CA1185691A - Method and apparatus for automatic abnormal events monitor in operating plants - Google Patents
Method and apparatus for automatic abnormal events monitor in operating plantsInfo
- Publication number
- CA1185691A CA1185691A CA000248995A CA248995A CA1185691A CA 1185691 A CA1185691 A CA 1185691A CA 000248995 A CA000248995 A CA 000248995A CA 248995 A CA248995 A CA 248995A CA 1185691 A CA1185691 A CA 1185691A
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- CA
- Canada
- Prior art keywords
- channel
- exceeded
- power spectral
- spectral density
- density data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
- G05B23/0229—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
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- G—PHYSICS
- G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
- G21D—NUCLEAR POWER PLANT
- G21D3/00—Control of nuclear power plant
- G21D3/04—Safety arrangements
- G21D3/06—Safety arrangements responsive to faults within the plant
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/028—Material parameters
- G01N2291/02872—Pressure
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E30/00—Energy generation of nuclear origin
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E30/00—Energy generation of nuclear origin
- Y02E30/30—Nuclear fission reactors
Abstract
ABSTRACT
An apparatus and method for automatically monitoring dynamic signals, such as from vibration sensors, in an operating industrial or other plant to identify abnormal events, draw conclusions as to their severity, and indicate action to be taken, utilizing a computer to control the scanning of one or two sensor channels at a time through a matrix of analog switches, and to process one or two channel signals through a signal processor for power spectral density (PSD) analysis (two channel signals for cross PSD analysis). The computer compares spectra with predetermined sets of frequency dependent limits and indicates the abnormal condition of apparatus in the plant associated with the spectra as a function of which set of limits is exceeded. The computer also indicates from a stored table the action to be taken for the abnormal condition found.
An apparatus and method for automatically monitoring dynamic signals, such as from vibration sensors, in an operating industrial or other plant to identify abnormal events, draw conclusions as to their severity, and indicate action to be taken, utilizing a computer to control the scanning of one or two sensor channels at a time through a matrix of analog switches, and to process one or two channel signals through a signal processor for power spectral density (PSD) analysis (two channel signals for cross PSD analysis). The computer compares spectra with predetermined sets of frequency dependent limits and indicates the abnormal condition of apparatus in the plant associated with the spectra as a function of which set of limits is exceeded. The computer also indicates from a stored table the action to be taken for the abnormal condition found.
Description
BACKGROUND CF THE INV~NTION
This invention relates to abnormal event monitors, and more particularly to dynamic signal monitors for parts of operating plan*s that are not readily ac essible for incpection.
Some plants ~re designed t~ oper~e for extended periods, such as nuclear p~wer plants. Inspection is virtually impossible in many of these plants without shutting down. Yet it would be desirable to continually ceek ol7t poten~ial pro~lems, analyze them as ~o severity and indicate wha~ action should be taken~
L~ose parts in a nuclear power plant can cause a varie~y of problemsO In vi~w of this, loose parts moni~oring of nuclear power plants has become common practice. A
~ypical loose pa:rt monit~r is disclosed in U. S. patent No.
3,860~481. Monit~ring is accomplished on-line by picking up impact energy of a loose part by a suitable sensor attached to it, and detecting the energy at the resonant frequency of the loose part. The outpu~ of the sensor is analyzed as 20 tG the ra~e ~nd ~he energy with which impact of the lo~se par~ occurs. H~wever9 this only indicates that a part being monitored has ~ecome loose, and does not provide informa~ion as to other conditions that may indicate a malfunction, or ~hat would indicate a potential mal~un~ionO ~or free and 25 1008e part detec~ion, s~ other techniques.have been developed ~s discl~sed in U. S. pat~nts .3,681,976 and 3~534,589.
Nondestruc~ive t~s~ing of pressure vessels~ and the like~ have been devised based on monitoring and analy~-- ing stress waves as discl~sed in U. S. patent No~ 3,545,262, ~3 and based on ultrasonic pulsing techniques as disclosed in U. S. patent No~ 3,857,052. Stress wave analysis is not~ however, suitable for ~n line monitoring~ and ultr -sonie pulsing techniques are limit~d to applications where an ul~rasonic transduoer can be po~ltioned or caused to be positioned from a remote console.
What is require~ is a system for con~inuously moni~oring a plant on line for anomalous behavior in which the monitor becomes part of the plant instrumentation and requires no opera~or action unless an anom~lous condition is detected. Such a monitorin~ system can decrease operating costs by preventive maintenance techniques.
In any pa~ticular system ~he~e will be a number of key parame~er; which can be easily monitored, such as temperature and pressure. However~ it would not be sufficient to monitor these parameters as they would, in general, indicate only when an alarm condi~ion is reached, and provide no opportunity to diagnose potential mal~unc-tion due to impending failure of some part, such as a pump or 20 . mo~or.
It has been recognized tha~ operating machinery will have charaoteristic vi:brations which will vary if the ma~hinery is not operating properly or if some part begins ~o deteriorate. See for example U. S~ patent~ No~.
This invention relates to abnormal event monitors, and more particularly to dynamic signal monitors for parts of operating plan*s that are not readily ac essible for incpection.
Some plants ~re designed t~ oper~e for extended periods, such as nuclear p~wer plants. Inspection is virtually impossible in many of these plants without shutting down. Yet it would be desirable to continually ceek ol7t poten~ial pro~lems, analyze them as ~o severity and indicate wha~ action should be taken~
L~ose parts in a nuclear power plant can cause a varie~y of problemsO In vi~w of this, loose parts moni~oring of nuclear power plants has become common practice. A
~ypical loose pa:rt monit~r is disclosed in U. S. patent No.
3,860~481. Monit~ring is accomplished on-line by picking up impact energy of a loose part by a suitable sensor attached to it, and detecting the energy at the resonant frequency of the loose part. The outpu~ of the sensor is analyzed as 20 tG the ra~e ~nd ~he energy with which impact of the lo~se par~ occurs. H~wever9 this only indicates that a part being monitored has ~ecome loose, and does not provide informa~ion as to other conditions that may indicate a malfunction, or ~hat would indicate a potential mal~un~ionO ~or free and 25 1008e part detec~ion, s~ other techniques.have been developed ~s discl~sed in U. S. pat~nts .3,681,976 and 3~534,589.
Nondestruc~ive t~s~ing of pressure vessels~ and the like~ have been devised based on monitoring and analy~-- ing stress waves as discl~sed in U. S. patent No~ 3,545,262, ~3 and based on ultrasonic pulsing techniques as disclosed in U. S. patent No~ 3,857,052. Stress wave analysis is not~ however, suitable for ~n line monitoring~ and ultr -sonie pulsing techniques are limit~d to applications where an ul~rasonic transduoer can be po~ltioned or caused to be positioned from a remote console.
What is require~ is a system for con~inuously moni~oring a plant on line for anomalous behavior in which the monitor becomes part of the plant instrumentation and requires no opera~or action unless an anom~lous condition is detected. Such a monitorin~ system can decrease operating costs by preventive maintenance techniques.
In any pa~ticular system ~he~e will be a number of key parame~er; which can be easily monitored, such as temperature and pressure. However~ it would not be sufficient to monitor these parameters as they would, in general, indicate only when an alarm condi~ion is reached, and provide no opportunity to diagnose potential mal~unc-tion due to impending failure of some part, such as a pump or 20 . mo~or.
It has been recognized tha~ operating machinery will have charaoteristic vi:brations which will vary if the ma~hinery is not operating properly or if some part begins ~o deteriorate. See for example U. S~ patent~ No~.
2~ 3~641~550 and 3,758,758~ For effec~ive monitor;ng,~he Yibra~ion signal~ of in~ere~t mus~ be identifiable above the ~ackground noise~ whic~ means that a baseline ~back~
ground) record of ~he sen~or signal must be ~adQ
to serve a~ a reference for comparison purpose~ la~er.
Both the linear vibration and nonlinear loose parts signals must be detec~ed and identified above the back-ground noise. For cost effectiveness, the sensors employed should be passive~ rather than active as in the S ultrasonic system disclosed in U. S. patent No. 3,?53,8$2 for monitoring vibrations in A nuclear reactor. ~owever, the us~ of passive sensors makes the background noise problem more severe.
Monitoring the vibration energy of a cu~ting tool and comparing it with a referen~e has been recognized as an effective way of determining wear for the purpose of determining the optimum time to change the t~ol. See for example U. S. patents Nos. 3,694,637 and 3,841~149.
But monitoring a single tool is not th~ same pro~lem as monitoring an operating plant. Plants usually have complex vibrational patterns due to various components operating independently. To complicate things even more, some components operate independe~tly and unsynchronized, and some even operate intermittently.
The development of programmed digital computers has made monit~ring systems for complex opera~ing plants feasible, as disclosed in U. S. pa~ent No. 3,142,820. In that moni~oring system, variables:of the pl~nt are monitored for comparison with operating limits. That will permit control of ~he plant, as by ~ompu~ing new ~e~ point~ for faetors con~rolling the variable, and wi~l~ of course, permit alarm csnditions ~o be de~e~ed and a~nounced. The problem is tha~ a failing component may, in the process 9 be overloaded to cause a complete
ground) record of ~he sen~or signal must be ~adQ
to serve a~ a reference for comparison purpose~ la~er.
Both the linear vibration and nonlinear loose parts signals must be detec~ed and identified above the back-ground noise. For cost effectiveness, the sensors employed should be passive~ rather than active as in the S ultrasonic system disclosed in U. S. patent No. 3,?53,8$2 for monitoring vibrations in A nuclear reactor. ~owever, the us~ of passive sensors makes the background noise problem more severe.
Monitoring the vibration energy of a cu~ting tool and comparing it with a referen~e has been recognized as an effective way of determining wear for the purpose of determining the optimum time to change the t~ol. See for example U. S. patents Nos. 3,694,637 and 3,841~149.
But monitoring a single tool is not th~ same pro~lem as monitoring an operating plant. Plants usually have complex vibrational patterns due to various components operating independently. To complicate things even more, some components operate independe~tly and unsynchronized, and some even operate intermittently.
The development of programmed digital computers has made monit~ring systems for complex opera~ing plants feasible, as disclosed in U. S. pa~ent No. 3,142,820. In that moni~oring system, variables:of the pl~nt are monitored for comparison with operating limits. That will permit control of ~he plant, as by ~ompu~ing new ~e~ point~ for faetors con~rolling the variable, and wi~l~ of course, permit alarm csnditions ~o be de~e~ed and a~nounced. The problem is tha~ a failing component may, in the process 9 be overloaded to cause a complete
3~
break down. It would be desirable to monit~r the vibrations of k~y componen~s and points in the plant, not for contrQl as disclosed in U. S. patent ~o. 3,71D~082 in a vibration testing environment, bu~ to find potential malfuncti~ns, draw some conclusions as ~o their severity, and then indicate to th~ operator what action he should take for preventive maintenance.
OBJECTS AND SUMMARY O~ THE INVENTION
An object ~f this invention is to provide for automatieally diagn~sing potenti21 malfuncticns in a~
operati~g plant and indicating any action to be taken f~r preventive maintenanceD
Another object of the invention is to m~nitor dyn~mic signals at selected points of ~ operating plant and per~orm power spectral density (PSD) analysis on the sig~al at selected pcints and cross PSD analysis between selected points to diagnose potential malfunctions and indicate preventive maintenance action, if any, to be taken.
Still another object is to compare PSD data from selected points with frequency dep~ndent limi~s so as to detect changes from baselin~ conditions~
Yet another obj~ct is to store PSD data in a historical file for comparison with cur~en~ data ~o 2~ determine trends and rate of ehange in equipmen~.
In accord nce with the pres ~t ~n~ention, ~onitor-ing o~ dy~amic signals; particularly time~depe~de~t .fluctuating sig~als such as ~rom vibration- and pre~re monitoring ~ensors at select~d points on an operating plant ~ 30 is maintained ~or de*ccting ~tential mal~unctions, such a~
~atigue-type o~ meo~anical ~ail~r~, drawin~ co~clusio~
','' : S
as to their severity, and indicating to operators what action should be taken by: sensing physical conditions at predetermined points monitored by sensors; employing a plurality of analog signal pr~cessing channe~s to detect subaudio frequency condition and low frequency condition 5 signal s in the range from about 0~01Hz to lkHz~ and high frequency noise signals above lkHz to about lOOkHz~ placing all o~ the channels under computer control selection for digital power spectral density (PSD) analysis, including cross PSD analysis of selected channels; employing the computer -10 -to compare PSD data with predetermined fre~uency dependent limits, and interpreting the result of these compari ons into diagnostlc ~onditions and indicating appropriate operator action from a prer~corded message library. In addition to this, a historical PSD data file is maintained for comparison of PSD data with baseline condi*ions pre-recorded in digital form from initial PSD calculations, and with subsequent PSD calculations in order to determine trends and the rate of change in ailing equipment.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic diagram of ~n exemplary operating plan~ illus*rating exemplary locations of physical condition sensors and an automatio monitoring and scanning system incorporating ~he present invention.
FIG. 2 is a block diagram of the au~omati~
monitoring and ~canning system shown in ~IG. 1.
FI~. 3 is a schematic diagram of a typical vibration monitoring channel~
FIG. 4 is a graph of th~ power spectral density ~PSD) of the typical channel shown in FIG. 3 illustrating ,~ `;.1 exemplary ~req~ency dependent limits used in diagnostic analysis.
~ IG. 5 is a graph of the PSD for the same channel as for the graph of FIGo 4 illustrating a deteriorated condition of the plant at a later time.
FIG. 6 is a typical sequential display of successive PSD records for the s~me channel illustrating the onset and subsidence of an exagg~rated anomalous condition.
DESCRIPTION OF THE PREFE~RED EMBODIMENTS
lG FIG. 1 illustrates a typical application of the present invention to a nuclear reactor 10 for a steam driven electric generator (not shown). The reactor is comprised o~ a pressurized low~r vessel 11 sealed by a~ upper vessel 129 through flanges .13.and 14. The reactor includes a nuclear core which generates substantial amounts of controlled he~at. Pumps 15 and 16 circulate a coolant through the reactor. The coolant enters through inlets 17 and 18, and exits through outlets 19 and 20~ The heated coolant i~ then circulated through steam generators 21 and 22 which are essentially only heat exchange units. Pump~
23 and 24 provide water under pressure through inlets 25 And 26 into ~he sealed chambers of the steam generator through which the coolant flows in spaced apar~ tubesO The chamber~ are comprised of upper and lower vessels hel~ toge~her 2~ by bolts through flanges in a manner similar to the reactor~
S~eam produced by the gener~tors passes ~hrough outle~s 27 and 28 ~o a turbine ~hich drives a rotor for the produc-tion of el~ctricity.
Abnormal vibration~ can o~ur in the r~actor due to ~ome internal failure. ~or early ~et~ction of such a 6q3~
failure, a neutron flux sensor 29 monitors th~ coolant and generates an analog signal sent to a monitoring and scanning system 30. 3nc~ detected, the plant must be shut down until the problem is corrected. It can be appreciated that if the impending failure could be an,ici~
pated in sufficient time, it would be possible to avoid it through routine prevQntive maintenance. To accomplish that, a vibration sensor 31, such as a triple-axis piezo-electric acceler~meter, is attached to the flange 13. The 10- composife signal (vector sum o~ vibra~ion components) generated by the sensor 31 is sent to the monitoring and seanning system. (Preamplifiers are assumed to be located ~t the site of the sensors to transmit analog signals over cables typically 500 feet long~. Vibration sQnsors ~re simi-larly attaehed to the pumps and steam generators, and coupledto the monitoring and scanning system through cablesO Each sensor may be a triplè-axis sensor or may co~sist o~ a si~gle-axis sensor. In the event separate vibration monitoring is desired at any one point in three orthogonal axes, three sensors may be provided, each coupled by a separate ~able as a dis-tinct input to the monitoring and seanning system.
These sensors could ~e used on any other type of plant as well as a nuclear plant. There is nvthing unique about a nuclear plant with respect to the manner in which vibration signals from the sensors are used to find potential malfunctionsj draw ~ome conclusions as to their severity and then indicate ~o operators wha~ preventive 74~26 S~R~
action he might ~ake. The signals may also be used by monitoring and scanning systems to detect any unusual event, such as impact of a loose part~ and to energizé
an alarm to call the ~vent to the attention of the plant operators. As will ~e described more fully with reference to FIG. 2, the sensor sign~ls are recorded on FM tape recorders 5 7 for record keeping and processed through a real-time signal processor for power spectral density analysis. Alarms insure instant operator attention to a pot~ntial damage or failure while spectral analysis of vibrations provide a highly refined, detailed record of plant dynamic characteristics through which identification and evaluation of potential failure mechanisms is made possible over a wide frequency range. PSD plo~s taken at regular intervals are examined ~y the moni~oring and scanning system for limits, changes and trends as the basis for failure prevention through timely indication of necessary preventive maintenance.
Identification and location of excessive vibra-tion requires characterization of the sensor signal for an observed condition. As will be described more fully hereinafter wi~h reference to ~IGS. 4 and 5, frequency range and amplitude limits of a PSD are predetermined and examined ~or a particular channel to determine whether it is exhibi~ing any anomaly. This requires the vibration signals ts b~ identifiable above background noise. To accomplish that, a baseline PSD is recorded ~or each channel, or pairs of channels ~o be eross oorrela~ed to serve as a reference. Both anomalous conditions and impac~s 5~
fr~m loose parts must be detected and identified above the background noise.
Referring now to FIG. 2, a vibration sensor 31 is shown coupled by its preamplifier 32 to a channel of an amplifier filter alàrm unit 33~ Each sensor has ~ts own channel in the unit 33 such that the signal from each se~sor is continually being amplifiedg filtered and tested for cer*a~n alarm conditions which produce "trip outpur"
signals to a programmed digital computer 34~ Ea~h such signal rPceived by the computer 34 causes the computer to branch into a subr~utine to effectively test each sensor to determine wh~ther it has created a "trip output" signal.
If so, the computer identifies the source of th~ alarm condition, display~ the information on a cathode ray tube 15 35 and produces a hard copy of the same informa~îon displayed on the CRT through a device 36. At the same time, a visual alarm ~light) is energized to indicate which channel has the alarm condition, and an audio alarm is energized to call the operators a~ention ~o the fact ~hat an alarm condition has been reached.
A similar amplifier filter alarm unit 37 i~
provided for other ~ypes of sensors such. as the neutron flux sensor 2 9 to determine when an alarm condition has occurred, sound the alarm and turn on the channe~ light.
2 5 A "trip output" signal is coupled from ea~h channel of the unit 37 to the computer 34 in order tha-t a separate subroutine of the prc~gram for the computer determine which channel has ~he alarm condition and to d.isplay the infor-mation through ~h~ CRT and hard copy device.
FIG. 3 illustrat~s a typical .hannel in the unit 33 for a vibration sensor and a typical channel for another type of sens~r in the unit 37. ~he vibration sensor 31 and neutron flux sensor 29 have b~en selected as r~presenting the typical sensors of each type. In the vibration ~hannel, the signal is first amplified through an amplifier 38 and then passed through a detector and ~ilter 39 to a discriminator 40. The output of the detector and filter 39 is a DC signal the amplitude of which is a function of vibration frequency and amplitude. Should ~he frequency and/or ~mplitude exceed a predetermined limit~ th~ DC output of the detector and filter will produce a "trip output" signal from the dis~rim-inator 40. That signal turns on a ligh~ 41 and se~s a latching s~i ch 42 which then connects the ligh~ 41 ~o a source of power (:B+) to m~intain the light until tha switch is rese~ upon.the operator responding to th~ vibration alarm.
The vibra~ion signal from amplifier ~8 is also passed through a detector and filter 44 for loose parts monitoring. The ~ilter characteri~tics are designed to produce an output signal above a predetermined amplitude only when impact signals (normally of higher frequency and lower amplitude~ are present. When the level has been exceeded, a discriminator 4S turns on a light 46 a~d sets a relay 47. All of the "trip output" signals ~rom vibration channels are coupled to an audio alarm 48 throu~h a buff~r 49 to sound an alarm.
Channels in the uni~ 37 (FIG. 2) for o~her ~ypes of sen~ors are very similar to ohannels in the unit 38 as shown in FIG f 3. The output of an amplifier SO is coupled by a low pass filter 51 and the filtered output is applied to a discriminator 52 which determines when a pre-determined amplitude has been excee~ed~ At that time a li-ght ~3 is turned on and an alarm relay 54 is set. The "trip out" signal from the discriminator 52 is applied to the audio alarm 48 through the buffer 49, as well as to the computer 34 (FIG~2).
Referring to FIG. 2, the output signal of the amplîfier in each rhannel of the unit 33 and the unit 37 is coupled through a separ2te cable to a selection matrix 55 which, under contrcl of the computer 34 selects which signal output is to be applied to a signal processor 56 and/or an FM tape recorder 57 for PSD analysis or reeordin~. Under normal operation, the computer will seauen-tially scan the signal outputs in a predetermined ordar for PSD analysis. The computer will also be able to turn on the FM ~ape reeorder in ord~r to record the analog signal from the sensor.
When an alarm condition produces a "~rip ou~put"
signal, the computer may be interrup~ed and caused to branch from its normal scanning pattern to select the channel pro-ducing the trip outpu~ signal for PSD analysis and tape recording. However, in the case of a "trip output" signal from the uni~ 37, the signal processor 56 is effectiv~ly turned off and the ~hannel signal .is passed straigh~ ~hrough with only analog-to-digital conv~rsion under control of the computer 34 to record j ust th~ signal producing the l'trip output" alarm unless PSD analysis o~ such a sign~l is r~quired.
Considering only output signals from vibration sensors~ and omitting from further discussion the loose parts monitoring function of ~ach channel~ it should be noted that normal operation of the monitoring and s~anning system is to sequentially connect the signal outputs of unit 33 to the signal processor 56 for PSD analysis under control of the computer. The spectral data developed by the signal processor 56 is received by the computer and further processed to find potential malfunctions.
In some cases it is desirable to analyze the relationship ~etween two channels so that events that are being sensed by two separate sensors may be correlated.
That is accomplished under control of. the computer by selecting two ch ~nnels, such 2S by se*ting a separa~e one-15 pole, N-position switch to connect a second ohannel to the processor 56. The signal processor would then be set to perform cross product calculations, which is a variation on the simpie Fouri~r transform calc.ulations ~ ~o analyze the cross PSD between the two channels. Fast Fourier 20 transform pro~essors capable of performing either ~he simple or the cross PSD calculations on command are commer-cially available from several sources.
In the case of cross PSD calculations s the cross product calculation performed be tween the two selected channels 25 can be used not only to obtain a cross ~pectral plot (cross correlation plots in the time domain) 9 but their transfer functio~s also. Ampli~udeg ph~se and coheren~e plots would be obtained from the transfer function c~lculations as well. These plots ~hen could be used to diagnose ~he condition of v2rious components relate~ to the channels from which these plots were o~tained.
While only vibrations have been referred to specifically, other types of physical conditions may be monitored by sensor~ ~ust as vibr tions are monito~ed by accelerometers to produce dynamic electrical signals, particularl~ those csnditions closely related to vibrations.
For example, pressure in a coolant line may be monitored since the dynamic variatîons of pressure in many ca~es can 10 be the driving ~unction of the vi~ration. Cross PSD analysis of the pressure function and .he vibration function can be of value in analyzing any anomaly present in the c301~nt line. A similar relationship can be found between two of the reactor plant channels which measure neutron flux leakage from the core ~only one is shown in FIG. 1). Cross PSD analysis between these channels can be used to-infer core vibrations which could not be sensed by conventional vibration sensors.
An example of cross PSD monitoring is in connection ~D with a charging pump in a nuclear power ~ation. Generating pressure pulsations cause movement in the core. A simple cross product (cross PS~) analysis of a pressure sensor fo~ the charging pump and a vibration sensor for ~he core would then indicate the cause of the core mo~ion and giv~
the operator an indi~ation of what ac~ion t~ ~ake, such ~s to check ~he charging pump to remove the caus~ of ~he core moti~n.
An example of a single channel PSD analysi~ is in connection with a reactor recirculation pump cavi~a~ing becau~e o~ a particular pres~ure co~ditio~ e~i~t~n~ at the pump. ~he dynamic condition signal too~ the ~orm o~
~n increa~lng spectr~l oontent at hl~her ~requenclo~.
~4 The sa~pling period for the signal is selected to pro~ide an adequate number of samples of the spectral content at the lol~est frequency of interest in the signal ~rom the pa~ticular sensor. Typical sampling periods ~o~ sensi~g ~ibrations in a nuclear power plant range f~o~ 1 to 120 seconds.
The normal PSD plot associated with the recirculating pump t~es the form of a decrea~ing spectral co~tent at higher frequencies. This gives a ~ery unique PSD plot for the pump while it is cavitating. The present invention would quickly detect this unique plot, diagnose the condition and indicate to the operator the action to take, Because of the many points that require monitoring in an operating plant~ the many potential malfunctions and the many causes, it is essential that all points be ~ery rapidly scanned and analy~ed. An operator could not be e~pected to scan all o~ the points in real time under ~anual 2~ control and also perform the analysis, e~en with a signal prooessor ~or au~omatically de~eloping the PSD data. An automatic monitoring and scanning system enhanced by the automatic diagnosis and indication of action to be taken, all in re~l time, in accordance with the present in~ention, will greatly increase the effectiveness o~ an operator and ~
insure much greater sa~ety than is othe~wise possible.
It should be ~oted t~at ~n the loose parts detec~io~
~unction of the system~ the occurrence of a loose~par~t~
signal is detected to cau6e an appropriate ma3sage to be displ~yed on the CRT. It also cause~ the F~ tape recorder to be tur~ed on ~nd to record the output of the se~sor ~rom the channel in which the loose parts eve~t has been detected to preser~e the signal from the loose part. It ~hould be ~oted that a standard ~ibration and loose parts ~o~ibor ~ 3~
has this same capability, i.e., it also can cause a tape recorder to be turned on and th~ appropriate tape recording channel selected to perform the s~me recording function.
In that case the use of a computer in the system does not significantly ~nhance the performance capabiliti~s, It is only in the PSD analysis and diagnosis fun~tion of the present invention that the ~se of a computer significantly enhances performance capabilities.
Any potential malfunction is found automatically 10 by the cGmputer based on comparison of PSD data wi~h frequency dependent limits s~ored in a table in the memory sectivn of the computer or a mass data file 5 B . In the latter case, the computer looks up the table and copies it into temporary memory in the computer. The transfer is made while the PSD data is being developed for the particular channel~
Looking up the appropriate table is merely a matter of converting ~he channel number to an address code for the first of a block of memory word addresses in the mass data file. As each w3rd of *he table is copied, the address îs incremented until a predetermined number of words have been copied into the compu-ter. The ~a~le also includes diagnostic and action data. When a frequency dependent limi~ is found to be exceed~d by the ~hannel PSD data, the condition in-dicated in ~he ~able is displayed on the CRT and copied 2~ by the hard copy device. For each condition, th~re is also a corresponding ac~ion indicated in the table. That a~tion is also displayed on the CRT and copi~d by the hard copy device. Th~ following i5 an example of the diagnostio informati~n display~d for one complete cycle of 32 chann~ls, four of which are 3pares not in us~.
7~A26 r~
CHAPTER 0000 PAGE 0043 YEA~ 1975 DAY:HR~MIN:SEC- 0105-17:3D-03 CH CHANNEL NAM~ CONDITION ACTION
Dl LOW~R VESSEL MID FREQ. NOIS~ LISTEN, INSPECT NOW
0~ LOWER VESSEL HIGH FR~. NOISE LISTEN, INSPECT NOW
03 UPPER VESSEL HIGH FREQ. NOIS~ LISTEN, INSPECT NOW
04 UPPER VESSEL HIGH FREQ. NOISE LISTEN9 INSPECT NOW
05 RC PU~P 1-1-1 PUMP SEAL INSPECT PUMP SEALS
06 RC PU~P 1-1-2 NORMAL NONE
07 RC PUMP 1~2~1 PUMP NOISE CHECK PUMP
08 RC PUMP 1-2-2 HI~H FR~Q, NOISE INSPECT PUMP INST.
09 SG 1 1 UPPER HIGH FREQo NOIS~ LISTEN, CHECK SG INST.
10 SG 1-1 LOWER STRUCT~RE MOTION CHECK FOR SG MOTION
11 SG 1-1 UPPER LOW FREQ. NOISE CHEC~ SG NOISE
12 SG 1~2 UPPLR MID ~REQ. NOISE INSPECT SG INST.
15 CORE INT NI~7 CORE NOISE INSPECT CORE
17 CTMT AIR COOL.l-l STRUCTURE MOTION CHECK FAN
18 CTMT AIR COOL.1-2 NORMAL NONE
13 CTMT AIR COOL.1-3 STRUCTURE MOTION CnECK FAN
20 ACOUSTIC RCPl 1-1 NORMAL NOIYE
-~2 ACOUSTIC RCPl--2-1 MID-FREQ. SO~ LISTEN TO CHANNELS 7~8 23 ACOUSTIC RCPl-2-2 HIGH FREQ. SOUN~ LISTEN TO CHANNELS 7~8 24 ACOVSTIC PRZR HI~H FREQ. ~OUND LISTEN TO ALL CHANNELS
25 RCS PRESSURE NORMAL NON~
26 MAK~ UP PUMP 1-1 NORMAL NONE
28 AUXILIARY NORMAL NO~E
Thcre are ~wo upper and two lower vessel vibration sensing channels, al~hough on~y -t~.o ~re shown in FIGo 1. Each recirculating (RC) pump i~ equiped with one vibration sensing channel. The four recirculating pumps shown in FIG. 1 are assigned unique eode numbers for identification. ~he vibration sensing st~am generator ~SG) channels (one for each upper and low~r vessel~ are also assigned unique ccde num~ers as shown in the di~playO The ne~t f~ur ehannels 13 through 16 for moni~oring c~re internals (sensors no~
show~ in FIG. 1) yield c~re dynamic information. The .
J~ ~
sensor signals are typically O to 10 volt for O to 125%
power operation wi~h a bandwidth of at least 2OHz. The next three channels 17 through 19 are for low temp~rature accelerometers for sensing vibra~ions on the containment (CTMT) air cooler motor frames near the fan blades.
Channels 20 through 24 are for dyn2mic microphones located inside the plant containment, such as one near each r~cir culating pump and one near a pressurizer (not shown in FIG.
1), each with a bandwidth of 50Hz to 15kHz. Channel 25 0 iS 2 core pressure channel (sensor not shown in FIG. 1~, and is similar to the core internals channels. Channels 26 and 27 are for low temperature accelerometers for sensing vibrations of two make up pumps~ The auxiliary channel 28 is provided 2S a complete additional channel connected to a vibration sensor that can be easilv mounted on any piece of equipment in the plant for loose parts and vibration monitoring.
The conditions indicated in the foregoing example of a 32-channel display are merely for illustration only.
2~ In pr~ctice there would no~ be o many poten~ial malfunctions indicated because failures are rare and as ~ach potential mal~unc~ion is found, i~ is corrected. Th~ actions indicated are also only exemplary. In prar~ice more specific instruc-tions may be indicated, particularly as more is learned about ~he plant equipmen~ by experience. Wh~n plant install-ation is first comple~ed, a h~seline PSD and ~he table o~
frequency dependent limit , conditions and actions are s~ored for each chann~l~ The table is derived from in~ormation gathered from suppliers of components and from experience in other similar plants. The table is thereafter used in monitoring actu21 plant ~peration, and is refined as it is used to elimin~te false malfunction indications and include others not origin211y included. That is done with experience by adding or altering frequency depe~dent limits and associa.ed condition and action indications.
~ IG. 4 illustrates ~ PSD graph for one channel with four sets of L requency dependent limits used in a .
manner to be described mor~ fully hereinaf*er. The PSD
data is, of cour~e, in digital form so that limit tests can be performed by the computer and ~o that the data may be stored in the mass data file 58 for comparison with a later PSD data to detect significant changes and the rate of changes or trends. The limit tests performed on the PSD
data of a channel will indicate whether particular ~om-ponents are no~al, and if not whether the abnormality merely requires caution or some immediate action. For example 9 at the lower end of the spectrum illustrated in FIG. 4, a firs~ level 61 must be exceeded. Failure to do so may be an indication of some impending failure which will bear watching, ~ut which presents no problem until su~h time. However, a higher limit 62 should-not be exceeded, At any time it is found to be exceeded by an excursion below a level 63, a diagnostic messag~ is displayed indiea~ing ~hat a bad condition is present and indica~ing as ~he action to be taken to inspec* the particular component associated with ~his chann~l, such as a coolant pump, If ~he upp2r limit 63 is exceeded, the condition indicated might be critical and the action indicated might be to check the component immediately.
The next higher frequency range is also provided with three limits. The first, limi~ ~4, i5 S0 low as $~
be normally exceeded throughout, thus indicating that the condition of a related component, such as the pump seals is normal. Should the ne~t level 65 be exceeded, the diagnosis might be an impending failure with appropriate action indicated, such as to check pump seals for leaka~eO The upper limit 65 would indicate a eritical condition with~
the action indicated to replace the seals.
The next frequency range, a narrow rang~, has a lower limit the same as the limit 64 for the p~mp seals, a higher limit the same as the cri~ie~1 limi~ 66 for the pump saals, and a still higher limît equal to the limit 63. This particular frequeney range may be, for example, associa~ed with struc~ur~ mo~ion o~ ~he pump installation such that the level 64 indicates normal ~peration, while the level 66 indica~es some impending failure which would require checking the fan installation~ The higher level would then indicate a mor~ critical condi~ion requiring immediate replacement or repair of the pump s,upport structure.
The balance of the PSD represent~ normal pump noise 60 ~ha~ a lower limi~ 57 i5 provided ~o de~ermine that the pump is in operation. ~he n~xt higher lev~1 68, ~he upper bound Gf normal pump noise, will indicate det~ri-orating pump bearings tha~ will require replacement during . 20 the next scheduled preventive maintenance, particularly if, when compared with a subsequent PSD shown in FIG. 5~
it is seen that this li~it 68 is being exceeded ~y more than in the earlier PSD of FIG. 4. An upper limit 69 indicat~s when ~he condition has become so critical as to require more immediate actionS but diagnostic analysis of the PSD
should require that this level be exceeded during more scanning cycles than just the one indicated at FlG. 5, particularly since the peaX which does exceed that level in the PSD of FIG. 5 is not present throughout the frequency range of the limit 68.
To aid in the diagnosis, any frequency ranga of a PSD may be selected for display on the CRT 35 with the same frequency ranges of previous PSDs as shown in FIG. 5 with the four mos. reoent ones in the foreground and, for example, every other one of earlier PSDs in the background, all in successive order with the most recent at the bottom and each successively earlier one displaced to the righ. ~o provide a pseudo three dimensional display tha~ will quickly show ~he operator any trend. In this case the display indicates the random noise of a pump throughout the range monitored by the level 68 as shown in FI6S~ 4 and 5 and shows ~he growing trend of ~he anomaly shown in FIGS. 4 and 5. The time at which the cri~ical level 69 will be exceeded can be quickly estimated by the operator and - more accurately determined ~y the compu~er, ~s by a sub~
routine called out by ~he operator from a console keyboard-~or a trend analysis~
21.
A trend analysis would be performed by taking data in each of the freauency intervals of a PSD plot used for particular limit analysis and averaging the data over that particular interval for any one scan cycle to ob~ain 5 an average value over that interval that is stored as hîstorical data. The historical data would then be used to perform a trend analysis by taking the averaged value of the sample in any one frequency interval and doing a regression analysis to fit the best trend line to that 0 data. If that trend line shows a significant slope in the way of an increasing or decreasing value over a period of time, it would b~ indicative of a significant trend and would be used to alert the operator to the fac~ tha~ ~he data în the particular interval is showing this trend, and indicate appropriate corrective actio~.
In addition to the use of this automatic monitoring and scanning systlem on nuolear pswer s~ations~ o~her types of power stations, for exampl~ coal~fired power sta~ions, could use ~he sys-tem to equal advantage. The system would be applicable to chemical processes and other industrial applications that use pumps for circulating ~luids, and to po tentially all sorts of other plants . . A refinery, ~or example, would have circulating fluids and pumps 9 and certainly changes in the makeup of these would be of 2~ interestO In a molten salt coal gasifica~ion proc~ss a vibration se~sor on the reaction vessel will be used to obtain a PSD plot and from an analysis of the PSD plot an index of the viscos;ty of the melt in ~he gasifica~ion rig.
That data provides a criteria by which an opera-tor could vary the makeup and discharge of the molten salt as it becomes too viscous to economically pump the mix throu~h.
It w~uld, of course, be possible to provide a closed control loop to maintain viscosity constant. That is well within the state of the art of computer cor.trol ovsr an industrial process. What is new is the automatic scanning of the vibration sensor and obtaining PSD data of the sensor signal for ~nalysis.
In operation, the computer program compares the ~ross amplitude of the PSD si~nal at different frequencies against predetermined limits to detect the normal or abnormal condition of an operating plantO The plant is here illustrated as a nuclear s~eam generating plant for an electrical gener-ator but, as noted hereinbefore, it may be an industrial plant. Normally there are ~o loose parts in a plant, so the output of.the loose parts channel of each vibration sensor is normal:Ly quite low 9 such as near 2ero~ Thus there is inherent in the vibration monitoring and scanning system a capability of de~ecting loose parts quite easilyO What is more difficult is finding potential malfunctions. For that the s~stem relies upon power spectra of vibration and other dynamic signals.-The dynamie signa.l ~rom each s~nsor is comp~sed of many diff~rent mechanical actions or pro~esses goingon within the plant~ mos~ of which have u~ique frequencies ass~ciated with them. The core barrel, for example1 vibrates a~ one frequency while the control rod is so structured as to vibrate a~ som2 o~her frequencyO By pr~-. 23 ~Sf~FD~L
gramming the computer to look at the spectrum of theseevents with respect to just amplitude as a function of frequ~ncy, the condition of each is found separately by looking at unique peaks found in the sensor signal. How~
ever to monitor the core and the rod separately~ it is necessary t3 employ ~ greater level of specification in - measurements. This is done through power spec~ral density measurements taken by connecting the output of the sensor into the signal processor 56 (FIG. 2) for power spectrum analysis. In practice ~he signal processor includes a spectrum analyz~r that is ~ommercially available, such as one based upon a fast Fourier transform algorithm.
The signal proeessor provides in digital form a p~wer measuremenl: which can be plotted in amplitude as function of frequency over whatever range is selected for the ope~ation. By looking at this power spectral density ~PSD) against pr~determined limits, it is possible to reeognize that a specific characteristic frequency may have changed in amplitude to ex~eed predetermined limits or to have chan~ed in frequency. These changes ~ould be at*ribu~ed to, for example, some change in ~he d~mping of a particular part by some structural member breaking, as has occurred in at least one actual plant. There are o~her recognizable factors which cc~uld change the frequency of 25 the sensor signal such ~ha~ the PSD pea3cs would shif~ ei~he:r in ampli*ude or in freque~cy.
To facilita~e analysis oIe potential malfunc~ions by cvmparison of PSDs with frequency dependen~ limi~s~ a baseline PSD is obtained from each sensor signal when i~
is known that the plant is operating normally with all components in good condition. Differen~ PSDs may then be obtai~ed for a given sensor with different possible mal-functions simulated or deliberately introduced momentarily.
Limits can then be set for different frequency ranges and an appropriate actisn stored in the computer in association with each limit. Once this basic information is obtained and s-tor~d in the computer, the operator may alter these limits and/or the associated statements of ac~ion indicated, ~rom experience. If done judiciously, this technique for predicting potential malfunctions can be refined to a very high degree. For example, if ~requency noi~e on a pump bearing indicates a potential malfunction, b~t the level of frequency noise stabilizes, the limits for that pump may be wide~ed, Another source of information useful in deter.min-ing limits, at least at the outset, is the data supplied by the manufacturer of the eomponent parts, such as the various pumps. However, the data thus supplied should be compared a~ainst the actual data after initial installation to ascertain the effect the particular ins~allation may have on the data, particularly the suppor~ing s~ructure.
In any case, the initial setting of limits may be but ~
first step in a learning pr~cess that is aided very signifi-ca~tly by the infallibl~ m~mory of ~he compu~er~
Specifically~ the op~ration of the scanning and `monitoring system is as followsO The computer is ~cheduled in its tasks by a real-t~me clock. A stored executive program directs the comput~r to perform ~arious tasks a~
specifi~d times or timed intervals. Iterativ~ execution of 74~26 this ex~cutive program which calls out subroutines as necessary is the normal mode of operation of the system.
The computer m~y be interrupted from this mode of opera-tion if an abnormal condi~ion is detected in the plant, 5 2S ~y the loose par~s monitoring channels or by the:PSD
analysis channels. In o~her words, the ~xecutive program will periodically respond to the real time clock to cause subroutine to be called out for scanning the sensor signals through the selection matrix 55. Typically there may ~e anywhere~from eight to several hundred signal outputs to be sequentially scanned and processed by t~ signal processor 56~ Each signal scanned may also be record~d on the FM tape recorder, as noted hereinbefore. The signals from these sensors are continually monitored for lGose parts and checked in gross amplitude to determine the presence of any ;malfunction as described he~einb~fore with reference to FIG. 3. The improvement in the scanning and monitoring system resides in analyzing the PSD of each sens~r signal in respect to frequency dependent ampli~ude limits.
The computer 34 controls the signal processor in selec~ing a frequency range over which the spectrum analysis is to be carried out for the particular sensor signal. When ~he spectrum analysis is comple~ed for a givcn signal~
the signal processor interrupts ~he compu~er and ~he com-puter receives ~he PSD in di~i~al form) i.eO, in th~ form of a digital value equal to the scaled amplitude of ~he PSD a~ a function of frequency~ Typically a PSD may înclude 74~26 ~5~
256 equally spaced frequency points, and the amplitude a.
each point is quantized to one part in 1024 for a resolu-tion that is essentially one tenth of one per~ent in amplitude.
This PSD data in digital form is ~hen compared with numerical limits in a ~able, either in the computer memory itself or in the mass data file 58. In either case, the operator can set or alter these limits through a console keyboard 70. Th~ particular family of limits chosen for a particular sensor signal can be typically plotted over 32 discrete intervals covering the PSD. These intervals can have arbitrary beginning and ending points in fr~quency, and for each of these intervals, three limit values may be set. On~ is a low limit which, for example, should be exceeded. Should the PSD being analyzed fall below this limit, a malfunc tion would be indicate~ and a diagnostic m~ssage would be displayed on the CRT 35 and the hard copy device 36 to the effect that the signal has been lost and that operation of some device should be checked, such as "cheek to see if motor No, 3 is on." The next level could be an alert level, that is to say the first degree of operating abnormality. The third level would then be an alarm level which indicates the frequency dependence amplitude o~ the PSD has grossly exceeded normal opera~ing limits. In other frequency interval6, the first (lower) level may be the cau~ion level if exceeded while the next is an abnormal;ty level and the third is an alarm level.
In either case, for each comparis~n level some diagnostic 74~26 informati~n is displayed on the screen of the CRT and the hard copy device.
The message display is in the form of a tabular listing giving channel (sensor number), channel identifica tion 9 the nature o~ the abnormal event that has been de~ected, and the corrective action indicated for the operator to take to either further define the nature oS thé abnormality or to correct the abnormality. The nature of these messages is such that they can be changed if~ in the judgment of the 10 operator, they do not a~equately describe the situation or, it is determined from experience that they do not accurately describ the situation. Thus, as more information is developed about the plant, the message information may be easily ch~nged through the console keyboard jus~ as the limits themselves may be changed.
In prac~tice~ the limits and the.di gnostic informa-tion would be~stored in the computer memory in order to facilitate executing the sequence of instructions necessary to make ~he limit comparisons and sele~t for display the appropriate diagnostic information. However, in the event there is insufficien~ memory in the computer to store all of ~he informa~ion, i~ would be possible ~o store i~ in the mass datA file and to read it into the computer for each channel 2S it is scanned in sequence, as indicated hereinbefore. Thus~ while the signal processor ~6 is carry-ing out ~he necessary compu~a~ions to develop th~ PSD for the channel, ~he ~ompu~er may be reading in~o compu~er memory the ~able of limi~ and diagnos~ic mes~ages for tha~ channel from the mass data file.
~ 9~ ~
In a preferred embodiment the mass data file is also used to store complete PSD scans for all channei~
over a selected interval of from one hour to as much as one year or even more~ It is then possible to retri~ve thls information from the ~ass data file to compare it with the current da~a and thus determine any changes and the rate o~ changes and trends. In practice~ a subroutine to recall this data from the mass data file for this purpose would be under operator control. At any time that an al~rm is indicated, or there is a diagnostic message of a serious nature, th~ operator would be able to call for CRT display in a ps udo three dimensional form as shown in FIG. 6 of a frequency interval of interest in prior PSDs for comparison.
Alternatively~ the operatcr could call for CRT display of only the current PSD with the limits indicated as shown in FIG. 4. Following that, he could ca~l for a particular prior PSD, such as one taken an h~ur ago, to be displayed superimposed over the current PSD so that he may compare the two spectra to determi~e the change which has taken place.
2D He could make sp~cific comparison with successively ~arlier PSDs ~o determine the ra~e of change and the trend, and for a final overview, display all of the prior PSDs wi~h the curren~ one in th~ psPudo ~hre~ dimensiona~ form of ~IG. 6.
The foll~wing flow charts illus~rate ~he more fundamental subroutines ~mployed. All may be readily executed by any scientific computer~ or industrial pr~cess control computer. A computer Model PDP 11 manufactured by Digi~al Equipment Corporation is typical.
74A~6 DAILY SERVICE ROUTINE
.
START
. -~ . . . _ .
~et N=O
. _ r~
Does operator want' koutine for modiflcation to modify cha~nels Yes of table which indicates in service table? ~ -whether channel N is in , ervice~
No .
Routine for modification to modify levels ~ ~of levels for channel N.
. f~r channel N?
~,, .,,, _ .
No opere or wan~ rRoutine for m~dification to modify anAlysis Yes _ ~ of frequency ran~es for fre~uency range~ ~channel ~.
for channel N? - -------------N _o-----_______ o __ . _ N~N ?
No mslx Yes YPS
r--- ~No ate entered in correct ~ormat?
, ~
_ INo e entered in correct ~ormat?
Yes .
ST~P
SCANNING N CHANNEL~
START
~1 ~ ~ ~ No LC h =~
Ye Look up frequency range ~ .
SELECT channel N; start PSD
prooessing; store start time 'Read PSD data into oomputer`
_____ _ 'Enter subroutine COMPARE for~
. channel N (all sets of limi~s) _~
~Compare PSD with frequency`
dependent limits and action statements 1 _~ , Display statements .
,~
Store PSD for channel N in ma~s data file No ~ ~_~
' ~
. Yes .
STOP
3~l The ~aily service rou~tine provides for entering the date and the correct time at the beginnir.g of the first shift of each day. The real-time cl~ck of the computer accepts the time entered as the correct ~ime from which time is thereafter reckoned. At this time the operator has the option to modify the table of channels in service~
to modify the ~est levels for the various channels and/or to msdi~y the frequency ranges for the test levels o~ the various channels.
- Once the daily service routine has been comple~ed~
the operator may initiate the scanning rou-tine from the console. The scanning routine stops when all N channels have been scanned, but is automatically started again at predetermined times, or intervals of time, as set in an P.xecutive routine.
Altho~agh particular embodiments have been dis-closed and described, it should be understood that e~uivalent embodiments and modifications are also contemplated, particu-larly in the respec*s already indicated of automatic analysis of the power spectra of any dynamic signals (time dependent fluctuating signals generally) in any operating plant, and in respect ~o cross correlation of power spe~tra of selected dynamic signals, including the maintenance of a historical file of power spectra in each dyn~mic signal for comparis~n, all for the purpose of finding potential malfunctions, drawing conclusions as to their severity, and indicating ~o ~he opera tor what action to ~ake. Consequen~ly 9 i~ iS intended ~hat the claims be interpreted to cover such modifications and equivalen~s.
break down. It would be desirable to monit~r the vibrations of k~y componen~s and points in the plant, not for contrQl as disclosed in U. S. patent ~o. 3,71D~082 in a vibration testing environment, bu~ to find potential malfuncti~ns, draw some conclusions as ~o their severity, and then indicate to th~ operator what action he should take for preventive maintenance.
OBJECTS AND SUMMARY O~ THE INVENTION
An object ~f this invention is to provide for automatieally diagn~sing potenti21 malfuncticns in a~
operati~g plant and indicating any action to be taken f~r preventive maintenanceD
Another object of the invention is to m~nitor dyn~mic signals at selected points of ~ operating plant and per~orm power spectral density (PSD) analysis on the sig~al at selected pcints and cross PSD analysis between selected points to diagnose potential malfunctions and indicate preventive maintenance action, if any, to be taken.
Still another object is to compare PSD data from selected points with frequency dep~ndent limi~s so as to detect changes from baselin~ conditions~
Yet another obj~ct is to store PSD data in a historical file for comparison with cur~en~ data ~o 2~ determine trends and rate of ehange in equipmen~.
In accord nce with the pres ~t ~n~ention, ~onitor-ing o~ dy~amic signals; particularly time~depe~de~t .fluctuating sig~als such as ~rom vibration- and pre~re monitoring ~ensors at select~d points on an operating plant ~ 30 is maintained ~or de*ccting ~tential mal~unctions, such a~
~atigue-type o~ meo~anical ~ail~r~, drawin~ co~clusio~
','' : S
as to their severity, and indicating to operators what action should be taken by: sensing physical conditions at predetermined points monitored by sensors; employing a plurality of analog signal pr~cessing channe~s to detect subaudio frequency condition and low frequency condition 5 signal s in the range from about 0~01Hz to lkHz~ and high frequency noise signals above lkHz to about lOOkHz~ placing all o~ the channels under computer control selection for digital power spectral density (PSD) analysis, including cross PSD analysis of selected channels; employing the computer -10 -to compare PSD data with predetermined fre~uency dependent limits, and interpreting the result of these compari ons into diagnostlc ~onditions and indicating appropriate operator action from a prer~corded message library. In addition to this, a historical PSD data file is maintained for comparison of PSD data with baseline condi*ions pre-recorded in digital form from initial PSD calculations, and with subsequent PSD calculations in order to determine trends and the rate of change in ailing equipment.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic diagram of ~n exemplary operating plan~ illus*rating exemplary locations of physical condition sensors and an automatio monitoring and scanning system incorporating ~he present invention.
FIG. 2 is a block diagram of the au~omati~
monitoring and ~canning system shown in ~IG. 1.
FI~. 3 is a schematic diagram of a typical vibration monitoring channel~
FIG. 4 is a graph of th~ power spectral density ~PSD) of the typical channel shown in FIG. 3 illustrating ,~ `;.1 exemplary ~req~ency dependent limits used in diagnostic analysis.
~ IG. 5 is a graph of the PSD for the same channel as for the graph of FIGo 4 illustrating a deteriorated condition of the plant at a later time.
FIG. 6 is a typical sequential display of successive PSD records for the s~me channel illustrating the onset and subsidence of an exagg~rated anomalous condition.
DESCRIPTION OF THE PREFE~RED EMBODIMENTS
lG FIG. 1 illustrates a typical application of the present invention to a nuclear reactor 10 for a steam driven electric generator (not shown). The reactor is comprised o~ a pressurized low~r vessel 11 sealed by a~ upper vessel 129 through flanges .13.and 14. The reactor includes a nuclear core which generates substantial amounts of controlled he~at. Pumps 15 and 16 circulate a coolant through the reactor. The coolant enters through inlets 17 and 18, and exits through outlets 19 and 20~ The heated coolant i~ then circulated through steam generators 21 and 22 which are essentially only heat exchange units. Pump~
23 and 24 provide water under pressure through inlets 25 And 26 into ~he sealed chambers of the steam generator through which the coolant flows in spaced apar~ tubesO The chamber~ are comprised of upper and lower vessels hel~ toge~her 2~ by bolts through flanges in a manner similar to the reactor~
S~eam produced by the gener~tors passes ~hrough outle~s 27 and 28 ~o a turbine ~hich drives a rotor for the produc-tion of el~ctricity.
Abnormal vibration~ can o~ur in the r~actor due to ~ome internal failure. ~or early ~et~ction of such a 6q3~
failure, a neutron flux sensor 29 monitors th~ coolant and generates an analog signal sent to a monitoring and scanning system 30. 3nc~ detected, the plant must be shut down until the problem is corrected. It can be appreciated that if the impending failure could be an,ici~
pated in sufficient time, it would be possible to avoid it through routine prevQntive maintenance. To accomplish that, a vibration sensor 31, such as a triple-axis piezo-electric acceler~meter, is attached to the flange 13. The 10- composife signal (vector sum o~ vibra~ion components) generated by the sensor 31 is sent to the monitoring and seanning system. (Preamplifiers are assumed to be located ~t the site of the sensors to transmit analog signals over cables typically 500 feet long~. Vibration sQnsors ~re simi-larly attaehed to the pumps and steam generators, and coupledto the monitoring and scanning system through cablesO Each sensor may be a triplè-axis sensor or may co~sist o~ a si~gle-axis sensor. In the event separate vibration monitoring is desired at any one point in three orthogonal axes, three sensors may be provided, each coupled by a separate ~able as a dis-tinct input to the monitoring and seanning system.
These sensors could ~e used on any other type of plant as well as a nuclear plant. There is nvthing unique about a nuclear plant with respect to the manner in which vibration signals from the sensors are used to find potential malfunctionsj draw ~ome conclusions as to their severity and then indicate ~o operators wha~ preventive 74~26 S~R~
action he might ~ake. The signals may also be used by monitoring and scanning systems to detect any unusual event, such as impact of a loose part~ and to energizé
an alarm to call the ~vent to the attention of the plant operators. As will ~e described more fully with reference to FIG. 2, the sensor sign~ls are recorded on FM tape recorders 5 7 for record keeping and processed through a real-time signal processor for power spectral density analysis. Alarms insure instant operator attention to a pot~ntial damage or failure while spectral analysis of vibrations provide a highly refined, detailed record of plant dynamic characteristics through which identification and evaluation of potential failure mechanisms is made possible over a wide frequency range. PSD plo~s taken at regular intervals are examined ~y the moni~oring and scanning system for limits, changes and trends as the basis for failure prevention through timely indication of necessary preventive maintenance.
Identification and location of excessive vibra-tion requires characterization of the sensor signal for an observed condition. As will be described more fully hereinafter wi~h reference to ~IGS. 4 and 5, frequency range and amplitude limits of a PSD are predetermined and examined ~or a particular channel to determine whether it is exhibi~ing any anomaly. This requires the vibration signals ts b~ identifiable above background noise. To accomplish that, a baseline PSD is recorded ~or each channel, or pairs of channels ~o be eross oorrela~ed to serve as a reference. Both anomalous conditions and impac~s 5~
fr~m loose parts must be detected and identified above the background noise.
Referring now to FIG. 2, a vibration sensor 31 is shown coupled by its preamplifier 32 to a channel of an amplifier filter alàrm unit 33~ Each sensor has ~ts own channel in the unit 33 such that the signal from each se~sor is continually being amplifiedg filtered and tested for cer*a~n alarm conditions which produce "trip outpur"
signals to a programmed digital computer 34~ Ea~h such signal rPceived by the computer 34 causes the computer to branch into a subr~utine to effectively test each sensor to determine wh~ther it has created a "trip output" signal.
If so, the computer identifies the source of th~ alarm condition, display~ the information on a cathode ray tube 15 35 and produces a hard copy of the same informa~îon displayed on the CRT through a device 36. At the same time, a visual alarm ~light) is energized to indicate which channel has the alarm condition, and an audio alarm is energized to call the operators a~ention ~o the fact ~hat an alarm condition has been reached.
A similar amplifier filter alarm unit 37 i~
provided for other ~ypes of sensors such. as the neutron flux sensor 2 9 to determine when an alarm condition has occurred, sound the alarm and turn on the channe~ light.
2 5 A "trip output" signal is coupled from ea~h channel of the unit 37 to the computer 34 in order tha-t a separate subroutine of the prc~gram for the computer determine which channel has ~he alarm condition and to d.isplay the infor-mation through ~h~ CRT and hard copy device.
FIG. 3 illustrat~s a typical .hannel in the unit 33 for a vibration sensor and a typical channel for another type of sens~r in the unit 37. ~he vibration sensor 31 and neutron flux sensor 29 have b~en selected as r~presenting the typical sensors of each type. In the vibration ~hannel, the signal is first amplified through an amplifier 38 and then passed through a detector and ~ilter 39 to a discriminator 40. The output of the detector and filter 39 is a DC signal the amplitude of which is a function of vibration frequency and amplitude. Should ~he frequency and/or ~mplitude exceed a predetermined limit~ th~ DC output of the detector and filter will produce a "trip output" signal from the dis~rim-inator 40. That signal turns on a ligh~ 41 and se~s a latching s~i ch 42 which then connects the ligh~ 41 ~o a source of power (:B+) to m~intain the light until tha switch is rese~ upon.the operator responding to th~ vibration alarm.
The vibra~ion signal from amplifier ~8 is also passed through a detector and filter 44 for loose parts monitoring. The ~ilter characteri~tics are designed to produce an output signal above a predetermined amplitude only when impact signals (normally of higher frequency and lower amplitude~ are present. When the level has been exceeded, a discriminator 4S turns on a light 46 a~d sets a relay 47. All of the "trip output" signals ~rom vibration channels are coupled to an audio alarm 48 throu~h a buff~r 49 to sound an alarm.
Channels in the uni~ 37 (FIG. 2) for o~her ~ypes of sen~ors are very similar to ohannels in the unit 38 as shown in FIG f 3. The output of an amplifier SO is coupled by a low pass filter 51 and the filtered output is applied to a discriminator 52 which determines when a pre-determined amplitude has been excee~ed~ At that time a li-ght ~3 is turned on and an alarm relay 54 is set. The "trip out" signal from the discriminator 52 is applied to the audio alarm 48 through the buffer 49, as well as to the computer 34 (FIG~2).
Referring to FIG. 2, the output signal of the amplîfier in each rhannel of the unit 33 and the unit 37 is coupled through a separ2te cable to a selection matrix 55 which, under contrcl of the computer 34 selects which signal output is to be applied to a signal processor 56 and/or an FM tape recorder 57 for PSD analysis or reeordin~. Under normal operation, the computer will seauen-tially scan the signal outputs in a predetermined ordar for PSD analysis. The computer will also be able to turn on the FM ~ape reeorder in ord~r to record the analog signal from the sensor.
When an alarm condition produces a "~rip ou~put"
signal, the computer may be interrup~ed and caused to branch from its normal scanning pattern to select the channel pro-ducing the trip outpu~ signal for PSD analysis and tape recording. However, in the case of a "trip output" signal from the uni~ 37, the signal processor 56 is effectiv~ly turned off and the ~hannel signal .is passed straigh~ ~hrough with only analog-to-digital conv~rsion under control of the computer 34 to record j ust th~ signal producing the l'trip output" alarm unless PSD analysis o~ such a sign~l is r~quired.
Considering only output signals from vibration sensors~ and omitting from further discussion the loose parts monitoring function of ~ach channel~ it should be noted that normal operation of the monitoring and s~anning system is to sequentially connect the signal outputs of unit 33 to the signal processor 56 for PSD analysis under control of the computer. The spectral data developed by the signal processor 56 is received by the computer and further processed to find potential malfunctions.
In some cases it is desirable to analyze the relationship ~etween two channels so that events that are being sensed by two separate sensors may be correlated.
That is accomplished under control of. the computer by selecting two ch ~nnels, such 2S by se*ting a separa~e one-15 pole, N-position switch to connect a second ohannel to the processor 56. The signal processor would then be set to perform cross product calculations, which is a variation on the simpie Fouri~r transform calc.ulations ~ ~o analyze the cross PSD between the two channels. Fast Fourier 20 transform pro~essors capable of performing either ~he simple or the cross PSD calculations on command are commer-cially available from several sources.
In the case of cross PSD calculations s the cross product calculation performed be tween the two selected channels 25 can be used not only to obtain a cross ~pectral plot (cross correlation plots in the time domain) 9 but their transfer functio~s also. Ampli~udeg ph~se and coheren~e plots would be obtained from the transfer function c~lculations as well. These plots ~hen could be used to diagnose ~he condition of v2rious components relate~ to the channels from which these plots were o~tained.
While only vibrations have been referred to specifically, other types of physical conditions may be monitored by sensor~ ~ust as vibr tions are monito~ed by accelerometers to produce dynamic electrical signals, particularl~ those csnditions closely related to vibrations.
For example, pressure in a coolant line may be monitored since the dynamic variatîons of pressure in many ca~es can 10 be the driving ~unction of the vi~ration. Cross PSD analysis of the pressure function and .he vibration function can be of value in analyzing any anomaly present in the c301~nt line. A similar relationship can be found between two of the reactor plant channels which measure neutron flux leakage from the core ~only one is shown in FIG. 1). Cross PSD analysis between these channels can be used to-infer core vibrations which could not be sensed by conventional vibration sensors.
An example of cross PSD monitoring is in connection ~D with a charging pump in a nuclear power ~ation. Generating pressure pulsations cause movement in the core. A simple cross product (cross PS~) analysis of a pressure sensor fo~ the charging pump and a vibration sensor for ~he core would then indicate the cause of the core mo~ion and giv~
the operator an indi~ation of what ac~ion t~ ~ake, such ~s to check ~he charging pump to remove the caus~ of ~he core moti~n.
An example of a single channel PSD analysi~ is in connection with a reactor recirculation pump cavi~a~ing becau~e o~ a particular pres~ure co~ditio~ e~i~t~n~ at the pump. ~he dynamic condition signal too~ the ~orm o~
~n increa~lng spectr~l oontent at hl~her ~requenclo~.
~4 The sa~pling period for the signal is selected to pro~ide an adequate number of samples of the spectral content at the lol~est frequency of interest in the signal ~rom the pa~ticular sensor. Typical sampling periods ~o~ sensi~g ~ibrations in a nuclear power plant range f~o~ 1 to 120 seconds.
The normal PSD plot associated with the recirculating pump t~es the form of a decrea~ing spectral co~tent at higher frequencies. This gives a ~ery unique PSD plot for the pump while it is cavitating. The present invention would quickly detect this unique plot, diagnose the condition and indicate to the operator the action to take, Because of the many points that require monitoring in an operating plant~ the many potential malfunctions and the many causes, it is essential that all points be ~ery rapidly scanned and analy~ed. An operator could not be e~pected to scan all o~ the points in real time under ~anual 2~ control and also perform the analysis, e~en with a signal prooessor ~or au~omatically de~eloping the PSD data. An automatic monitoring and scanning system enhanced by the automatic diagnosis and indication of action to be taken, all in re~l time, in accordance with the present in~ention, will greatly increase the effectiveness o~ an operator and ~
insure much greater sa~ety than is othe~wise possible.
It should be ~oted t~at ~n the loose parts detec~io~
~unction of the system~ the occurrence of a loose~par~t~
signal is detected to cau6e an appropriate ma3sage to be displ~yed on the CRT. It also cause~ the F~ tape recorder to be tur~ed on ~nd to record the output of the se~sor ~rom the channel in which the loose parts eve~t has been detected to preser~e the signal from the loose part. It ~hould be ~oted that a standard ~ibration and loose parts ~o~ibor ~ 3~
has this same capability, i.e., it also can cause a tape recorder to be turned on and th~ appropriate tape recording channel selected to perform the s~me recording function.
In that case the use of a computer in the system does not significantly ~nhance the performance capabiliti~s, It is only in the PSD analysis and diagnosis fun~tion of the present invention that the ~se of a computer significantly enhances performance capabilities.
Any potential malfunction is found automatically 10 by the cGmputer based on comparison of PSD data wi~h frequency dependent limits s~ored in a table in the memory sectivn of the computer or a mass data file 5 B . In the latter case, the computer looks up the table and copies it into temporary memory in the computer. The transfer is made while the PSD data is being developed for the particular channel~
Looking up the appropriate table is merely a matter of converting ~he channel number to an address code for the first of a block of memory word addresses in the mass data file. As each w3rd of *he table is copied, the address îs incremented until a predetermined number of words have been copied into the compu-ter. The ~a~le also includes diagnostic and action data. When a frequency dependent limi~ is found to be exceed~d by the ~hannel PSD data, the condition in-dicated in ~he ~able is displayed on the CRT and copied 2~ by the hard copy device. For each condition, th~re is also a corresponding ac~ion indicated in the table. That a~tion is also displayed on the CRT and copi~d by the hard copy device. Th~ following i5 an example of the diagnostio informati~n display~d for one complete cycle of 32 chann~ls, four of which are 3pares not in us~.
7~A26 r~
CHAPTER 0000 PAGE 0043 YEA~ 1975 DAY:HR~MIN:SEC- 0105-17:3D-03 CH CHANNEL NAM~ CONDITION ACTION
Dl LOW~R VESSEL MID FREQ. NOIS~ LISTEN, INSPECT NOW
0~ LOWER VESSEL HIGH FR~. NOISE LISTEN, INSPECT NOW
03 UPPER VESSEL HIGH FREQ. NOIS~ LISTEN, INSPECT NOW
04 UPPER VESSEL HIGH FREQ. NOISE LISTEN9 INSPECT NOW
05 RC PU~P 1-1-1 PUMP SEAL INSPECT PUMP SEALS
06 RC PU~P 1-1-2 NORMAL NONE
07 RC PUMP 1~2~1 PUMP NOISE CHECK PUMP
08 RC PUMP 1-2-2 HI~H FR~Q, NOISE INSPECT PUMP INST.
09 SG 1 1 UPPER HIGH FREQo NOIS~ LISTEN, CHECK SG INST.
10 SG 1-1 LOWER STRUCT~RE MOTION CHECK FOR SG MOTION
11 SG 1-1 UPPER LOW FREQ. NOISE CHEC~ SG NOISE
12 SG 1~2 UPPLR MID ~REQ. NOISE INSPECT SG INST.
15 CORE INT NI~7 CORE NOISE INSPECT CORE
17 CTMT AIR COOL.l-l STRUCTURE MOTION CHECK FAN
18 CTMT AIR COOL.1-2 NORMAL NONE
13 CTMT AIR COOL.1-3 STRUCTURE MOTION CnECK FAN
20 ACOUSTIC RCPl 1-1 NORMAL NOIYE
-~2 ACOUSTIC RCPl--2-1 MID-FREQ. SO~ LISTEN TO CHANNELS 7~8 23 ACOUSTIC RCPl-2-2 HIGH FREQ. SOUN~ LISTEN TO CHANNELS 7~8 24 ACOVSTIC PRZR HI~H FREQ. ~OUND LISTEN TO ALL CHANNELS
25 RCS PRESSURE NORMAL NON~
26 MAK~ UP PUMP 1-1 NORMAL NONE
28 AUXILIARY NORMAL NO~E
Thcre are ~wo upper and two lower vessel vibration sensing channels, al~hough on~y -t~.o ~re shown in FIGo 1. Each recirculating (RC) pump i~ equiped with one vibration sensing channel. The four recirculating pumps shown in FIG. 1 are assigned unique eode numbers for identification. ~he vibration sensing st~am generator ~SG) channels (one for each upper and low~r vessel~ are also assigned unique ccde num~ers as shown in the di~playO The ne~t f~ur ehannels 13 through 16 for moni~oring c~re internals (sensors no~
show~ in FIG. 1) yield c~re dynamic information. The .
J~ ~
sensor signals are typically O to 10 volt for O to 125%
power operation wi~h a bandwidth of at least 2OHz. The next three channels 17 through 19 are for low temp~rature accelerometers for sensing vibra~ions on the containment (CTMT) air cooler motor frames near the fan blades.
Channels 20 through 24 are for dyn2mic microphones located inside the plant containment, such as one near each r~cir culating pump and one near a pressurizer (not shown in FIG.
1), each with a bandwidth of 50Hz to 15kHz. Channel 25 0 iS 2 core pressure channel (sensor not shown in FIG. 1~, and is similar to the core internals channels. Channels 26 and 27 are for low temperature accelerometers for sensing vibrations of two make up pumps~ The auxiliary channel 28 is provided 2S a complete additional channel connected to a vibration sensor that can be easilv mounted on any piece of equipment in the plant for loose parts and vibration monitoring.
The conditions indicated in the foregoing example of a 32-channel display are merely for illustration only.
2~ In pr~ctice there would no~ be o many poten~ial malfunctions indicated because failures are rare and as ~ach potential mal~unc~ion is found, i~ is corrected. Th~ actions indicated are also only exemplary. In prar~ice more specific instruc-tions may be indicated, particularly as more is learned about ~he plant equipmen~ by experience. Wh~n plant install-ation is first comple~ed, a h~seline PSD and ~he table o~
frequency dependent limit , conditions and actions are s~ored for each chann~l~ The table is derived from in~ormation gathered from suppliers of components and from experience in other similar plants. The table is thereafter used in monitoring actu21 plant ~peration, and is refined as it is used to elimin~te false malfunction indications and include others not origin211y included. That is done with experience by adding or altering frequency depe~dent limits and associa.ed condition and action indications.
~ IG. 4 illustrates ~ PSD graph for one channel with four sets of L requency dependent limits used in a .
manner to be described mor~ fully hereinaf*er. The PSD
data is, of cour~e, in digital form so that limit tests can be performed by the computer and ~o that the data may be stored in the mass data file 58 for comparison with a later PSD data to detect significant changes and the rate of changes or trends. The limit tests performed on the PSD
data of a channel will indicate whether particular ~om-ponents are no~al, and if not whether the abnormality merely requires caution or some immediate action. For example 9 at the lower end of the spectrum illustrated in FIG. 4, a firs~ level 61 must be exceeded. Failure to do so may be an indication of some impending failure which will bear watching, ~ut which presents no problem until su~h time. However, a higher limit 62 should-not be exceeded, At any time it is found to be exceeded by an excursion below a level 63, a diagnostic messag~ is displayed indiea~ing ~hat a bad condition is present and indica~ing as ~he action to be taken to inspec* the particular component associated with ~his chann~l, such as a coolant pump, If ~he upp2r limit 63 is exceeded, the condition indicated might be critical and the action indicated might be to check the component immediately.
The next higher frequency range is also provided with three limits. The first, limi~ ~4, i5 S0 low as $~
be normally exceeded throughout, thus indicating that the condition of a related component, such as the pump seals is normal. Should the ne~t level 65 be exceeded, the diagnosis might be an impending failure with appropriate action indicated, such as to check pump seals for leaka~eO The upper limit 65 would indicate a eritical condition with~
the action indicated to replace the seals.
The next frequency range, a narrow rang~, has a lower limit the same as the limit 64 for the p~mp seals, a higher limit the same as the cri~ie~1 limi~ 66 for the pump saals, and a still higher limît equal to the limit 63. This particular frequeney range may be, for example, associa~ed with struc~ur~ mo~ion o~ ~he pump installation such that the level 64 indicates normal ~peration, while the level 66 indica~es some impending failure which would require checking the fan installation~ The higher level would then indicate a mor~ critical condi~ion requiring immediate replacement or repair of the pump s,upport structure.
The balance of the PSD represent~ normal pump noise 60 ~ha~ a lower limi~ 57 i5 provided ~o de~ermine that the pump is in operation. ~he n~xt higher lev~1 68, ~he upper bound Gf normal pump noise, will indicate det~ri-orating pump bearings tha~ will require replacement during . 20 the next scheduled preventive maintenance, particularly if, when compared with a subsequent PSD shown in FIG. 5~
it is seen that this li~it 68 is being exceeded ~y more than in the earlier PSD of FIG. 4. An upper limit 69 indicat~s when ~he condition has become so critical as to require more immediate actionS but diagnostic analysis of the PSD
should require that this level be exceeded during more scanning cycles than just the one indicated at FlG. 5, particularly since the peaX which does exceed that level in the PSD of FIG. 5 is not present throughout the frequency range of the limit 68.
To aid in the diagnosis, any frequency ranga of a PSD may be selected for display on the CRT 35 with the same frequency ranges of previous PSDs as shown in FIG. 5 with the four mos. reoent ones in the foreground and, for example, every other one of earlier PSDs in the background, all in successive order with the most recent at the bottom and each successively earlier one displaced to the righ. ~o provide a pseudo three dimensional display tha~ will quickly show ~he operator any trend. In this case the display indicates the random noise of a pump throughout the range monitored by the level 68 as shown in FI6S~ 4 and 5 and shows ~he growing trend of ~he anomaly shown in FIGS. 4 and 5. The time at which the cri~ical level 69 will be exceeded can be quickly estimated by the operator and - more accurately determined ~y the compu~er, ~s by a sub~
routine called out by ~he operator from a console keyboard-~or a trend analysis~
21.
A trend analysis would be performed by taking data in each of the freauency intervals of a PSD plot used for particular limit analysis and averaging the data over that particular interval for any one scan cycle to ob~ain 5 an average value over that interval that is stored as hîstorical data. The historical data would then be used to perform a trend analysis by taking the averaged value of the sample in any one frequency interval and doing a regression analysis to fit the best trend line to that 0 data. If that trend line shows a significant slope in the way of an increasing or decreasing value over a period of time, it would b~ indicative of a significant trend and would be used to alert the operator to the fac~ tha~ ~he data în the particular interval is showing this trend, and indicate appropriate corrective actio~.
In addition to the use of this automatic monitoring and scanning systlem on nuolear pswer s~ations~ o~her types of power stations, for exampl~ coal~fired power sta~ions, could use ~he sys-tem to equal advantage. The system would be applicable to chemical processes and other industrial applications that use pumps for circulating ~luids, and to po tentially all sorts of other plants . . A refinery, ~or example, would have circulating fluids and pumps 9 and certainly changes in the makeup of these would be of 2~ interestO In a molten salt coal gasifica~ion proc~ss a vibration se~sor on the reaction vessel will be used to obtain a PSD plot and from an analysis of the PSD plot an index of the viscos;ty of the melt in ~he gasifica~ion rig.
That data provides a criteria by which an opera-tor could vary the makeup and discharge of the molten salt as it becomes too viscous to economically pump the mix throu~h.
It w~uld, of course, be possible to provide a closed control loop to maintain viscosity constant. That is well within the state of the art of computer cor.trol ovsr an industrial process. What is new is the automatic scanning of the vibration sensor and obtaining PSD data of the sensor signal for ~nalysis.
In operation, the computer program compares the ~ross amplitude of the PSD si~nal at different frequencies against predetermined limits to detect the normal or abnormal condition of an operating plantO The plant is here illustrated as a nuclear s~eam generating plant for an electrical gener-ator but, as noted hereinbefore, it may be an industrial plant. Normally there are ~o loose parts in a plant, so the output of.the loose parts channel of each vibration sensor is normal:Ly quite low 9 such as near 2ero~ Thus there is inherent in the vibration monitoring and scanning system a capability of de~ecting loose parts quite easilyO What is more difficult is finding potential malfunctions. For that the s~stem relies upon power spectra of vibration and other dynamic signals.-The dynamie signa.l ~rom each s~nsor is comp~sed of many diff~rent mechanical actions or pro~esses goingon within the plant~ mos~ of which have u~ique frequencies ass~ciated with them. The core barrel, for example1 vibrates a~ one frequency while the control rod is so structured as to vibrate a~ som2 o~her frequencyO By pr~-. 23 ~Sf~FD~L
gramming the computer to look at the spectrum of theseevents with respect to just amplitude as a function of frequ~ncy, the condition of each is found separately by looking at unique peaks found in the sensor signal. How~
ever to monitor the core and the rod separately~ it is necessary t3 employ ~ greater level of specification in - measurements. This is done through power spec~ral density measurements taken by connecting the output of the sensor into the signal processor 56 (FIG. 2) for power spectrum analysis. In practice ~he signal processor includes a spectrum analyz~r that is ~ommercially available, such as one based upon a fast Fourier transform algorithm.
The signal proeessor provides in digital form a p~wer measuremenl: which can be plotted in amplitude as function of frequency over whatever range is selected for the ope~ation. By looking at this power spectral density ~PSD) against pr~determined limits, it is possible to reeognize that a specific characteristic frequency may have changed in amplitude to ex~eed predetermined limits or to have chan~ed in frequency. These changes ~ould be at*ribu~ed to, for example, some change in ~he d~mping of a particular part by some structural member breaking, as has occurred in at least one actual plant. There are o~her recognizable factors which cc~uld change the frequency of 25 the sensor signal such ~ha~ the PSD pea3cs would shif~ ei~he:r in ampli*ude or in freque~cy.
To facilita~e analysis oIe potential malfunc~ions by cvmparison of PSDs with frequency dependen~ limi~s~ a baseline PSD is obtained from each sensor signal when i~
is known that the plant is operating normally with all components in good condition. Differen~ PSDs may then be obtai~ed for a given sensor with different possible mal-functions simulated or deliberately introduced momentarily.
Limits can then be set for different frequency ranges and an appropriate actisn stored in the computer in association with each limit. Once this basic information is obtained and s-tor~d in the computer, the operator may alter these limits and/or the associated statements of ac~ion indicated, ~rom experience. If done judiciously, this technique for predicting potential malfunctions can be refined to a very high degree. For example, if ~requency noi~e on a pump bearing indicates a potential malfunction, b~t the level of frequency noise stabilizes, the limits for that pump may be wide~ed, Another source of information useful in deter.min-ing limits, at least at the outset, is the data supplied by the manufacturer of the eomponent parts, such as the various pumps. However, the data thus supplied should be compared a~ainst the actual data after initial installation to ascertain the effect the particular ins~allation may have on the data, particularly the suppor~ing s~ructure.
In any case, the initial setting of limits may be but ~
first step in a learning pr~cess that is aided very signifi-ca~tly by the infallibl~ m~mory of ~he compu~er~
Specifically~ the op~ration of the scanning and `monitoring system is as followsO The computer is ~cheduled in its tasks by a real-t~me clock. A stored executive program directs the comput~r to perform ~arious tasks a~
specifi~d times or timed intervals. Iterativ~ execution of 74~26 this ex~cutive program which calls out subroutines as necessary is the normal mode of operation of the system.
The computer m~y be interrupted from this mode of opera-tion if an abnormal condi~ion is detected in the plant, 5 2S ~y the loose par~s monitoring channels or by the:PSD
analysis channels. In o~her words, the ~xecutive program will periodically respond to the real time clock to cause subroutine to be called out for scanning the sensor signals through the selection matrix 55. Typically there may ~e anywhere~from eight to several hundred signal outputs to be sequentially scanned and processed by t~ signal processor 56~ Each signal scanned may also be record~d on the FM tape recorder, as noted hereinbefore. The signals from these sensors are continually monitored for lGose parts and checked in gross amplitude to determine the presence of any ;malfunction as described he~einb~fore with reference to FIG. 3. The improvement in the scanning and monitoring system resides in analyzing the PSD of each sens~r signal in respect to frequency dependent ampli~ude limits.
The computer 34 controls the signal processor in selec~ing a frequency range over which the spectrum analysis is to be carried out for the particular sensor signal. When ~he spectrum analysis is comple~ed for a givcn signal~
the signal processor interrupts ~he compu~er and ~he com-puter receives ~he PSD in di~i~al form) i.eO, in th~ form of a digital value equal to the scaled amplitude of ~he PSD a~ a function of frequency~ Typically a PSD may înclude 74~26 ~5~
256 equally spaced frequency points, and the amplitude a.
each point is quantized to one part in 1024 for a resolu-tion that is essentially one tenth of one per~ent in amplitude.
This PSD data in digital form is ~hen compared with numerical limits in a ~able, either in the computer memory itself or in the mass data file 58. In either case, the operator can set or alter these limits through a console keyboard 70. Th~ particular family of limits chosen for a particular sensor signal can be typically plotted over 32 discrete intervals covering the PSD. These intervals can have arbitrary beginning and ending points in fr~quency, and for each of these intervals, three limit values may be set. On~ is a low limit which, for example, should be exceeded. Should the PSD being analyzed fall below this limit, a malfunc tion would be indicate~ and a diagnostic m~ssage would be displayed on the CRT 35 and the hard copy device 36 to the effect that the signal has been lost and that operation of some device should be checked, such as "cheek to see if motor No, 3 is on." The next level could be an alert level, that is to say the first degree of operating abnormality. The third level would then be an alarm level which indicates the frequency dependence amplitude o~ the PSD has grossly exceeded normal opera~ing limits. In other frequency interval6, the first (lower) level may be the cau~ion level if exceeded while the next is an abnormal;ty level and the third is an alarm level.
In either case, for each comparis~n level some diagnostic 74~26 informati~n is displayed on the screen of the CRT and the hard copy device.
The message display is in the form of a tabular listing giving channel (sensor number), channel identifica tion 9 the nature o~ the abnormal event that has been de~ected, and the corrective action indicated for the operator to take to either further define the nature oS thé abnormality or to correct the abnormality. The nature of these messages is such that they can be changed if~ in the judgment of the 10 operator, they do not a~equately describe the situation or, it is determined from experience that they do not accurately describ the situation. Thus, as more information is developed about the plant, the message information may be easily ch~nged through the console keyboard jus~ as the limits themselves may be changed.
In prac~tice~ the limits and the.di gnostic informa-tion would be~stored in the computer memory in order to facilitate executing the sequence of instructions necessary to make ~he limit comparisons and sele~t for display the appropriate diagnostic information. However, in the event there is insufficien~ memory in the computer to store all of ~he informa~ion, i~ would be possible ~o store i~ in the mass datA file and to read it into the computer for each channel 2S it is scanned in sequence, as indicated hereinbefore. Thus~ while the signal processor ~6 is carry-ing out ~he necessary compu~a~ions to develop th~ PSD for the channel, ~he ~ompu~er may be reading in~o compu~er memory the ~able of limi~ and diagnos~ic mes~ages for tha~ channel from the mass data file.
~ 9~ ~
In a preferred embodiment the mass data file is also used to store complete PSD scans for all channei~
over a selected interval of from one hour to as much as one year or even more~ It is then possible to retri~ve thls information from the ~ass data file to compare it with the current da~a and thus determine any changes and the rate o~ changes and trends. In practice~ a subroutine to recall this data from the mass data file for this purpose would be under operator control. At any time that an al~rm is indicated, or there is a diagnostic message of a serious nature, th~ operator would be able to call for CRT display in a ps udo three dimensional form as shown in FIG. 6 of a frequency interval of interest in prior PSDs for comparison.
Alternatively~ the operatcr could call for CRT display of only the current PSD with the limits indicated as shown in FIG. 4. Following that, he could ca~l for a particular prior PSD, such as one taken an h~ur ago, to be displayed superimposed over the current PSD so that he may compare the two spectra to determi~e the change which has taken place.
2D He could make sp~cific comparison with successively ~arlier PSDs ~o determine the ra~e of change and the trend, and for a final overview, display all of the prior PSDs wi~h the curren~ one in th~ psPudo ~hre~ dimensiona~ form of ~IG. 6.
The foll~wing flow charts illus~rate ~he more fundamental subroutines ~mployed. All may be readily executed by any scientific computer~ or industrial pr~cess control computer. A computer Model PDP 11 manufactured by Digi~al Equipment Corporation is typical.
74A~6 DAILY SERVICE ROUTINE
.
START
. -~ . . . _ .
~et N=O
. _ r~
Does operator want' koutine for modiflcation to modify cha~nels Yes of table which indicates in service table? ~ -whether channel N is in , ervice~
No .
Routine for modification to modify levels ~ ~of levels for channel N.
. f~r channel N?
~,, .,,, _ .
No opere or wan~ rRoutine for m~dification to modify anAlysis Yes _ ~ of frequency ran~es for fre~uency range~ ~channel ~.
for channel N? - -------------N _o-----_______ o __ . _ N~N ?
No mslx Yes YPS
r--- ~No ate entered in correct ~ormat?
, ~
_ INo e entered in correct ~ormat?
Yes .
ST~P
SCANNING N CHANNEL~
START
~1 ~ ~ ~ No LC h =~
Ye Look up frequency range ~ .
SELECT channel N; start PSD
prooessing; store start time 'Read PSD data into oomputer`
_____ _ 'Enter subroutine COMPARE for~
. channel N (all sets of limi~s) _~
~Compare PSD with frequency`
dependent limits and action statements 1 _~ , Display statements .
,~
Store PSD for channel N in ma~s data file No ~ ~_~
' ~
. Yes .
STOP
3~l The ~aily service rou~tine provides for entering the date and the correct time at the beginnir.g of the first shift of each day. The real-time cl~ck of the computer accepts the time entered as the correct ~ime from which time is thereafter reckoned. At this time the operator has the option to modify the table of channels in service~
to modify the ~est levels for the various channels and/or to msdi~y the frequency ranges for the test levels o~ the various channels.
- Once the daily service routine has been comple~ed~
the operator may initiate the scanning rou-tine from the console. The scanning routine stops when all N channels have been scanned, but is automatically started again at predetermined times, or intervals of time, as set in an P.xecutive routine.
Altho~agh particular embodiments have been dis-closed and described, it should be understood that e~uivalent embodiments and modifications are also contemplated, particu-larly in the respec*s already indicated of automatic analysis of the power spectra of any dynamic signals (time dependent fluctuating signals generally) in any operating plant, and in respect ~o cross correlation of power spe~tra of selected dynamic signals, including the maintenance of a historical file of power spectra in each dyn~mic signal for comparis~n, all for the purpose of finding potential malfunctions, drawing conclusions as to their severity, and indicating ~o ~he opera tor what action to ~ake. Consequen~ly 9 i~ iS intended ~hat the claims be interpreted to cover such modifications and equivalen~s.
Claims (18)
PROPERTY OR PRIVILEGE IS CLAIMED ARE DEFINED AS FOLLOWS:
1. In an operating plant having significant background noise in time dependent fluctuating signals derived from sensors placed at selected points for continually monitoring the operating vibration conditions of system components, a method for scanning in real-time separate signal conditioning channels, one for each of said signals, to find potential malfunctions, draw conclusions as to their severity and indicating to an operator what action to take comprising the steps of:
establishing predetermined sets of vibration frequency dependent limits on the basis of a stored table based upon prior experience as to malfunctions and known characteristic spectra of operating components;
selecting each channel in sequence for spectral analysis;
processing the signal of each channel selected to produce power spectral density data at predetermined frequencies over a predetermined frequency range as a simple Fourier transform;
comparing said power spectral density data of each channel with said established predetermined sets of vibration frequency dependent limits, each set consisting of at least two limits, one for a condition requiring caution and another for an alarm condition requiring more direct action by the operator; and indicating to the operator the condition of plant components associated with each channel and the action to be taken as a function of which set of limits and which limit of the set is exceeded by said power spectral data.
establishing predetermined sets of vibration frequency dependent limits on the basis of a stored table based upon prior experience as to malfunctions and known characteristic spectra of operating components;
selecting each channel in sequence for spectral analysis;
processing the signal of each channel selected to produce power spectral density data at predetermined frequencies over a predetermined frequency range as a simple Fourier transform;
comparing said power spectral density data of each channel with said established predetermined sets of vibration frequency dependent limits, each set consisting of at least two limits, one for a condition requiring caution and another for an alarm condition requiring more direct action by the operator; and indicating to the operator the condition of plant components associated with each channel and the action to be taken as a function of which set of limits and which limit of the set is exceeded by said power spectral data.
2. A method as defined in Claim 1 wherein two paired channels are selected simultaneously in place of a selected single channel, and wherein the step of processing the signal of the paired channels selected is modified to produce cross power spectral density data as a variation on the simple Fourier transform for analysis of the relationship between the paired signals.
3. A method as defined in Claim 2 wherein one of said paired channel signals is a vibration signal from a sensor mounted on a fluid handling component, and the other one of said paired channel signals is a pressure signal from a transducer responsive to the pressure of said fluid.
4. A method as defined in Claim 1 wherein at least one set of frequency dependent limits for a selected channel includes three levels: a first one of which must be exceeded for a normal equipment operating condition to be indicated; a second one of which must be exceeded for an alert condition to be indicated; and a third one of which must be exceeded for an alarm condition to be indicated.
5. A method as defined in Claim 1 wherein at least one set of frequency dependent limits for a selected channel includes three levels: a first one of which must be exceeded for a caution condition to be indicated; a second one of which must be exceeded for an alert condition to be indicated; and a third one of which must be exceeded for an alarm condition to be indicated; said levels thus being spaced apart to indicate different degrees of severity in a potential malfunction and different actions to be taken when exceeded.
6. A method as defined in Claim 1 including the step of storing power spectral density data from each channel in a historical file, and the step of calling up the power spectral density data for a selected channel from at least one prior scan for comparison of power spectral density data derived from a single channel at different times for determining any change.
7. A method as defined in Claim 6 including the step of displaying power spectral density data of selected prior scans for visual comparison.
8. A method as defined in Claim 7 wherein the power spectral data displayed is for only a selected frequency range of interest.
9. A method as defined in Claim 1 including the step of updating said table periodically on the basis of experience since the last time of updating said table.
10. In an operating plant having significant background noise in time dependent fluctuating signals derived from sensors placed at selected points for continually monitoring the operating vibration conditions of system components, apparatus for scanning in real-time separate signal conditioning channels, one for each of said signals, to find potential malfunctions, draw conclusions so as to their severity and indicating to an operator what action to take comprising a computer and including:
means for establishing predetermined sets of vibration frequency dependent limits on the basis of a stored table based upon prior experience as to malfunctions and known characteristic spectra of operating components, computer controlled means for automatically selecting each channel in sequence for power spectrum density analysis;
computer controlled means for automatically processing the signal of each channel selected to produce power spectral density data at predetermined frequencies over a predetermined frequency range as a simple Fourier transform;
means within said computer for automatically comparing said power spectral density data of each channel with said established predetermined sets of vibration frequency dependent limits, each set consisting of at least two limits, one for a condition requiring caution, and another for an alarm condition requiring more direct action by the operator; and computer controlled means for automatically indicating to the operator the condition of plant components associated with each channel and the action to be taken as a function of which set of limits and which limit of the set is exceeded by said power spectral density data.
means for establishing predetermined sets of vibration frequency dependent limits on the basis of a stored table based upon prior experience as to malfunctions and known characteristic spectra of operating components, computer controlled means for automatically selecting each channel in sequence for power spectrum density analysis;
computer controlled means for automatically processing the signal of each channel selected to produce power spectral density data at predetermined frequencies over a predetermined frequency range as a simple Fourier transform;
means within said computer for automatically comparing said power spectral density data of each channel with said established predetermined sets of vibration frequency dependent limits, each set consisting of at least two limits, one for a condition requiring caution, and another for an alarm condition requiring more direct action by the operator; and computer controlled means for automatically indicating to the operator the condition of plant components associated with each channel and the action to be taken as a function of which set of limits and which limit of the set is exceeded by said power spectral density data.
11. Apparatus as defined in Claim 10 wherein said selecting means selects two paired channels simultaneously in place of a selected single channel, and wherein the means for processing the signal of the paired channels selected is modified by said computer to produce cross power spectral density data as a variation on the simple Fourier transform for analysis of the relationship between the paired signals.
12. Apparatus as defined in Claim 11, wherein one of said paired channel signals is a vibration signal from a sensor mounted on a fluid handling component, and the other one of said paired channel signals is a pressure signal from a transducer responsive to the pressure of said fluid.
13. Apparatus as defined in Claim 10 wherein at least one set of frequency dependent limits for a selected channel includes three levels: a first one of which must be exceeded for a normal equipment operating condition to be indicated; a second one of which must be exceeded for an alert condition to be indicated; and a third one of which must be exceeded for an alarm condition to be indicated.
14. Apparatus as defined in Claim 10 wherein at least one set of frequency dependent limits for a selected channel includes three levels: a first one of which must be exceeded for a caution condition to be indicated;
a second one of which must be exceeded for an alert condition to be indicated; and a third one of which must be exceeded for an alarm condition to be indicated; said levels thus being spaced apart to indicate different degrees of severity in a potential malfunction, and different actions to be taken when exceeded.
a second one of which must be exceeded for an alert condition to be indicated; and a third one of which must be exceeded for an alarm condition to be indicated; said levels thus being spaced apart to indicate different degrees of severity in a potential malfunction, and different actions to be taken when exceeded.
15. Apparatus as defined in Claim 10 including means for storing power spectral density data from each channel in a historical file, and means for calling up the power spectral density data for a selected channel from at least one prior scan for comparison of power spectral density data derived from a single channel at different times for determining any change.
16. Apparatus as defined in Claim 15 including means for calling up and displaying power spectral density data of selected prior scans.
17. Apparatus as defined in Claim 16 wherein the power spectral density data displayed is for only a selected frequency range of interest.
18. Apparatus as defined in Claim 10 including a a computer console means for updating said table perio-dically on the basis of experience since the last time of updating said table.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US578,558 | 1975-05-19 | ||
| US05/578,558 US4060716A (en) | 1975-05-19 | 1975-05-19 | Method and apparatus for automatic abnormal events monitor in operating plants |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA1185691A true CA1185691A (en) | 1985-04-16 |
Family
ID=24313382
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA000248995A Expired CA1185691A (en) | 1975-05-19 | 1976-03-29 | Method and apparatus for automatic abnormal events monitor in operating plants |
Country Status (11)
| Country | Link |
|---|---|
| US (1) | US4060716A (en) |
| JP (1) | JPS51141991A (en) |
| BE (1) | BE841575A (en) |
| CA (1) | CA1185691A (en) |
| CH (1) | CH610125A5 (en) |
| DE (1) | DE2622120A1 (en) |
| ES (1) | ES448066A1 (en) |
| FR (1) | FR2312060A1 (en) |
| GB (1) | GB1498372A (en) |
| IT (2) | IT1063688B (en) |
| SE (1) | SE409770B (en) |
Families Citing this family (160)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| USRE31750E (en) * | 1977-11-25 | 1984-11-27 | Ird Mechanalysis, Inc. | Data acquisition system |
| US4184205A (en) * | 1977-11-25 | 1980-01-15 | Ird Mechanalysis, Inc. | Data acquisition system |
| DE2934928C2 (en) * | 1979-08-29 | 1984-03-29 | Siemens AG, 1000 Berlin und 8000 München | Device for permanent monitoring of a part of a plant in operation |
| US4319329A (en) * | 1980-02-21 | 1982-03-09 | Iowa State University Research Foundation, Inc. | Frequency measuring and monitoring apparatus, methods and systems |
| JPS56132594A (en) * | 1980-03-19 | 1981-10-16 | Hitachi Ltd | Monitoring system for grasping core state at accident |
| FR2494877A1 (en) * | 1980-11-26 | 1982-05-28 | Commissariat Energie Atomique | LOGIC SAFETY SYSTEM FOR RELEASING THE PROTECTIVE ACTION OF A SAFETY ACTUATOR |
| US4568514A (en) * | 1981-07-06 | 1986-02-04 | Gamma-Metrics | Fission chamber detector system for monitoring neutron flux in a nuclear reactor over an extra wide range, with high sensitivity in a hostile environment |
| US4477804A (en) * | 1982-03-01 | 1984-10-16 | The Babcock & Wilcox Company | Electrical circuit for providing an abnormal transient display system for nuclear reactor operation |
| HU184537B (en) * | 1982-03-31 | 1984-09-28 | Elektroakusztikai Gyar | Fast fourier-analizator with multiprocessor |
| IT1166509B (en) * | 1982-06-01 | 1987-05-06 | British American Tobacco Co | IMPROVEMENTS RELATED TO MACHINES FOR THE MANUFACTURE OF CIGARETTES |
| US4582672A (en) * | 1982-08-11 | 1986-04-15 | Westinghouse Electric Corp. | Method and apparatus for preventing inadvertent criticality in a nuclear fueled electric powering generating unit |
| JPS5979852A (en) * | 1982-10-29 | 1984-05-09 | Asahi Chem Ind Co Ltd | Apparatus for detecting microscopic destruction |
| DE3305379A1 (en) * | 1983-02-17 | 1984-09-20 | Hochtemperatur-Reaktorbau GmbH, 4600 Dortmund | Method for monitoring the mechanical and thermal operating state of a prestressed concrete pressure vessel of a nuclear power station |
| SE8303785L (en) * | 1983-07-01 | 1985-01-02 | Jan Ludwik Liszka | SYSTEM FOR OPERATING CONTROL OF A MACHINE |
| GB2149551B (en) * | 1983-11-07 | 1988-08-17 | Eel Limited | Apparatus for monitoring the operation of a system |
| GB2156520B (en) * | 1984-03-27 | 1987-08-19 | Trade & Industry Secretary Of | Monitoring of process steps |
| AT390516B (en) * | 1985-02-14 | 1990-05-25 | Vasipari Kutato Fejleszto | METHOD FOR CONTROLLING A HETEROGENIC DIFFUSION-KINETIC CONVERSION PROCESS IN A TURBULENT LIQUID FLOW |
| US4820059A (en) * | 1985-10-30 | 1989-04-11 | Central Institute For The Deaf | Speech processing apparatus and methods |
| EP0243479A4 (en) * | 1985-10-30 | 1989-12-13 | Central Inst Deaf | Speech processing apparatus and methods. |
| US4744242A (en) * | 1986-09-16 | 1988-05-17 | The Boeing Company | Method for monitoring cutting tool wear during a machining operation |
| FR2605170A1 (en) * | 1986-10-09 | 1988-04-15 | Letailleur Bernard | Method and installation for monitoring the progressive wear of machines |
| US5005142A (en) * | 1987-01-30 | 1991-04-02 | Westinghouse Electric Corp. | Smart sensor system for diagnostic monitoring |
| US4783307A (en) * | 1987-03-05 | 1988-11-08 | Commonwealth Edison Company | Reactor control system verification |
| DE3734487A1 (en) * | 1987-10-12 | 1989-04-20 | Grs Ges Reaktorsicherheit | Method for monitoring the reliable mode of operation and for the early detection of damage in complicated technical systems |
| US4935195A (en) * | 1988-08-29 | 1990-06-19 | Westinghouse Electric Corp. | Corrosion-erosion trend monitoring and diagnostic system |
| US4961898A (en) * | 1988-08-30 | 1990-10-09 | Westinghouse Electric Corp. | Reactor internals and core support monitoring system |
| US4957690A (en) * | 1988-12-07 | 1990-09-18 | General Electric Company | System and method for monitoring and control of safety-related components of a nuclear power plant |
| US5001346A (en) * | 1990-02-26 | 1991-03-19 | Rockwell International Corporation | Leak detection system with background compensation |
| US5237518A (en) * | 1990-10-27 | 1993-08-17 | Vanderbilt University | Optimization method for adaptive sensor reading scheduling and delayed alarm evaluation in real-time diagnostic systems |
| JP3128832B2 (en) * | 1991-01-23 | 2001-01-29 | 株式会社日立製作所 | Plant diagnostic apparatus and plant diagnostic method |
| US5203188A (en) * | 1991-09-16 | 1993-04-20 | Morgan Construction Company | System and method for monitoring a rolling mill |
| CH686378A5 (en) * | 1992-10-12 | 1996-03-15 | Rieter Ag Maschf | Machine Management System. |
| US5410492A (en) * | 1992-01-29 | 1995-04-25 | Arch Development Corporation | Processing data base information having nonwhite noise |
| US5459675A (en) * | 1992-01-29 | 1995-10-17 | Arch Development Corporation | System for monitoring an industrial process and determining sensor status |
| JP3278452B2 (en) * | 1992-04-01 | 2002-04-30 | 株式会社東芝 | Adjustment support device for connecting the rotating body |
| JP2973726B2 (en) * | 1992-08-31 | 1999-11-08 | 株式会社日立製作所 | Information processing device |
| FR2698470B1 (en) * | 1992-11-26 | 1995-02-10 | Kodak Pathe | Method and installation for continuous and real-time monitoring of a complex manufacturing process. |
| US5790413A (en) * | 1993-03-22 | 1998-08-04 | Exxon Chemical Patents Inc. | Plant parameter detection by monitoring of power spectral densities |
| JP3169036B2 (en) * | 1993-06-04 | 2001-05-21 | 株式会社日立製作所 | Plant monitoring and diagnosis system, plant monitoring and diagnosis method, and nondestructive inspection and diagnosis method |
| US5989190A (en) * | 1994-01-27 | 1999-11-23 | Mizur Technology, Ltd. | Passive sensor system using ultrasonic energy |
| US5625150A (en) * | 1994-08-18 | 1997-04-29 | General Electric Company | Integrated acoustic leak detection sensor subsystem |
| US5846056A (en) * | 1995-04-07 | 1998-12-08 | Dhindsa; Jasbir S. | Reciprocating pump system and method for operating same |
| US5847658A (en) * | 1995-08-15 | 1998-12-08 | Omron Corporation | Vibration monitor and monitoring method |
| US5761090A (en) * | 1995-10-10 | 1998-06-02 | The University Of Chicago | Expert system for testing industrial processes and determining sensor status |
| CN1110728C (en) * | 1995-12-06 | 2003-06-04 | 霍尼韦尔公司 | Method of predicative maintenance of a process control system having fluid movement |
| AU719783B2 (en) * | 1995-12-06 | 2000-05-18 | Honeywell Inc. | A method of predictive maintenance of a process control system having fluid movement |
| US5963884A (en) * | 1996-09-23 | 1999-10-05 | Machine Xpert, Llc | Predictive maintenance system |
| GB2323197B (en) * | 1997-03-13 | 1999-02-10 | Intelligent Applic Ltd | A monitoring system |
| US5955855A (en) * | 1997-04-09 | 1999-09-21 | Medar, Inc. | Method and system for tuning a drive to its coupled motor to minimize motor resonance and sensing device for use therein |
| US5975854A (en) * | 1997-05-09 | 1999-11-02 | Copeland Corporation | Compressor with protection module |
| SE9703450L (en) * | 1997-09-24 | 1999-03-25 | Sca Graphic Sundsvall Ab | Methods and apparatus for process monitoring |
| US5800331A (en) * | 1997-10-01 | 1998-09-01 | Song; Jin Y. | Imbalance detection and rotor identification system |
| US6505145B1 (en) * | 1999-02-22 | 2003-01-07 | Northeast Equipment Inc. | Apparatus and method for monitoring and maintaining plant equipment |
| US6505475B1 (en) | 1999-08-20 | 2003-01-14 | Hudson Technologies Inc. | Method and apparatus for measuring and improving efficiency in refrigeration systems |
| US6302654B1 (en) * | 2000-02-29 | 2001-10-16 | Copeland Corporation | Compressor with control and protection system |
| US6752165B2 (en) | 2000-03-08 | 2004-06-22 | J & L Fiber Services, Inc. | Refiner control method and system |
| US6502774B1 (en) | 2000-03-08 | 2003-01-07 | J + L Fiber Services, Inc. | Refiner disk sensor and sensor refiner disk |
| US6778936B2 (en) | 2000-03-08 | 2004-08-17 | J & L Fiber Services, Inc. | Consistency determining method and system |
| US6957172B2 (en) | 2000-03-09 | 2005-10-18 | Smartsignal Corporation | Complex signal decomposition and modeling |
| US7739096B2 (en) * | 2000-03-09 | 2010-06-15 | Smartsignal Corporation | System for extraction of representative data for training of adaptive process monitoring equipment |
| US6973794B2 (en) | 2000-03-14 | 2005-12-13 | Hussmann Corporation | Refrigeration system and method of operating the same |
| US7000422B2 (en) | 2000-03-14 | 2006-02-21 | Hussmann Corporation | Refrigeration system and method of configuring the same |
| US6332327B1 (en) | 2000-03-14 | 2001-12-25 | Hussmann Corporation | Distributed intelligence control for commercial refrigeration |
| US6647735B2 (en) | 2000-03-14 | 2003-11-18 | Hussmann Corporation | Distributed intelligence control for commercial refrigeration |
| US7047753B2 (en) | 2000-03-14 | 2006-05-23 | Hussmann Corporation | Refrigeration system and method of operating the same |
| US6999996B2 (en) * | 2000-03-14 | 2006-02-14 | Hussmann Corporation | Communication network and method of communicating data on the same |
| US6768969B1 (en) * | 2000-04-03 | 2004-07-27 | Flint Hills Scientific, L.L.C. | Method, computer program, and system for automated real-time signal analysis for detection, quantification, and prediction of signal changes |
| US6350224B1 (en) * | 2000-07-17 | 2002-02-26 | Westinghouse Savannah River Company, Llc | Centrifugal unbalance detection system |
| US6556939B1 (en) | 2000-11-22 | 2003-04-29 | Smartsignal Corporation | Inferential signal generator for instrumented equipment and processes |
| US7233886B2 (en) * | 2001-01-19 | 2007-06-19 | Smartsignal Corporation | Adaptive modeling of changed states in predictive condition monitoring |
| US6938843B2 (en) | 2001-03-06 | 2005-09-06 | J & L Fiber Services, Inc. | Refiner control method and system |
| US7539597B2 (en) | 2001-04-10 | 2009-05-26 | Smartsignal Corporation | Diagnostic systems and methods for predictive condition monitoring |
| US6668240B2 (en) | 2001-05-03 | 2003-12-23 | Emerson Retail Services Inc. | Food quality and safety model for refrigerated food |
| US6892546B2 (en) | 2001-05-03 | 2005-05-17 | Emerson Retail Services, Inc. | System for remote refrigeration monitoring and diagnostics |
| US6845161B2 (en) * | 2001-05-21 | 2005-01-18 | Hewlett-Packard Development Company, L.P. | System and method for performing acoustic analysis of devices |
| US6975962B2 (en) | 2001-06-11 | 2005-12-13 | Smartsignal Corporation | Residual signal alert generation for condition monitoring using approximated SPRT distribution |
| US6770032B2 (en) | 2001-12-03 | 2004-08-03 | Microsense Cardiovascular Systems 1996 | Passive ultrasonic sensors, methods and systems for their use |
| US6889173B2 (en) * | 2002-10-31 | 2005-05-03 | Emerson Retail Services Inc. | System for monitoring optimal equipment operating parameters |
| US6933693B2 (en) * | 2002-11-08 | 2005-08-23 | Eaton Corporation | Method and apparatus of detecting disturbances in a centrifugal pump |
| US6826513B1 (en) * | 2002-11-29 | 2004-11-30 | Council Of Scientific & Industrial Research | Method and apparatus for online identification of safe operation and advance detection of unsafe operation of a system or process |
| US6990432B1 (en) | 2003-04-04 | 2006-01-24 | General Electric Company | Apparatus and method for performing gas turbine adjustment |
| MXPA06002197A (en) | 2003-08-25 | 2006-05-22 | Computer Process Controls Inc | Refrigeration control system. |
| US7104480B2 (en) * | 2004-03-23 | 2006-09-12 | J&L Fiber Services, Inc. | Refiner sensor and coupling arrangement |
| US7412842B2 (en) | 2004-04-27 | 2008-08-19 | Emerson Climate Technologies, Inc. | Compressor diagnostic and protection system |
| US7359831B2 (en) * | 2004-05-21 | 2008-04-15 | Bea Systems, Inc. | Diagnostic context |
| US7379849B2 (en) * | 2004-05-21 | 2008-05-27 | Bea Systems, Inc. | Diagnostic image |
| US8490064B2 (en) * | 2004-05-21 | 2013-07-16 | Oracle International Corporation | Hierarchical debug |
| US7376534B2 (en) * | 2004-05-21 | 2008-05-20 | Bea Systems, Inc. | Watches and notifications |
| US7395458B2 (en) * | 2004-05-21 | 2008-07-01 | Bea Systems, Inc. | Diagnostic instrumentation |
| US7275377B2 (en) | 2004-08-11 | 2007-10-02 | Lawrence Kates | Method and apparatus for monitoring refrigerant-cycle systems |
| US7567887B2 (en) * | 2004-09-10 | 2009-07-28 | Exxonmobil Research And Engineering Company | Application of abnormal event detection technology to fluidized catalytic cracking unit |
| US20060174164A1 (en) * | 2005-02-01 | 2006-08-03 | General Electric Company | Methods, systems, and computer program products for implementing condition monitoring activities |
| EP1851959B1 (en) | 2005-02-21 | 2012-04-11 | Computer Process Controls, Inc. | Enterprise control and monitoring system |
| JP2006252229A (en) * | 2005-03-11 | 2006-09-21 | Nec Electronics Corp | Abnormality detection system and abnormality detection method |
| JP2006277523A (en) * | 2005-03-30 | 2006-10-12 | Nec Electronics Corp | Abnormality detection system and abnormality detecting method |
| US8718937B2 (en) * | 2005-09-28 | 2014-05-06 | Honeywell International Inc. | Methods and apparatus for real time position surveying using inertial navigation |
| US7752853B2 (en) | 2005-10-21 | 2010-07-13 | Emerson Retail Services, Inc. | Monitoring refrigerant in a refrigeration system |
| US7752854B2 (en) | 2005-10-21 | 2010-07-13 | Emerson Retail Services, Inc. | Monitoring a condenser in a refrigeration system |
| US7665315B2 (en) | 2005-10-21 | 2010-02-23 | Emerson Retail Services, Inc. | Proofing a refrigeration system operating state |
| US7594407B2 (en) | 2005-10-21 | 2009-09-29 | Emerson Climate Technologies, Inc. | Monitoring refrigerant in a refrigeration system |
| US7596959B2 (en) | 2005-10-21 | 2009-10-06 | Emerson Retail Services, Inc. | Monitoring compressor performance in a refrigeration system |
| US8190251B2 (en) * | 2006-03-24 | 2012-05-29 | Medtronic, Inc. | Method and apparatus for the treatment of movement disorders |
| US8165683B2 (en) * | 2006-04-21 | 2012-04-24 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US7764989B2 (en) * | 2006-04-21 | 2010-07-27 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US7761145B2 (en) * | 2006-04-21 | 2010-07-20 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US20070249956A1 (en) * | 2006-04-21 | 2007-10-25 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US20070249953A1 (en) * | 2006-04-21 | 2007-10-25 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US7761146B2 (en) * | 2006-04-21 | 2010-07-20 | Medtronic, Inc. | Method and apparatus for detection of nervous system disorders |
| US7720641B2 (en) * | 2006-04-21 | 2010-05-18 | Exxonmobil Research And Engineering Company | Application of abnormal event detection technology to delayed coking unit |
| US8590325B2 (en) | 2006-07-19 | 2013-11-26 | Emerson Climate Technologies, Inc. | Protection and diagnostic module for a refrigeration system |
| JP4634347B2 (en) * | 2006-08-14 | 2011-02-16 | 三菱重工業株式会社 | Moderator temperature coefficient measuring device, measuring method and measuring program thereof |
| US20080216494A1 (en) | 2006-09-07 | 2008-09-11 | Pham Hung M | Compressor data module |
| US8275577B2 (en) | 2006-09-19 | 2012-09-25 | Smartsignal Corporation | Kernel-based method for detecting boiler tube leaks |
| US8311774B2 (en) | 2006-12-15 | 2012-11-13 | Smartsignal Corporation | Robust distance measures for on-line monitoring |
| KR100946637B1 (en) | 2006-12-29 | 2010-03-09 | 한국원자력연구원 | Abnormal simulation signal analysis methods for 4~20mA instrumental system |
| US7895475B2 (en) * | 2007-07-11 | 2011-02-22 | Oracle International Corporation | System and method for providing an instrumentation service using dye injection and filtering in a SIP application server environment |
| US20090037142A1 (en) | 2007-07-30 | 2009-02-05 | Lawrence Kates | Portable method and apparatus for monitoring refrigerant-cycle systems |
| US8393169B2 (en) | 2007-09-19 | 2013-03-12 | Emerson Climate Technologies, Inc. | Refrigeration monitoring system and method |
| US8160827B2 (en) | 2007-11-02 | 2012-04-17 | Emerson Climate Technologies, Inc. | Compressor sensor module |
| US9140728B2 (en) | 2007-11-02 | 2015-09-22 | Emerson Climate Technologies, Inc. | Compressor sensor module |
| US9618037B2 (en) | 2008-08-01 | 2017-04-11 | Honeywell International Inc. | Apparatus and method for identifying health indicators for rolling element bearings |
| US8958995B2 (en) | 2009-04-02 | 2015-02-17 | Honeywell International Inc. | System and method for monitoring rotating and reciprocating machinery |
| CN102449606B (en) * | 2009-05-29 | 2015-01-21 | 爱默生零售服务公司 | System and method for monitoring and evaluating equipment operating parameter modifications |
| US9500553B2 (en) * | 2009-11-09 | 2016-11-22 | Kulite Semiconductor Products, Inc. | Systems and methods for improved dynamic pressure measurements |
| US20110112814A1 (en) * | 2009-11-11 | 2011-05-12 | Emerson Retail Services, Inc. | Refrigerant leak detection system and method |
| US8862250B2 (en) | 2010-05-07 | 2014-10-14 | Exxonmobil Research And Engineering Company | Integrated expert system for identifying abnormal events in an industrial plant |
| KR101046300B1 (en) * | 2010-10-08 | 2011-07-04 | 중앙대학교 산학협력단 | Method and system for safety management of gas charging facility |
| WO2012118830A2 (en) | 2011-02-28 | 2012-09-07 | Arensmeier Jeffrey N | Residential solutions hvac monitoring and diagnosis |
| US9256224B2 (en) | 2011-07-19 | 2016-02-09 | GE Intelligent Platforms, Inc | Method of sequential kernel regression modeling for forecasting and prognostics |
| US8620853B2 (en) | 2011-07-19 | 2013-12-31 | Smartsignal Corporation | Monitoring method using kernel regression modeling with pattern sequences |
| US9250625B2 (en) | 2011-07-19 | 2016-02-02 | Ge Intelligent Platforms, Inc. | System of sequential kernel regression modeling for forecasting and prognostics |
| US8964338B2 (en) | 2012-01-11 | 2015-02-24 | Emerson Climate Technologies, Inc. | System and method for compressor motor protection |
| US8963733B2 (en) * | 2012-02-13 | 2015-02-24 | Honeywell International Inc. | System and method for blind fault detection for rotating machinery |
| US9480177B2 (en) | 2012-07-27 | 2016-10-25 | Emerson Climate Technologies, Inc. | Compressor protection module |
| US9255578B2 (en) | 2012-07-31 | 2016-02-09 | Fisher-Rosemount Systems, Inc. | Systems and methods to monitor pump cavitation |
| US9310439B2 (en) | 2012-09-25 | 2016-04-12 | Emerson Climate Technologies, Inc. | Compressor having a control and diagnostic module |
| US9803902B2 (en) | 2013-03-15 | 2017-10-31 | Emerson Climate Technologies, Inc. | System for refrigerant charge verification using two condenser coil temperatures |
| US9551504B2 (en) | 2013-03-15 | 2017-01-24 | Emerson Electric Co. | HVAC system remote monitoring and diagnosis |
| WO2014144446A1 (en) | 2013-03-15 | 2014-09-18 | Emerson Electric Co. | Hvac system remote monitoring and diagnosis |
| AU2014248049B2 (en) | 2013-04-05 | 2018-06-07 | Emerson Climate Technologies, Inc. | Heat-pump system with refrigerant charge diagnostics |
| CN105683852B (en) | 2013-09-06 | 2018-04-10 | 通用电气智能平台有限公司 | Apparatus and method for model adaptation |
| JP2015108530A (en) * | 2013-12-04 | 2015-06-11 | 株式会社東芝 | Nuclear reactor output stability monitoring apparatus and nuclear reactor output stability monitoring method |
| CN106062373B (en) * | 2014-03-05 | 2017-10-24 | 富世华股份有限公司 | Pump device for water management |
| WO2015134753A1 (en) | 2014-03-07 | 2015-09-11 | Ubiquiti Networks, Inc. | Cloud device identification and authentication |
| WO2016003862A1 (en) | 2014-06-30 | 2016-01-07 | Ubiquiti Networks, Inc. | Methods and tools for assisting in the configuration of a wireless radio network using functional maps |
| CN105874839B (en) | 2014-08-31 | 2019-11-15 | 优倍快网络公司 | Method and apparatus for monitoring and improving wireless network health |
| CN104700909B (en) * | 2014-12-31 | 2017-07-28 | 大亚湾核电运营管理有限责任公司 | Nuclear power plant's group's heap security system |
| US11774944B2 (en) | 2016-05-09 | 2023-10-03 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for the industrial internet of things |
| US20180284758A1 (en) | 2016-05-09 | 2018-10-04 | StrongForce IoT Portfolio 2016, LLC | Methods and systems for industrial internet of things data collection for equipment analysis in an upstream oil and gas environment |
| US11327475B2 (en) | 2016-05-09 | 2022-05-10 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for intelligent collection and analysis of vehicle data |
| CN107330994B (en) * | 2017-06-30 | 2019-11-26 | 联想(北京)有限公司 | The switching moment acquisition methods and electronic equipment of operating status |
| US11442445B2 (en) | 2017-08-02 | 2022-09-13 | Strong Force Iot Portfolio 2016, Llc | Data collection systems and methods with alternate routing of input channels |
| KR102103143B1 (en) * | 2018-03-14 | 2020-04-22 | (주)아이티공간 | Predictive maintenance method of driving device |
| CN110444301B (en) * | 2019-08-13 | 2022-07-01 | 中国核动力研究设计院 | Experimental device and experimental method for simulating supercritical pressure transient working condition |
| DE102020130861A1 (en) | 2020-11-23 | 2022-05-25 | Christian Sojka | visual system |
| US11791059B2 (en) * | 2021-02-24 | 2023-10-17 | Westinghouse Electric Company Llc | System for continually monitoring the condition of nuclear reactor internals |
| US20220341316A1 (en) * | 2021-04-26 | 2022-10-27 | Schlumberger Technology Corporation | Automated configuration of telemetry transmission |
| CN115446662B (en) * | 2022-07-22 | 2023-10-10 | 湖南工业大学 | Cutter vibration signal processing method based on CEEMDAN-IFTC-PSR |
| CN115862276B (en) * | 2022-11-22 | 2023-11-03 | 江苏中烟工业有限责任公司 | Water cooling system early warning method, device, equipment and medium applied to cigarette making machine set |
| CN116402136B (en) * | 2023-03-22 | 2023-11-17 | 中航信移动科技有限公司 | Rule extraction method based on offline data, storage medium and electronic equipment |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3324458A (en) * | 1964-05-18 | 1967-06-06 | Bunker Ramo | Monitoring apparatus |
| US3400374A (en) * | 1965-06-16 | 1968-09-03 | Robertshaw Controls Co | Computerized control systems |
| US3778347A (en) * | 1971-09-27 | 1973-12-11 | Giras T | Method and system for operating a boiling water reactor-steam turbine plant preferably under digital computer control |
| US3753852A (en) * | 1971-12-10 | 1973-08-21 | C Scott | Ultrasonic system for monitoring vibrations in a nuclear reactor |
| US3809870A (en) * | 1972-06-08 | 1974-05-07 | Gleason Works | Method and apparatus for monitoring condition of cutting blades |
| DE2241553A1 (en) * | 1972-08-24 | 1974-02-28 | Daimler Benz Ag | DEVICE FOR DETECTION AND LOCATION OF FAULTS ON MACHINE ELEMENTS EQUIPPED WITH ROTATING PARTS, IN PARTICULAR VEHICLE ASSEMBLIES |
| US3860480A (en) * | 1973-01-29 | 1975-01-14 | Westinghouse Electric Corp | Reactor core component vibration monitro |
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1975
- 1975-05-19 US US05/578,558 patent/US4060716A/en not_active Expired - Lifetime
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1976
- 1976-03-29 GB GB12509/76A patent/GB1498372A/en not_active Expired
- 1976-03-29 CA CA000248995A patent/CA1185691A/en not_active Expired
- 1976-04-26 SE SE7604766A patent/SE409770B/en unknown
- 1976-05-03 IT IT49303/76A patent/IT1063688B/en active
- 1976-05-05 IT IT7649301Q patent/IT1073704B/en active
- 1976-05-07 FR FR7613869A patent/FR2312060A1/en active Granted
- 1976-05-07 BE BE166831A patent/BE841575A/en not_active IP Right Cessation
- 1976-05-18 DE DE19762622120 patent/DE2622120A1/en not_active Ceased
- 1976-05-18 JP JP51057184A patent/JPS51141991A/en active Pending
- 1976-05-18 CH CH620976A patent/CH610125A5/xx not_active IP Right Cessation
- 1976-05-19 ES ES448066A patent/ES448066A1/en not_active Expired
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| JPS51141991A (en) | 1976-12-07 |
| ES448066A1 (en) | 1977-07-01 |
| FR2312060B1 (en) | 1982-10-22 |
| IT1063688B (en) | 1985-02-11 |
| BE841575A (en) | 1976-09-01 |
| US4060716A (en) | 1977-11-29 |
| DE2622120A1 (en) | 1976-12-02 |
| GB1498372A (en) | 1978-01-18 |
| FR2312060A1 (en) | 1976-12-17 |
| SE409770B (en) | 1979-09-03 |
| IT1073704B (en) | 1985-04-17 |
| CH610125A5 (en) | 1979-03-30 |
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