GB2122749A - Electrical condition monitoring of electric motors - Google Patents
Electrical condition monitoring of electric motors Download PDFInfo
- Publication number
- GB2122749A GB2122749A GB08217582A GB8217582A GB2122749A GB 2122749 A GB2122749 A GB 2122749A GB 08217582 A GB08217582 A GB 08217582A GB 8217582 A GB8217582 A GB 8217582A GB 2122749 A GB2122749 A GB 2122749A
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- United Kingdom
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- samples
- statistical
- condition
- statistical moment
- line
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
- Tests Of Circuit Breakers, Generators, And Electric Motors (AREA)
Abstract
Methods and apparatus for monitoring the condition of an electrically driven motor by sampling one line quantity to the motor, typically current (I), calculating statistical moments, such as mean, standard deviation, skew or kurtosis, from a number of the sampled waveforms (18), comparing the calculated values with reference values (20) for a motor in good condition and applying significance testing (19) to the comparison. The motor condition can thus be monitored automatically and without the need for visual comparison of "current" waveform spectra. This procedure can follow pulse height analysis (16) and Fourier analysis (12), in which latter case (13) corresponds to (18) in the former case and (14, 15) correspond to (19, 20), the results being displayed at (25). <IMAGE>
Description
SPECIFICATION
Electrical condition monitoring of electric motors
This invention relates to methods and apparatus for electrically monitoring the condition of electric motors.
Condition monitoring of electrical drives is an important aid to the prevention of expensive plant breakdowns since it provides warning of incipient failure. At present vibration or noise techniques are used to monitor most mechanical defects in electrical drives. The majority of these defects are associated with rolling-element bearings and special techniques have been developed to monitor them; the most significant being acoustic emission monitoring, shock pulse monitoring and the kurtosis method. One vibration analysis technique uses an accelerometer operated over its linear response range to provide an electrical signal proportional to acceleration. This signal is passed through a spectrum analyser, enabling frequency components corresponding to various vibration sources to be identified. Changes in the spectrum indicate wear effects and possibly incipient failure.A variant of this technique, known as demodulated resonance analysis, or envelope detection, uses the natural resonance frequency of a transducer to highlight high frequency signals produced by flaws in rolling-element bearings. In acoustic emission monitoring, high frequency vibration produced by bearings is analysed to monitor condition. This method is very effective since high frequency signals are influenced by bearing defects. Vibration monitoring techniques, however, require access to the motor for the location of the transducer, which is disadvantageous in certain circumstances, such as in remote applications, for example in mines, or in submersibles, for example submersible sewage pumps, or in hazardous environments.
According to one aspect of the present invention there is provided a method of monitoring the electrical and/or mechanical condition of an electrically driven motor connected to an electrical power supply by a line, including the steps of monitoring one line electrical quantity, storing samples of the monitored line quantity, calculating at least one statistical moment from a number of said samples, comparing the calculated statistical moment with reference statistical moment for a motor in a first condition, and applying significance testing to the comparison whereby to determine the occurrence of significant changes in the machine's condition.
According to another aspect of the present invention there is provided an apparatus for use in monitoring the electrical and/or mechanical condition of an electrically driven motor connected to an electrical power supply by a line, comprising an input transducer for monitoring one line electrical quantity; means for sampling and storing samples of the monitored line quantity; first means for calculating at least one statistical moment from a number of said samples; first means for comparing the calculated statistical moment with a respective reference statistical moment for a machine in a first condition, and first means for applying a significance testing to the comparison whereby to determine the occurrence of significant changes in the machine's condition.
Embodiments of the present invention will now be described with reference to the accompanying drawings, in which
Fig. 1 shows a basic power sensing circuit based on that described in our co-pending
Application No. 811181 5; Fig. 2 shows schematically part of the signal processing of a condition monitoring apparatus according to the present invention, and
Fig. 3 shows schematically pulse height signal processing for use in Fig. 2.
In our co-pending Patent Application No.
8111815 (Serial No. ) (M. E. Steele-G.
F. Barker 3-1) there is described a method of condition monitoring which involves harmonic power analysis. Mechanical noise/vibrations and other effects in an electrical motor, such as a pump drive, are related to peaks in the electrical input power spectrum of the motor. Similarly,
bearing friction loss is related to the electrical input power spectrum. The noise/vibration and other effects in the motor dissipate power, with components at certain dominant frequencies, in addition to the main supply of power absorbed directly in driving the shaft of the motor against a steady load. Measurement of the electrical spectra at the input to the motor can provide an
indication of the mechanical/noise spectra.
Our Application No.8111815 employed the frequency spectrum of the input power to produce a frequency spectrum piot. To do this it is
necessary to measure the instantaneous power dissipation, or produce a signal which is proportional to the instantaneous power, and apply this signal to a spectrum analyser. One
phase of a basic power sensing circuit, based on that described in Application No. 8111 81 5, is shown in Fig. 1. A line amplifier A, 'floats' at the
line potential Vph and produces a differential voltage output proportional to the line current I from current monitoring resistors R1 and R2.The commamode (line voltage) and differential (line
current) outputs from A, are divided down, by
resistors R3, R4 and R5, R6, and applied to the
inputs of an amplifier A2. Amplifier A2 provides
gain compensation for the line current (differential)
signal divider reduction. In addition, a differential (VPhVref) phase voltage is produced by an
amplifier A3. Vref will usually be the neutral or
common point. The voltages from A2 and A3 are
then multipled electronically by multiplier M1 to
produce an instantaneous power signal which can
be processed by a spectrum analyser S1 attached
via a metering/display circuit 2 to either phase
power output (P) or the sum of the phases (P), as produced by a summing amplifier A4.The
phase current iand phase voltage v are also applied to the metering/display circuit 2, which may provide scaling and digital display, with options of average/r.m.s. and linear dB values. The spectrum analyser may comprise an FFT (Fast
Fourier Transform) spectrum analyser with a frequency range of O to 20 kHz.
If the supply voltage is constant and has a low source impedance, it is sufficient to monitor the "current" signal only, that is monitor the output of amplifier A2. In which case for three phase systems only one phase should be monitored in order to avoid the cancellation effects which would occur in monitoring a balanced system whereas in some instances a record of the spectrum analysis of the "current" signal may be interpreted visually, in other cases where, for example, the record shows a large number of harmonics or sidebands, it may be difficult if not impossible to interpret visually. It is sometimes possible to simplify the record pattern by further signal processing, such as by taking the logarithm of the spectrum and performing a Fourier analysis on the resuit to obtain a cepstrum.The cepstrum has the effect of separating the sidebands from the source spectrum or differentiating between sets of harmonics or sidebands.
In order to facilitate electrical condition monitoring of electrical motors, the present invention aims to provide an instrument which can analyse fluctuations, due to electrical and mechanical motor defects, in one line quantity, typically the supply current to the motor, and then make comparisons with reference results obtained from a motor in good condition in order to automatically indicate the relative condition of a motor being monitored.
With reference to Fig. 2, in a monitoring instrument of the present invention a voltage signal proportional to the current drawn by a motor and load combination is derived from an input transducer 10, which may, for example, be a monitoring resistance, a Hall probe or a current transformer. Instead of employing a spectrum analyser to determine and display the power spectrum as described above, the signal from the input transducer 10 is passed to a sampling and storage unit 11, comprising part of a computing system of the instrument and including analogue to digital converters, a signal processer and appropriate memory facility, where an appropriate time length of the current is sampled, digitised and stored as a "current" waveform.For periodic or almost periodic waveforms coherent sampling may be effected by an external synchronising signal or from a selected feature of the current waveform.
Fourier analysis is then carried out, at element 12, on a sample of the stored "current" waveform. This may be effected by the signal processor, or a microprocessor, using an efficient algorithm for the analysis, such as an FFT. The resulting spectrum is expanded about a designated frequency, or "zoomed", also at element 12.
Statistical moments relative to the current waveform amplitude are then calculated, at element 13, for selected frequencies, for example, from a number of the samples which have been
Fourier analysed at element 1 2. The moments calculated are mean; variance and standard deviation; skew; and kurtosis. These statistical parameters are compared, at element 14, with stored (at element 15) reference statistical parameters for the motor/load combination in good or new condition and a significance test calculation employed to determine if there are any significant changes in condition of the motor/load combination.
On the sampled and stored "current" waveform, stored at unit 11, pulse height analysis is also performed, as indicated at element 1 6. For this purpose the stored signal is first high-pass filtered, as at element 1 7 (Fig. 3), to remove any d.c. component and low frequency, for example rotational frequency, components. Statistical moments in the time domain are then calculated at element 1 8. The statistical moments calculated are mean; standard deviation; skew; and kurtosis.
The r.m.s. value of the signal may also be calculated. Comparison with reference statistical data, stored in element 20, and significance testing is then performed at element 1 9 (Fig. 1) as described above with reference to the Fourier analysed signal samples.
A threshold value, proportional to a "spread" parameter of the processed signal, for example, the standard deviation or the r.m.s. value, is evaluated at element 21, and a new waveform containing only signal levels in excess of the threshold value is constructed at element 22.
Statistical moments for this new waveform are calculated at element 23, as before, and Fourier analysis of the new waveform is performed at element 24, as described previously at element 1 2. Significance testing of the statistical moments calculated at 23 and obtained from subsequent statistical moment calculation from the Fourier analysed samples (at 24) is performed similarly to that described above.
- Ali ofthe four described significance tests results may be displayed on a readout 25, although in Fig. 2 only two are shown connected thereto. The readout may be a digital display, particularly for portable condition monitoring instruments, giving values of the statistical moments calculated 9r, for example, indicating by "flashing" or an audible aiarm if a significant result is obtained. A strip-chart recorder and printer 26 may be employed to display "observed" histograms and spectra and enable comparison with stored histograms and spectra, and to print details of the calculated statistical moments and significance tests, if required.
Reference data for a particular motor-load combination can be stored in the memory of the instrument or pre-ioaded into the memory of the instrument from a data link or tape recorder. The actual reference data selected can be determined from an external knowledge of the average speed prevailing or by analysing the current test data to deduce average speed and load conditions and then select the reference data automatically.
The instrument described above can be used on a portable instrument or numbers of such instruments can be permanently installed for monitoring numbers of motors. The information outputs from each individual instrument such as spectra, histograms and statistics can be fed back to a central computer via a data link for further signal analysis and processing. Such a hierarchial system enables on-site inspection with more sophisticated central computer back-up and serveillance.
Alternatively, multiplexed systems can be implemented in which only the input transducers and the storage and sampling units of the current waveform are sited at the monitoring points and are connected via a multiplexed data link to the main computing part of the instrument, which is sited at a central control point.
Apart from the input transducer the practical implementation of the condition monitoring system need involve only digital electronics and micro and signal processor technology. Such a system or instrument may be employed to detect, for example, defective bearings, broken rotor bars, missing or damaged gear teeth, out-of-balance loads, coupling/shaft alignments, pump impeller/fan faults, all without the necessity of stripping the machine concerned down, removing it from its operating position or even stopping the functioning of the machine during testing. This is particularly beneficial for motors in remote or hazardous applications such as in mines or submerged.
Whereas the above-described method involves the calculation of four different statistical moments, since motor condition changes may affect any of them, any one or any combination of these statistical moments may be utilised in practical embodiments of the present invention.
Claims (14)
1. A method of monitoring the electrical and/or mechanical condition of an electrically driven motor connected to an electrical power supply by a line, including the steps of monitoring one line electrical quantity, storing samples of the monitored line quantity, calculating at least one statistical moment from a number of said samples, comparing the calculated statistical moment with reference statistical moment for a motor in a first condition, and applying significance testing to the comparison whereby to determine the occurrence of significant changes in the machine's condition.
2. A method as claimed in claim 1, wherein the line quantity is the motor supply current.
3. A method as claimed in claim 2,-wherein the samples are stored in digital form, wherein in a first computation process a number of the stored samples are Fourier analysed prior to calculation of statistical moments therefrom, and wherein the calculation of statistical moments step comprises calculation of a first set of statistical moments
relative to the current waveform amplitude for
selected frequencies.
4. A method as claimed in claim 2 or claim 3,
wherein the samples are stored in digital form,
wherein in a second computation process a
number of the stored samples are high pass
filtered prior to calculation of statistical moments,
comprising a second set of statistical moments,
therefrom in the time domain and subsequently
subjected to significance testing.
5. A method as claimed in claim 4, wherein a
threshold value proportional to a spread
parameter of the samples processed in the
second computation process is evaluated, and
wherein a second current waveform containing
only signal levels in excess of the threshold value
is constructed.
6. A method as claimed in claim 5, wherein in a
third computation process a third set of statistical
moments are calculated for the second current
waveform and subsequently subjected to
significance testing.
7. A method as claimed in claim 5 or claim 6,
wherein in a fourth computation process the second
current waveform is Fourier analysed prior calculation of a fourth set of statistical moments
therefrom, which moments are subsequently
subjected to significance testing.
8. A method as claimed in any one of the
preceding claims wherein the results of the or
each significance test are digitally displayed on
readout means.
9. A method as claimed in any one of the
preceding claims, wherein the statistical
moments comprise mean; variance and standard
deviation; skew; and kurtosis.
10. Apparatus for use in monitoring the
electrical and/or mechanical condition of an
electrically driven motor connected to an
electrical power supply by a line, comprising an
input transducer for monitoring one line electrical
quantity; means for sampling and storing samples
of the monitored line quantity; first means for
calculating at least one statistical moment from a -number of said samples; first means for
comparing the calculated statistical moment with
a respective reference statistical moment for a
machine in a first condition, and first means for
applying significance testing to the comparison
whereby to determine the occurrence of
significant changes in the machine's condition.
1 Apparatus as claimed in claim 10, wherein
the samples are stored in the sampling and
storing means in digitised form, and including
means to Fourier analyse the stored samples prior
to application to the first means for calculating
the statistical moment.
12. Apparatus as claimed in claim 10 or claim
1 1, further including a high pass filter, second
means for calculating at least one statistical
moment from a number of said samples after
filtering by said high pass filter, second means for
comparing the second means calculated
statistical moment with a respective reference
statistical moment for a machine in a first condition, and second means for applying significance testing to the second means comparison whereby to determine the occurrence of significant changes in the machine's condition.
13. Apparatus as claimed in claim 12, including means to evaluate a threshold value proportion to a spread parameter of the samples processed by the second statistical moment calculating means and to construct a second line quantity waveform containing only signal levels in excess of the threshold value.
14. Apparatus as claimed in claim 13, including third means for calculating at least one statistical moment from the second line quantity waveform and third means for applying significance testing to the thus calculated statistical moment.
1 5. Apparatus as claimed in claim 13, including means to Fourier analyse the second line quantity waveform, fourth means for calculating at least one statistical moment from the Fourier analysed second line quantity waveform and fourth means for applying significance testing to the thus calculated statistical moment.
1 6. Apparatus as claimed in any one of claims 10 to 15, including readout means for displaying the results obtained from the or each means for applying significance testing.
1 7. Apparatus as claimed in claim 10 and arranged to monitor the condition of a plurality of electrically driven motors connected to a respective electrical power supply by a respective line, including a plurality of input transducers and respective means for sampling and storing samples of each respective monitored line quantity, and including a multiplexed data link whereby the plurality of sampling and storage means can be connected in turn to the first means for calculating the at least one statistical moment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB08217582A GB2122749B (en) | 1982-06-17 | 1982-06-17 | Electrical condition monitoring of electric motors |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB08217582A GB2122749B (en) | 1982-06-17 | 1982-06-17 | Electrical condition monitoring of electric motors |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB2122749A true GB2122749A (en) | 1984-01-18 |
| GB2122749B GB2122749B (en) | 1985-07-10 |
Family
ID=10531110
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| GB08217582A Expired GB2122749B (en) | 1982-06-17 | 1982-06-17 | Electrical condition monitoring of electric motors |
Country Status (1)
| Country | Link |
|---|---|
| GB (1) | GB2122749B (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0229719A2 (en) * | 1986-01-17 | 1987-07-22 | Westinghouse Electric Corporation | Diagnostic apparatus for an electric generator seal oil system |
| EP0240684A1 (en) * | 1986-03-10 | 1987-10-14 | Siemens Aktiengesellschaft | Arrangement for the managerial electronic processing of operational data of an electric motor |
| DE3617452A1 (en) * | 1986-05-23 | 1987-11-26 | Klein Schanzlin & Becker Ag | Method for monitoring an asynchronous machine |
| EP0392367A2 (en) * | 1989-04-11 | 1990-10-17 | Mitsubishi Denki Kabushiki Kaisha | Load state decision apparatus of servomotor |
| WO1991006872A1 (en) * | 1989-10-24 | 1991-05-16 | Robert Bosch Gmbh | Procedure for testing generators |
| EP0462050A1 (en) * | 1990-06-12 | 1991-12-18 | Saia Ag | Method and circuit for detecting the drop from synchronism of a stepper or synchronous motor |
| FR2683049A1 (en) * | 1991-10-23 | 1993-04-30 | Laborde Kupfer Repelec | Method for detecting defects in a rotating electrical machine |
| US6023228A (en) * | 1995-11-30 | 2000-02-08 | Siemens Aktiengesellschaft | Method and apparatus for checking electrical drive mechanisms |
| WO2002007301A1 (en) * | 2000-07-13 | 2002-01-24 | Saia-Burgess Gmbh | Loss of step detection by means of frequency spectrum analysis |
| CN101303393B (en) * | 2007-05-08 | 2011-01-05 | 鸿富锦精密工业（深圳）有限公司 | Monitoring system and monitoring method of motor operation |
| WO2012131159A1 (en) * | 2011-04-01 | 2012-10-04 | Kone Corporation | Method for monitoring operating condition of an elevator system and an elevator system |
| FR3003037A1 (en) * | 2013-03-05 | 2014-09-12 | Electricite De France | METHOD FOR DETECTING A SHORT CIRCUIT FAULT IN WINDINGS OF A ROTOR OF A ROTATING ELECTRIC MACHINE |
| WO2017208051A1 (en) * | 2016-05-29 | 2017-12-07 | Aplisens S.A. | Method for diagnosing technical condition of submersible pump unit |
| WO2019034343A1 (en) * | 2017-08-17 | 2019-02-21 | Robert Bosch Gmbh | Method for detecting a malfunction of an electric machine |
| CN114487826A (en) * | 2022-02-14 | 2022-05-13 | 爱科赛智能科技(浙江)有限公司 | Motor starting locked rotor detection method based on current kurtosis |
-
1982
- 1982-06-17 GB GB08217582A patent/GB2122749B/en not_active Expired
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0229719A2 (en) * | 1986-01-17 | 1987-07-22 | Westinghouse Electric Corporation | Diagnostic apparatus for an electric generator seal oil system |
| EP0229719A3 (en) * | 1986-01-17 | 1988-09-21 | Westinghouse Electric Corporation | Diagnostic apparatus for an electric generator seal oil system |
| EP0240684A1 (en) * | 1986-03-10 | 1987-10-14 | Siemens Aktiengesellschaft | Arrangement for the managerial electronic processing of operational data of an electric motor |
| DE3617452A1 (en) * | 1986-05-23 | 1987-11-26 | Klein Schanzlin & Becker Ag | Method for monitoring an asynchronous machine |
| EP0392367A2 (en) * | 1989-04-11 | 1990-10-17 | Mitsubishi Denki Kabushiki Kaisha | Load state decision apparatus of servomotor |
| EP0392367A3 (en) * | 1989-04-11 | 1991-09-11 | Mitsubishi Denki Kabushiki Kaisha | Load state decision apparatus of servomotor |
| WO1991006872A1 (en) * | 1989-10-24 | 1991-05-16 | Robert Bosch Gmbh | Procedure for testing generators |
| EP0462050A1 (en) * | 1990-06-12 | 1991-12-18 | Saia Ag | Method and circuit for detecting the drop from synchronism of a stepper or synchronous motor |
| CH680547A5 (en) * | 1990-06-12 | 1992-09-15 | Saia Ag | |
| FR2683049A1 (en) * | 1991-10-23 | 1993-04-30 | Laborde Kupfer Repelec | Method for detecting defects in a rotating electrical machine |
| US6023228A (en) * | 1995-11-30 | 2000-02-08 | Siemens Aktiengesellschaft | Method and apparatus for checking electrical drive mechanisms |
| WO2002007301A1 (en) * | 2000-07-13 | 2002-01-24 | Saia-Burgess Gmbh | Loss of step detection by means of frequency spectrum analysis |
| CN101303393B (en) * | 2007-05-08 | 2011-01-05 | 鸿富锦精密工业（深圳）有限公司 | Monitoring system and monitoring method of motor operation |
| WO2012131159A1 (en) * | 2011-04-01 | 2012-10-04 | Kone Corporation | Method for monitoring operating condition of an elevator system and an elevator system |
| EP2694416A4 (en) * | 2011-04-01 | 2015-03-04 | Kone Corp | Method for monitoring operating condition of an elevator system and an elevator system |
| FR3003037A1 (en) * | 2013-03-05 | 2014-09-12 | Electricite De France | METHOD FOR DETECTING A SHORT CIRCUIT FAULT IN WINDINGS OF A ROTOR OF A ROTATING ELECTRIC MACHINE |
| WO2014135785A3 (en) * | 2013-03-05 | 2014-11-20 | Electricite De France | Method for detecting a short-circuit fault in the windings of a rotor of a rotating electric machine |
| WO2017208051A1 (en) * | 2016-05-29 | 2017-12-07 | Aplisens S.A. | Method for diagnosing technical condition of submersible pump unit |
| WO2019034343A1 (en) * | 2017-08-17 | 2019-02-21 | Robert Bosch Gmbh | Method for detecting a malfunction of an electric machine |
| CN110945373A (en) * | 2017-08-17 | 2020-03-31 | 罗伯特·博世有限公司 | Method for detecting a fault state of an electric machine |
| US11269010B2 (en) | 2017-08-17 | 2022-03-08 | Robert Bosch Gmbh | Method for detecting a malfunction state of an electric machine |
| CN114487826A (en) * | 2022-02-14 | 2022-05-13 | 爱科赛智能科技(浙江)有限公司 | Motor starting locked rotor detection method based on current kurtosis |
Also Published As
| Publication number | Publication date |
|---|---|
| GB2122749B (en) | 1985-07-10 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PCNP | Patent ceased through non-payment of renewal fee |