Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals

A. Alwodai, Y. Shao, X. Yuan, M. Ahmed, F. Gu, A. D. Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Motor current signature analysis (MCSA) is a common practice in industry for finding motor faults. However, because of small modulations caused by faults and high noise contamination, it is difficult to quantify the modulation in measured signals which is dominated by the supply frequency, higher order harmonics and noise. In this paper a modulation signal bispectrum (MSB) is investigated to detect stator winding faults. This type of fault can cause high winding temperatures which may effect on current signal so motor temperature will be considered in this paper. The results show that MSB has the capability to accurately estimate modulation degrees and suppress the random and non-modulation components. The test results show that MSB has a better performance in differentiating spectrum amplitudes due to stator faults, and hence produces better diagnosis performance, compared with that of conventional power spectrum analysis.

Original languageEnglish
Title of host publicationICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing
Subtitle of host publicationFuture Energy and Automation
PublisherIEEE Computer Society
Pages197-202
Number of pages6
ISBN (Print)9781908549082
Publication statusPublished - 14 Sep 2013
Event19th International Conference on Automation and Computing - London, United Kingdom
Duration: 13 Sep 201314 Sep 2013
Conference number: 19

Conference

Conference19th International Conference on Automation and Computing
Abbreviated titleICAC 2013
CountryUnited Kingdom
CityLondon
Period13/09/1314/09/13

Fingerprint

Signal analysis
Short circuit currents
Modulation
Stators
Power spectrum
Spectrum analysis
Contamination
Temperature
Industry

Cite this

Alwodai, A., Shao, Y., Yuan, X., Ahmed, M., Gu, F., & Ball, A. D. (2013). Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals. In ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation (pp. 197-202). [6662037] IEEE Computer Society.
Alwodai, A. ; Shao, Y. ; Yuan, X. ; Ahmed, M. ; Gu, F. ; Ball, A. D. / Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals. ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation. IEEE Computer Society, 2013. pp. 197-202
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abstract = "Motor current signature analysis (MCSA) is a common practice in industry for finding motor faults. However, because of small modulations caused by faults and high noise contamination, it is difficult to quantify the modulation in measured signals which is dominated by the supply frequency, higher order harmonics and noise. In this paper a modulation signal bispectrum (MSB) is investigated to detect stator winding faults. This type of fault can cause high winding temperatures which may effect on current signal so motor temperature will be considered in this paper. The results show that MSB has the capability to accurately estimate modulation degrees and suppress the random and non-modulation components. The test results show that MSB has a better performance in differentiating spectrum amplitudes due to stator faults, and hence produces better diagnosis performance, compared with that of conventional power spectrum analysis.",
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Alwodai, A, Shao, Y, Yuan, X, Ahmed, M, Gu, F & Ball, AD 2013, Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals. in ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation., 6662037, IEEE Computer Society, pp. 197-202, 19th International Conference on Automation and Computing, London, United Kingdom, 13/09/13.

Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals. / Alwodai, A.; Shao, Y.; Yuan, X.; Ahmed, M.; Gu, F.; Ball, A. D.

ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation. IEEE Computer Society, 2013. p. 197-202 6662037.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals

AU - Alwodai, A.

AU - Shao, Y.

AU - Yuan, X.

AU - Ahmed, M.

AU - Gu, F.

AU - Ball, A. D.

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N2 - Motor current signature analysis (MCSA) is a common practice in industry for finding motor faults. However, because of small modulations caused by faults and high noise contamination, it is difficult to quantify the modulation in measured signals which is dominated by the supply frequency, higher order harmonics and noise. In this paper a modulation signal bispectrum (MSB) is investigated to detect stator winding faults. This type of fault can cause high winding temperatures which may effect on current signal so motor temperature will be considered in this paper. The results show that MSB has the capability to accurately estimate modulation degrees and suppress the random and non-modulation components. The test results show that MSB has a better performance in differentiating spectrum amplitudes due to stator faults, and hence produces better diagnosis performance, compared with that of conventional power spectrum analysis.

AB - Motor current signature analysis (MCSA) is a common practice in industry for finding motor faults. However, because of small modulations caused by faults and high noise contamination, it is difficult to quantify the modulation in measured signals which is dominated by the supply frequency, higher order harmonics and noise. In this paper a modulation signal bispectrum (MSB) is investigated to detect stator winding faults. This type of fault can cause high winding temperatures which may effect on current signal so motor temperature will be considered in this paper. The results show that MSB has the capability to accurately estimate modulation degrees and suppress the random and non-modulation components. The test results show that MSB has a better performance in differentiating spectrum amplitudes due to stator faults, and hence produces better diagnosis performance, compared with that of conventional power spectrum analysis.

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Alwodai A, Shao Y, Yuan X, Ahmed M, Gu F, Ball AD. Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals. In ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation. IEEE Computer Society. 2013. p. 197-202. 6662037