CN1111285C - Expert diagnostic method for fault of dc. motor - Google Patents
Expert diagnostic method for fault of dc. motor Download PDFInfo
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- CN1111285C CN1111285C CN 97120280 CN97120280A CN1111285C CN 1111285 C CN1111285 C CN 1111285C CN 97120280 CN97120280 CN 97120280 CN 97120280 A CN97120280 A CN 97120280A CN 1111285 C CN1111285 C CN 1111285C
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Abstract
The present invention discloses an expert diagnostic method for DC motor faults, which is mainly realized by a data acquisition part and a fault diagnosis part, wherein a diagnosis system can be divided into an on-site diagnosis system (a near-end computer) and a remote diagnosis system (a far-end computer); remote communication which is composed of modems and telephone lines is adopted for the connection between the on-site diagnosis system and the remote diagnosis system so as to realize remote diagnosis. The knowledge of the method of the present invention adopts a production rule expression method; the inner structure of the expression method is composed of a repository, an inference machine, an integrated database, a knowledge acquisition (KA) program, an interpreter program, a man-machine interface, etc.; the present invention can carry out the on-line data acquisition, the state monitoring, the fault diagnosis, the technical calculation, the standard query, the data display and the data recording of DC motors. The present invention has notable economic effect by being applied to industries.
Description
Technical field:
The present invention relates to a kind of direct current generator expert diagnostic method for fault, specifically adopt computing machine direct current generator to be carried out the method for operational factor and state parameter collection, supervision and fault diagnosis etc. by image data and expertise.
Background technology:
Japan " Toshiba's comment " magazine 1987 № 5 " Toshiba's large-sized DC motor diagnosis expert system " literary composition discloses a kind of direct current generator expert diagnostic method for fault.It adopts TOShiBAC-7/70 type control computer and MYEXPERT-II " shell " also is system development tool, is somebody's turn to do " shell " application drawing list processing language LISP-7, establishes inference machine, knowledge base and database.The narration of inferenctial knowledge has three kinds: historical romance inference, inductive inference and definite countermeasure.Knowledge base is transplanted knowledge network according to the MYEXPERT-II knowledge base editor and is constituted.The status data that the motor of collecting according to monitoring system moves is input to inference machine by the MYEXPERT-II interface.This expert system can commutate and the fault diagnosis of coil and the judgement of unusual moment of torsion to direct current generator, amounts to 40 kinds.Comprise this expert system, present both at home and abroad direct current generator method for diagnosing faults, the subject matter of existence is that function is few, and checkup item is single or only several, and diagnostic reliability needs further to improve, and can not carry out remote diagnosis.
Summary of the invention:
The purpose of this invention is to provide a kind of can be to the various types of 91 kinds of diagnosing malfunctions of direct current generator, motor is carried out presence monitor, and can calculate and realize the direct current generator expert diagnostic method for fault of remote fault diagnosis electromagnetic parameter, commutating parameter and the insulation life of motor.
The object of the present invention is achieved like this.
A kind of direct current generator expert diagnostic method for fault adopts computing machine and system development tool, and functional module comprises inference machine, knowledge base, database, and system development tool adopts the Exsys expert system, and diagnostic procedure is as follows:
1) data acquisition: record relevant commutation spark, insulation resistance, vibration, temperature, humidity class state parameter signal and record electric current, voltage, rotating speed class operating parameter signal from electrical control cubicles by being installed in sensor in the motor;
2) signal shows and data processing: graphoscope shows the sample mode picture, and immediate status parameter and time domain waveform are reported to the police when state parameter transfinites automatically, and can carry out data processing to state parameter as required;
3) artificial input information: by the out of Memory of user interface with artificial conversational mode input dc power machine fault diagnosis needs;
4) state recognition and fault diagnosis: computing machine calls its inner functional module various states is discerned according to various status informations, realizes commutation, insulation, vibration or torsional oscillation Fault Diagnosis to direct current generator, makes explanations.
In the gatherer process of described vibration parameters, after the vibration signal that vibration-measuring sensor is recorded excludes direct current and photoelectricity isolation processing, enter the high-speed data acquisition plate.
The collection of described insulation resistance parameter is carried out under the motor stopped status with offline mode, to the detection of the polarization index PI of insulation resistance.
Described torsional oscillation failure diagnostic process is: the typical torsional oscillation collection of illustrative plates of storing in motor torsional oscillation domain waveform actual time that write down and the knowledge base functional module is contrasted, manually import sign, system can draw diagnostic result; By further dynamic analysis, the moment enlargement factor (TAF) when calculating torsional oscillation is determined its harmfulness.
Store the calculating formula collection in the described knowledge base functional module, after the user interface input rating of electric machine, performance parameter, member and main geometric, can commutation ability parameter, the electromagnetic parameter of motor be calculated, after the input operational factor, can calculate the insulation life of motor.
Described computing machine is the near-end computing machine, with state parameter and operational factor that data acquisition obtains, is transferred to far-end computer by the near-end computing machine, realizes remote fault diagnosis and status surveillance.
The advantage that the present invention is compared with prior art had is: utilize data acquisition to obtain diagnosis required status information and operation information, it is required but can't directly import the failure message and the sign of computing machine by sensor and data acquisition to carry out man-machine conversation input dc power machine fault diagnosis by man-machine interface, for diagnosis provides more detailed and definite data, sign and foundation, improved the confidence level and the hit rate of diagnosis.Automatic warning function when immediate status parameter and time domain waveform show and state parameter transfinites; realized the presence of motor is monitored, can the early detection failure symptom, in time promptly fault is made diagnosis; reduce the incidence of force outage, reduce maintenance cost.What particularly this method realized calculates and remote fault diagnosis motor electromagnetic parameter, commutating parameter and insulation life, can satisfy the needs of field maintemance and high one deck secondary device management simultaneously.
Description of drawings:
Fig. 1 is system's composition diagram of the inventive method.
Fig. 2 is the vibration detection schematic diagram of the inventive method.
Fig. 3 is that the voltage input parameter of the inventive method detects schematic diagram.
Fig. 4 is the temperature detection schematic diagram of the inventive method.
Fig. 5 is the Humidity Detection schematic diagram of the inventive method.
Fig. 6 is that the insulation resistance of the inventive method detects schematic diagram.
Fig. 7 is the software connection layout of the inventive method.
Fig. 8 is the integrated figure of the user interface of the inventive method.
Fig. 9 is the fault diagnosis flowsheet of the inventive method.
Figure 10 is the technique computes flowsheet of the inventive method.
Embodiment:
Below in conjunction with accompanying drawing embodiments of the invention are done further to discuss.
System's composition diagram of the inventive method, see Fig. 1, mainly the detecting unit by the last detected state that is installed in each position of direct current generator also is that sensor 1, electrical control cubicles 2, data collector 3, near-end computing machine 4, far-end computer 5 and the telecommunication 6 that detects motor operating parameter are formed.Sensor 1, electrical control cubicles 2 and data collector 3 are the equipment that obtains immediate status parameter and operational factor, and according to principle of work, its formation can be divided into sensor and transmitter, conversion of signals and processing and three ingredients of power-supply system.Its main body is a modular data acquisition system (DAS) (Micro DAC), and temperature detection, current detecting, commutation spark detection, insulation resistance detection etc. all constitute a detecting unit, and each detecting unit is controlled by a standalone module in the system.The gatherer process of signal is as follows: the various operational factors of on-the-spot motor in service and state parameter signal, through sensor, mutual inductor, transmitter and other pick-up units are sent into each corresponding detection module, module is at first done filtering according to different signals with it, buffering, conditioning, pre-service such as amplification, then signal is done the V/F conversion, pulse signal after will changing is again made the photoelectricity isolation processing, digital quantity signal after the photoelectricity isolation processing is sent to the buffer zone of the controller (Micro DAC Controller) of data collector and deposits, and waits for that the near-end computing machine comes reading of data.Data type comprises: instant sampled data, one-minute average Value Data, five minutes average datas, one minute maximum value data, five minutes maximum value datas, root-mean-square value data.
Data collector 3 carries out data communication with near-end computing machine 4 in the RS422 mode, is connected by a four-core shielded cable or two pairs of twisted-pair feeders between the two.Data collector 3 carries out data acquisition according to the sampling instruction of computing machine, by communication interface data is sent to near-end computing machine 4.
Near-end computing machine 4 is the systems with complete fault diagnosis functions, is made up of main frame, keyboard, mouse, CRT, printer.Main frame dominant frequency 90MHZ, internal memory 16MB, hard disk 1000MB are furnished with 3.5 inches floppy disks, 4 times of fast CD-ROM, and sound card, look the configuration of multimedia such as card; Inner structure partly is made up of database, inference machine, knowledge acquisition, data acquisition, fault handling and user interface etc.Far-end computer 5 is positioned at several kilometers diagnosis room in addition of distance field, has identical soft or hard, part configuration, structure, function and mode of operation with near-end computing machine 4.The telecommunication 6 that near-end computing machine 4 adopts OPTIMA144 type modulator-demodular unit and telephone wire to form is carried out communication with far-end computer 5, will be by the state parameter and the operational factor of data collector 3 acquisitions, be transferred to far-end computer in the data file mode, realize remote fault diagnosis and status surveillance.
Fig. 2 is the vibration detection schematic diagram of the inventive method.Its data collector mainly is made up of vibration-measuring sensor 7, transmitter 8, analog quantity photoelectric isolation module 9 and high-speed data acquisition plate 10.After connecting the 220V AC power supplies, transmitter 8 at first provides DC24V working power for the vibration-measuring sensor 7 that is installed on the motor shaft bearing.When bear vibration, sensitive element in the sensor 7 bears vibration and produces voltage signal, this voltage signal and vibrational waveform are identical, it is through impedance variation and amplify the back by sensor 7 outputs, through transmitter 8 input interface input transducers 8, this moment, the level at transmitter 8 input interface terminals was actually the alternating voltage signal (vibration signal) that superposeed on the DC24V.Transmitter 8 input interfaces and output interface occur with parallel form, but an isolation capacitance is arranged between them, and therefore the signal of exporting on the output interface of transmitter 8 has been isolated flip-flop, being and exchanging level signal, i.e. vibration signal of output.This vibration signal is sent into analog quantity photoelectric isolation module 9 and is made photoelectricity and isolate, and the signal after the isolation is sent into high-speed data acquisition plate 10, after the A/D conversion, stored digital signal is waited in the buffer zone of Micro DAC controller that computing machine takes data away again.Computing machine then according to the demand of diagnosis, is taken these data away in the mode of sampling command file regulation, in computing machine these data is handled.
The voltage input parameter of data collector detects principle in the inventive method, sees Fig. 3.The voltage input parameter is the standard d. c. voltage signal of obtaining from electrical control cubicles, directly enter corresponding simulating amount DC voltage load module 11, after process filtering and buffering, amplification, V/F conversion, photoelectricity are isolated in module 11, deposit in the buffer zone of input Micro DAC controller, the wait computing machine is taken data away.This class signal also has: commutation spark, armature supply, rotating speed, exciting current etc.
The temperature detection principle of data collector in the inventive method, as shown in Figure 4.Motor temperature element 12 passes through input plug socket 13 signal input temp detection module 14 in the three-wire system mode, after process filtering and buffering, amplification, V/F conversion, photoelectricity are isolated in module, deposit in the buffer zone of input Micro DAC controller, the wait computing machine is taken data away.
The Humidity Detection principle of data collector in the inventive method, as shown in Figure 5.Humidity sensor 15 is capacitors very responsive to humidity, and temperature sensor 16 is platinum resistance, and they are exported signal by transmitter 17 and 18 separately. Transmitter 17 and 18 usefulness DC24V power supply, output signal are 4～20mA electric currents.Output signal directly is delivered to two electric current load modules 19 and 20, and module carries out depositing in the buffer zone of input Micro DAC controller after filtering and buffering, amplification, V/F conversion, photoelectricity isolates to signal, waits for that computing machine takes data away.
The insulation resistance of the inventive method data collector detects principle, as shown in Figure 6.The collection of the polarization index PI of insulation resistance is carried out with offline mode, promptly detects and must carry out under the motor stopped status.Insulation tester table 24 is proven transistor meggers.When detecting after direct supply and the supply of insulation detection power supply, computing machine sends insulation and detects instruction, switching value output module 21 outputs one switching value of Micro DAC, the relay coil loop of engage relay 22, make relay 22 and 23 adhesives, the electric power loop of insulation tester table 24 and measurement loop are connected simultaneously.Begin with the 1000V nominal voltage when arriving 60 seconds,, will to detect data and to input to Micro DAC controller, the record insulating resistance value by voltage load module 25 to the motor main circuit detection of insulating; Measurement is proceeded, and when arriving 10 minutes, insulating resistance value when writing down 10 minutes calculates the ratio of 10 minutes insulating resistance values and 1 minute insulating resistance value again, is the polarization index PI of insulation resistance.When computer recording behind 10 minutes measured values, output immediately stops the sampling instruction, this moment, the output of switching value module 21 terminating switch amounts made relay 22 and 23 dead electricity, insulation tester table 24 quits work, and opens simultaneously and measure the loop, detects and finishes.
The diagnostic work process of direct current generator expert diagnostic method for fault of the present invention is as follows:
1) data acquisition: according to the needs of checkup item, the sampling instruction that computing machine sends, after data collector is gathered according to the mode of sampling instruction appointment, deposit data the buffer zone of data collector in, be transferred to the near-end computing machine by communication interface with data communication method then;
2) signal shows and data processing: show the sample mode picture on the near-end graphoscope, immediate status parameter and time domain waveform, when transfiniting, state parameter reports to the police automatically, also can carry out data processing to state parameter as required, as the root-mean-square value of calculated load electric current, vibration signal is carried out fft analysis;
3) artificial input information: some required information of direct current generator fault diagnosis can't directly be imported computing machine by sensor and data collector, as commutator epithelium state, insulation variable color and peculiar smell, brush wear and breakage, information such as the bright trace of commutator, need to import with artificial conversational mode, provide more detailed and definite data and foundation for fault diagnosis in proper order by user interface.The artificial input data is indispensable in the diagnosis;
4) state recognition and fault diagnosis: computing machine is according to the various status informations of input, call its inner functional module such as inference machine, knowledge base, database etc., various states are discerned, realization is to commutation, insulation, vibration or the torsional oscillation Fault Diagnosis of direct current generator, making explanations comprises failure cause and handling suggestion etc., and is printed as diagnosis report output;
Store the calculating formula collection in the knowledge base functional module, after the user interface input rating of electric machine, performance parameter, member and main geometric, can commutation ability parameter, the electromagnetic parameter of motor be calculated, after the input operational factor, can calculate that result's report is calculated or calculated in printout to the insulation life of motor;
The near-end computing machine can be as required, the state parameter and the operational factor that will obtain by data collector, by modulator-demodular unit and telephone wire, be transferred to far-end computer in the data file mode, far-end computer carries out state recognition and fault diagnosis in the mode identical with the near-end computing machine, realizes remote fault diagnosis and status surveillance.Can call the calculating formula collection of storing in the knowledge base functional module own equally, carry out technique computes and deduction, result's report is calculated or is calculated in printout.
Fig. 7 is the software connection layout of the inventive method.Wherein Windows-95 is a running program, Visual Basic is the language edit tool, Win Word6.0 shows and the file Chinese software, Dems-SKB is the application software of knowledge base etc., Vborog is with (comprise compress and non-compression) application software for data acquisition, Dems Main is the master of a system application software, comprises all application software such as data acquisition, fault diagnosis, technique computes, data foundation, knowledge base, and Exsys is system development tool and 27 knowledge bases that have whole planning.Select the Exsys expert system develoment tool, form motor commutation, insulation, vibration, torsional oscillation fault diagnosis knowledge base.Because the composition of the knowledge base of Exsys expert system develoment tool, inference machine planning is to use the method for production rule, the complex process of artificial intelligence expert system will be set up, be simplified to process by man-machine conversation input knowledge and experience, and can revise easily, edit the knowledge base rule by man-machine conversation, solve reliability, the maintainability of knowledge base and made things convenient for problems such as additions and deletions.So motor commutation, insulation, vibration, torsional oscillation Fault Diagnosis, " the relevant determining method of supporting ", " classification fault scalping method ", " the Permanent fault waiting line approach " and " overlapping weighting support determining method " that can adopt the expert of the art when carrying out fault diagnosis, to use always respectively, make when diagnosis in the face of many influence factors, can make real reason outstanding, other reason is not then moved back in back burner because of confidence level is high, obviously determines failure cause.
The probability of all faults all adopts following algebraic expression to calculate:
1-[(1-probable value 1) * (1-probable value 2)]=final probable value
Said system software moves under the above version software environment of DOS6.0.
The inventive method is finally finished by user interface.Fig. 8 is the integrated figure of the user interface of the inventive method.The packetized file menu is the repertoire control module of expert diagnostic method for fault of the present invention, and the portrait of functions such as data acquisition, fault diagnosis, technique computes is arranged on the picture.In elected during arbitrary function portrait, system enters institute immediately and chooses function window under and move.Under arbitrary function window, can continue to open as required one deck window down, carry out next step function.No matter system moves under any function, and each picture is all clearly indicated selectable content and project.
Diagnostic procedure adopts the man-machine conversation interactive diagnosis, computing machine is pointed out various possible failure causes and relevant factor, and the operator can select by the information of oneself grasping, and inapt information can not answered, no matter any selection of operator, diagnosis can both be made by system.But diagnostic result is in detail relevant with order of accuarcy with operator's input information.Input information is detailed, accurate, and diagnostic result confidence level and hit rate are just high; Input information is imprecise or seldom, diagnosis is just fuzzy slightly.
There are a large amount of pictures, program and file in system, also has a lot of diagnostic results, result of calculation in the operating process, gathers the various parameters of motor and the standard that inquires, and all these can both come out with printer prints.
Above-mentioned user interface is utilized menu-drive, mainly makes mouse-based operation, and is simple to operate, easy to use, window clear layer, picture easy to understand.
As an example, Fig. 9 is the fault diagnosis flowsheet of the inventive method, and Figure 10 is the technique computes flowsheet of the inventive method.
Claims (6)
1. a direct current generator expert diagnostic method for fault adopts computing machine and system development tool, and functional module comprises inference machine, knowledge base, database, it is characterized in that system development tool adopts the Exsys expert system, and diagnostic procedure is as follows:
1) data acquisition: record relevant commutation spark, insulation resistance, vibration, temperature, humidity class state parameter signal by the sensor that is installed in the motor, and record electric current, voltage, rotating speed class operating parameter signal from electrical control cubicles;
2) signal shows and data processing: graphoscope shows the sample mode picture, and immediate status parameter and time domain waveform are reported to the police when state parameter transfinites automatically, and can carry out data processing to state parameter as required;
3) artificial input information: by the out of Memory of user interface with artificial conversational mode input dc power machine fault diagnosis needs;
4) state recognition and fault diagnosis: computing machine calls its inner functional module various states is discerned according to various status informations, realizes commutation, insulation, vibration or torsional oscillation Fault Diagnosis to direct current generator, makes explanations.
2. method according to claim 1 is characterized in that in the gatherer process of described vibration parameters, after the vibration signal that vibration-measuring sensor is recorded excludes direct current and photoelectricity isolation processing, enters the high-speed data acquisition plate.
3. method according to claim 1 is characterized in that the collection of described insulation resistance parameter is carried out under the motor stopped status with offline mode, to the detection of the polarization index PI of insulation resistance.
4. method according to claim 1, it is characterized in that described torsional oscillation failure diagnostic process is: the typical torsional oscillation collection of illustrative plates of storing in motor torsional oscillation domain waveform actual time that write down and the knowledge base functional module is contrasted, artificial input sign, system can draw diagnostic result; By further dynamic analysis, the moment enlargement factor (TAF) when calculating torsional oscillation is determined its harmfulness.
5. method according to claim 1, it is characterized in that storing the calculating formula collection in the described knowledge base functional module, after the user interface input rating of electric machine, performance parameter, member and main geometric, can commutation ability parameter, the electromagnetic parameter of motor be calculated, after the input operational factor, can calculate the insulation life of motor.
6. method according to claim 1 is characterized in that described computing machine is the near-end computing machine, with state parameter and operational factor that data acquisition obtains, is transferred to far-end computer by the near-end computing machine, realizes remote fault diagnosis and status surveillance.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 97120280 CN1111285C (en) | 1997-11-12 | 1997-11-12 | Expert diagnostic method for fault of dc. motor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 97120280 CN1111285C (en) | 1997-11-12 | 1997-11-12 | Expert diagnostic method for fault of dc. motor |
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| Publication Number | Publication Date |
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| CN1217473A CN1217473A (en) | 1999-05-26 |
| CN1111285C true CN1111285C (en) | 2003-06-11 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN 97120280 Expired - Fee Related CN1111285C (en) | 1997-11-12 | 1997-11-12 | Expert diagnostic method for fault of dc. motor |
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| CN (1) | CN1111285C (en) |
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| DE102007033152A1 (en) * | 2007-07-13 | 2009-01-15 | Robert Bosch Gmbh | For the diagnosis of a direct current motor, it runs as a generator during the diagnosis time for the induced voltage to be analyzed for faults |
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| CN110618384A (en) * | 2019-10-25 | 2019-12-27 | 四川诚邦浩然测控技术有限公司 | Motor performance test platform |
| CN111766516B (en) * | 2020-07-14 | 2023-02-28 | 北京经纬恒润科技股份有限公司 | Direct current motor parameter calibration method and device |
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1997
- 1997-11-12 CN CN 97120280 patent/CN1111285C/en not_active Expired - Fee Related
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