

42097833

42098833

42099833

42100833

42101833

42102833

42103833

42104833

42105833

42106833

42107845

42108845

42109845

42110845

42111845

42112845

42113845

42114845

42115845

42116845

42117845

42118845

42119845

42120845

42121845

42122845

42123845

42124845

42125845

42126845

42127845

42128845

42129845

42130845

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42132855

42133855

42134855

42135855

42136855

42137855

42138855

42139855

42140855

42141855

42142855

42143855

42144855

42145855

42146855

42147855

42148855

42149855

42150855

42151855

42152855

42153855

42154855

42155855

42156855

42157855

42158855

42159855

42160855

42161855

42162855

42163855 42164855 42165855 42166855 42167855 42168855 42169855 42170855 42171855 42172855 42173855 42174855 42175855 42176855 42177855 42178855 42179855 42180855 43040812 43041812 43042812 43043812 43044812 43045812 43046812 43047812 43048812 43049812 43050812 43051812 43052812 43053812 43054812 43055812 43056812 43057812 43058812 43059812 43060812 43061812 43062812 43063812 43064812 43065812 43066812 43067812 43068812 43069812 43070812 43071812 43072812 43073812 43074812

43075812

43076812

43077812

43078812

43079812

43080812

43081812

43082833

43083833

43084833

43085833

43086833

43087833

43088833

43089833

43090833

43091833

43092833

43093833

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43095833

43096833

43097833

43098833

43099833

43100833

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43102833

43103833

43104833

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43107833

43108845

43109845

43110845

43111845

43112845

43113845

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43115845

43116845

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43118845

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43120845

43121845

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43123845

43124845 43125845

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43132855

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43134855

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43137855

43138855

43139855

43140855

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43144855

43145855

43146855

43147855

43148855

43149855

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43151855

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43154855

43155855

43156855

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43158855

43159855

43160855

43161855

43162855

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43164855

43165855

43166855

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43169855

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43171855

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43173855

43174855

43175855 43176855

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43179855

43180855

44040812

44041812

44042812

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44044812

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44046812

44047812

44048812

44049812

44050812

44051812

44052812

44053812

44054812

44055812

44056812

44057812

44058812

44059812

44060812

44061812

44062812

44063812

44064812

44065812

44066812

44067812

44068812

44069812

44070812

44071812

44072812

44073812

44074812

44075812

44076812

44077812

44078812

44079812

44080812

44081812

44082833

44083833

44084833

44085833

44086833

44087833

44088833

44089833

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44091833

44092833

44093833

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44095833

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44098833

44099833

44100833

44101833

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44103833

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44105833

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44108845

44109845

44110845

44111845

44112845

44113845

44114845

44115845

44116845

44117845

44118845

44119845

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44121845

44122845

44123845

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44125845

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44128844

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44133855

44134855

44135855

44136855 44137855

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44145855

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44150855

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44154855

44155855

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44157855

44158855

44159855

44160855

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44162855

44163855

44164855

44165855

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44167855

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44169855

44170855

44171855

44172855

44173855

14174855

44175855

44176855

44177855

44178855

44179855

44180855

45040812

45041812

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45049812

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45052812

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45054812

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45056812

45057812

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45060812

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45063812

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45065812

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45071812

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45073812

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45082833

45083833

45084833

45085833

45086833

45087833

45088833

45069833

45090833

45091833

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45093833

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45097833

45098833

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45100833

45101833

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45103833

45104833

45105833

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45107833

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45109845

45110845

45111845

45112845

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45114845

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45117845

45118845

45119845

45120844

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45125844

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45127844

45128844

45129844

45130844

45131844

45132844

45133855

45134855

45135855

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45138855

45139855

45140855

45141855

45142855

45143855

45144855

45145855

45146855

45147855

Λ«1 Aftft«?ς 45149855 45150855 45151855 45152855 45153855 45154855 45155855 45156855 45157855 45158855 45159855 45160855 45161855 45162855 45163855 45164855 45165855 45166855 45167855 45168855 45169855 45170855 45171855 45172855 45173855 45174855 45175855 45176855 45177855 45178855 45179854 45180854 46040812 46041812 46042812 46043812 46044812 46045812 46046812 46047812 46048812 46049812 46050812 46051812 46052812 46053812 46054812 46055812 46056812 46057812 46058812 46059812

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Claims

We Claim:

1. A computer program product comprising a computer useable medium having computer program logic recorded thereon for enabling a processor in a computer system to control the processing of cotton through a gin to produce lint, said computer program logic comprising: measuring means for enabling the processor to measure sensor data that correspond to color, moisture content, and trash content of the cotton as it enters the gin; gin decision matrix generating means for enabling the processor to generate a gin decision matrix that includes optimum process control decisions that maximize net return from the lint as a function of input state of the cotton entering the gin; gin process control decision means for enabling the processor to select an optimum process control decision from said gin decision matrix for an input state corresponding to said sensor data, wherein said optimum process control decision corresponds to an optimum gin machine sequence for cotton having said input state corresponding to said sensor data, said optimum gin machine sequence having a first portion and a second portion; predicting means for enabling the processor to compute and store predicted values for color, moisture content, and trash content for the cotton after processing through said first portion of said optimum gin machine sequence; and gin process control implementation means for enabling the processor to implement said optimum process control decision by routing cotton through said optimum gin machine sequence .

2. The computer program product of claim 1, further comprising: second measuring means for enabling the processor to measure second sensor data that correspond to color, moisture content , and trash content of the cotton after it has been processed through said first portion of said optimum gin machine sequence .

3. The computer program product of claim 2, further comprising: error feedback means for enabling the processor to compare said second sensor data to said predicted values to generate an error; and error adjusting means for enabling the processor to adjust said optimum gin machine sequence and to adjust said predicted values to compensate for said error.

4. The computer program product of claim 3 , further comprising: third measuring means for enabling the processor to measure lint sensor data that correspond to color, moisture content, and trash content of the cotton after it has been processed through said second portion of said optimum gin machine sequence .

5. The computer program product of claim 4 , further comprising: second predicting means for enabling the processor to compute and store second predicted values for color, moisture content, and trash content for the cotton after processing through said second portion of said optimum gin machine sequence.

6. The computer program product of claim 5, further comprising: second error feedback means for enabling the processor to compare said lint sensor data to said second predicted values to generate a second error; and second error adjusting means for enabling the processor to adjust said second portion of said optimum gin machine sequence and to adjust said second predicted values to compensate for said second error.

7. The computer program product of claim 3 , wherein said error adjusting means comprises weighting means for enabling the processor to weight said error.

8. The computer program product of claim 6 , wherein said second error adjusting means comprises second weighting means for enabling the processor to weight said second error.

9. The computer program product of claim 1, wherein said gin decision matrix generating means comprises a plurality of tabular transition functions.

10. The computer program product of claim 1, wherein said gin decision matrix generating means comprises an algorithm for each gin machine in said optimum gin machine sequence, wherein said algorithm quantifies the effect of that gin machine on leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) .

11. The computer program product of claim 10, wherein said gin decision matrix generating means comprises a cylinder cleaner algorithm as follows :

SLFL = -0.1305 - 0.0619 * SM + 1.0599 * SLF SML = SM SRDL = 3.4151 - 0.0008 * SM + 0.9606 * SRD

STOL = -0.6071 - 0.0057 * SM + 1.0127 * STO

SLNL = 0.2557 - 0.0012 * SM + 0.7764 * SLN

SPBL = 2.8104 - 0.0137 * SM + 0.6457 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by a cylinder cleaner, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the cylinder cleaner.

12. The computer program product of claim 10, wherein said gin decision matrix generating means comprises a ginstand algorithm as follows :

SLFL = SLF

SML = SM

SRDL = 19.52 - 0.12 * SM + 0.75 * SRD

STOL = 9.22 + 0.14 * SM + 0.72 * STO

SLNL = 0.31 + 0.002 * SM + 0.72 * SLN

SPBL = 1.50 + 0.02 * SM + 0.81 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by a ginstand, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the ginstand.

13. The computer program product of claim 10, wherein said gin decision matrix generating means comprises an impact cleaner algorithm as follows : SLFL = -0.1305 - 0.0619 * SM + 1.0599 * SLF

SML = SM

SRDL = 3.4151 - 0.0008 * SM + 0.9606 * SRD

STOL = -0.6071 - 0.0057 * SM + 1.0127 * STO

SLNL = 0.2557 - 0.0012 * SM + 0.7764 * SLN

SPBL = 2.8104 - 0.0137 * SM + 0.6457 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by an impact cleaner, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the impact cleaner.

14. The computer program product of claim 10, wherein said gin decision matrix generating means comprises a one lint cleaner algorithm as follows:

SLFL = -0.6665 + 0.0937 * SM + 0.8296 * SLF

SML = SM

SRDL = 25.9279 - 0.0834 * SM + 0.6757 * SRD

STOL = -8.0604 - 0.1694 * SM + 1.2043 * STO

SLNL = 0.1742 + 0.0003 * SM + 0.8288 * SLN

SPBL = 3.3751 - 0.0222 * SM + 0.5970 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by one lint cleaner, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the one lint cleaner.

15. The computer program product of claim 10, wherein said gin decision matrix generating means comprises a two lint cleaner algorithm as follows:

SLFL = -1.0150 + 0.1483 * SM + 0.7278 * SLF SML = SM

SRDL = 38.1983 - 0.2905 * SM + 0.5302 * SRD STOL = -12.6405 - 0.1969 * SM + 1.3191 * STO SLNL = -0.0520 + 0.0003 * SM + 1.0266 * SLN SPBL = 2.3649 - 0.0183 * SM + 0.7439 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by two lint cleaners, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the two lint cleaners.

16. The computer program product of claim 10, wherein said gin decision matrix generating means comprises a stick machine algorithm as follows :

SLFL = 0.1625 - 0.0710 * SM + 1.0326 * SLF

SML = SM

SRDL = 2.3777 - 0.0299 * SM + 0.9736 * SRD

STOL = 1.8168 - 0.0011 * SM + 0.9419 * STO

SLNL = 0.1996 - 0.0003 * SM + 0.8226 * SLN

SPBL = 1.8629 - 0.0025 * SM + 0.7587 * SPB wherein SLFL, SML, SRDL, STOL, SLNL, SPBL represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, after processing by a stick machine, and SLF, SM, SRD, STO, SLN, SPB represent the values of leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and +b (PB) , respectively, input to the stick machine.

17. The computer program product of claim 1, wherein said gin decision matrix generating means comprises a drier algorithm as follows :

SLFL = SLF

SRDL = SRD

STOL = STO* (1.0- (SM-SMD/100.0)

SLNL = SLN

SPBL = SPB

SML = 4.2767+0.6397*SM-0.01713*TEMP wherein SLFL, SRDL, STOL, SLNL, SPBL, SML represent the values of leaf trash (LF) , reflectance (RD) , turnout (TO) , length (LN) , +b (PB) , and moisture content (M) , respectively, after processing by the drier, and SLF, SRD, STO, SLN, SPB, SM represent the values of leaf trash (LF) , reflectance (RD) , turnout (TO) , length (LN) , +b (PB) , and moisture content (M) , respectively, input to the drier, and TEMP represents the temperature of the drier.

18. The computer program product of claim 1, wherein said gin process control implementation means comprises: valve control means for enabling the processor to change a position of valves that divert the flow of cotton through said optimum gin machine sequence; and valve position determining means for enabling the processor to determine the position of the valves.

19. The computer program product of claim 1, further comprising: display means for enabling the processor to display said sensor data and said optimum gin machine sequence .

20. A control system for controlling the processing of cotton through a gin to produce lint, the gin having a plurality of auxiliary treatment units and a duct through which entrained cotton flows, said control system comprising: measuring means for measuring sensor data that correspond to color, moisture content, and trash content of the cotton; processing means coupled to said measuring means , said processing means processing said sensor data and selecting a set of said plurality of auxiliary treatment units through which the cotton is processed to produce lint, said set corresponding to an optimum gin machine sequence that maximizes net return from the lint ,- and cotton diversion means coupled to each of said plurality of auxiliary treatment units and coupled to said processing means, wherein said processing means activates said cotton diversion means to divert cotton to flow through each of said plurality of auxiliary treatment units in said set and wherein said processing means deactivates said cotton diversion means to bypass each of said plurality of auxiliary treatment units not in said set.

21. The control system of claim 20, further comprising: second measuring means coupled to said processing means, said second measuring means measuring lint cleaner sensor data that correspond to color, moisture content, and trash content of the cotton as it enters a lint cleaning stage that contains a plurality of lint cleaners, wherein said processing means processes said lint cleaner sensor data and selects a set of lint cleaners through which the cotton is processed to produce lint, said set of lint cleaners corresponding to an optimum lint cleaning sequence that maximizes revenue from the lint, wherein said processing means activates said cotton diversion means to divert cotton to flow through each of said plurality of lint cleaners in said set and wherein said processing means deactivates said cotton diversion means to bypass each of said plurality of lint cleaners not in said set.

22. The control system of claim 21, wherein said cotton diversion means for each of said plurality of lint cleaners comprises : a supply valve for controlling flow of cotton through a supply conduit connecting said lint cleaner to the duct at a supply connection location; a return valve for controlling flow of cotton through a return conduit connecting said lint cleaner to the duct at a return connection location downstream from said supply connection location; and a duct valve for controlling flow of cotton through the duct, said duct valve disposed between said supply connection location and said return connection location.

23. The control system of claim 22, wherein said processing means activates said cotton diversion means by closing said duct valve while substantially simultaneously opening said supply valve and said return valve .

24. The control system of claim 23, wherein said processing means deactivates said cotton diversion means by opening said duct valve while substantially simultaneously closing said supply valve, and then closing said return valve after a pre-determined time delay.

25. The control system of claim 21, further comprising: third measuring means coupled to said processing means for measuring color, moisture content, and trash content of the lint after processing by said set of auxiliary treatment units.

26. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for processing input material through a processing plant to produce processed material, said method steps comprising:

(a) measuring sensor data at a measurement station that correspond to a physical state of the input material at said measurement station;

(b) determining an optimum processing machine sequence for input material entering the processing plant based on the physical state of the input material at said measurement station that corresponds to said sensor data, wherein said optimum processing machine sequence maximizes net return from the processed material; and

(c) routing the input material through said optimum processing machine sequence.

27. The program storage device of claim 26, wherein step (a) is performed as the input material enters the processing plant at said measurement station.

28. The program storage device of claim 26, wherein step (a) is performed after the input material at said measurement station has been processed through a first portion of said optimum processing machine sequence .

29. The program storage device of claim 26, wherein step (a) is performed after the input material at said measurement station has been completely processed through said optimum processing machine sequence .

30. The program storage device of claim 27, further comprising:

(d) measuring second sensor data at a second measurement station that correspond to the physical state of the input material after it has been processed through a first portion of said optimum processing machine sequence; and

(e) computing and storing a predicted value for the physical state of the input material after processing through said first portion of said optimum processing machine sequence.

31. The program storage device of claim 30, further comprising:

(f) comparing said second sensor data to said predicted value to generate an error; and

(g) adjusting said optimum processing machine sequence and said predicted value to compensate for said error.

32. The program storage device of claim 31, further comprising:

(h) measuring third sensor data that correspond to physical state of the input material after it has been completely processed through said optimum processing machine sequence; and

(i) computing and storing a second predicted value for the physical state of the input material after processing completely through said optimum processing machine sequence.

33. The program storage device of claim 32, further comprising:

(j) comparing said third sensor data to said second predicted value to generate a second error; and

(k) adjusting a second portion of said optimum processing machine sequence and said second predicted value to compensate for said second error.

34. The program storage device of claim 31, wherein step (g) comprises : weighting said error with a weighting factor.

35. The program storage device of claim 33, wherein step (k) comprises : weighting said second error with a weighting factor.

36. The program storage device of claim 29, further comprising:

37. The program storage device of claim 36, further comprising :

38. The program storage device of claim 37, further comprising:

(h) measuring third sensor data that correspond to the physical state of the input material after it has been completely processed though said optimum processing machine sequence;

(i) computing and storing a second predicted value for the physical state of the input material after processing completely through said optimum processing machine sequence;

39. The program storage device of claim 26, wherein step (b) comprises :

(1) evaluating an algorithm for each machine in said optimum processing machine sequence, wherein said algorithm quantifies the effect of that machine on the physical state of the input material .

40. The program storage device of claim 39, wherein step (1) comprises :

(i) determining coefficients for said algorithm based on cotton variety.

41. The program storage device of claim 33, wherein step (b) comprises :

42. The program storage device of claim 41, wherein step (1) comprises :

(i) determining coefficients for said algorithm based on cotton variety.

43. The program storage device of claim 41, wherein step (1) comprises :

(i) determining coefficients for said algorithm as a function of said error and said second error.

44. The computer program product of claim 6 , wherein said gin decision matrix generating means comprises an algorithm for each gin machine in said optimum gin machine sequence, wherein said algorithm quantifies the effect of that gin machine on leaf trash (LF) , moisture content (M) , reflectance (RD) , turnout (TO) , length (LN) , and -i-b (PB) , wherein coefficients for said algorithm are determined as a function of said error and said second error.

45. A control system for controlling the processing of lint through a mill, the mill having a plurality of auxiliary treatment units and a duct through which lint flows, said control system comprising: measuring means for measuring sensor data that correspond to color, moisture content, and trash content of the lint; processing means coupled to said measuring means, said processing means processing said sensor data and selecting a set of said plurality of auxiliary treatment units through which the lint is processed to produce lint of a predetermined quality, said set corresponding to an optimum mill machine sequence; and lint diversion means coupled to each of said plurality of auxiliary treatment units and coupled to said processing means, wherein said processing means activates said lint diversion means to divert lint to flow through each of said plurality of auxiliary treatment units in said set and wherein said processing means deactivates said lint diversion means to bypass each of said plurality of auxiliary treatment units not in said set.

46. The control system of claim 45, further comprising: second measuring means coupled to said processing means , said second measuring means measuring sensor data that correspond to color, moisture content, and trash content of the lint as it enters a second cleaning stage, wherein said processing means processes said sensor data and selects a set of cleaners in said second cleaning stage through which the lint is processed, said set of cleaners corresponding to an optimum cleaning sequence that maximizes quality of the lint, wherein said processing means activates said lint diversion means to divert lint to flow through each of said set of cleaners and wherein said processing means deactivates said lint diversion means to bypass cleaners not in said set .

47. The control system of claim 45, wherein said lint diversion means for each of said plurality of auxiliary treatment units comprises: a supply valve for controlling flow of lint through a supply conduit connecting said auxilliary treatment unit to the duct at a supply connection location; a return valve for controlling flow of lint through a return conduit connecting said auxilliary treatment unit to the duct at a return connection location downstream from said supply connection location; and a duct valve for controlling flow of lint through the duct, said duct valve disposed between said supply connection location and said return connection location.

48. The control system of claim 47, wherein said processing means activates said lint diversion means by closing said duct valve while substantially simultaneously opening said supply valve and said return valve .

49. The control system of claim 48, wherein said processing means deactivates said lint diversion means by opening said duct valve while substantially simultaneously closing said supply valve, and then closing said return valve after a pre-determined time delay.