Modulation signal bispectrum analysis of motor current signals for stator fault diagnosis

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)


Induction motors are the most widely used electrical machines in industry. To diagnose any possible incipient faults, many techniques have been developed. Motor current signature analysis (MCSA) is a common practice in industry to find motor faults. However, because small modulations due to faults it is difficult to quantify it in the measured signals which predominates with supply frequency, higher order harmonics and noise. In this paper a modulation signal (MS) bispectrum is investigated to detect different severities of stator faults. It shows that MS bispectrum has the capability to accurately estimate modulation degrees and suppress the random and nonmodulation components. Test results show that MS bispectrum 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 12 - Proceedings of the 18th International Conference on Automation and Computing
Subtitle of host publicationIntegration of Design and Engineering
Number of pages6
ISBN (Electronic)9781908549006
Publication statusPublished - 15 Oct 2012
Event18th International Conference on Automation and Computing: Integration of Design and Engineering - Loughborough University, Leicestershire, United Kingdom
Duration: 7 Sep 20128 Sep 2012
Conference number: 18 (Link to Conference Website)


Conference18th International Conference on Automation and Computing
Abbreviated titleICAC 2012
Country/TerritoryUnited Kingdom
Internet address


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