Detection and diagnosis of compound faults in induction motors using electric signals from variable speed drives

Abdulkarim Shaeboub, Mark Lane, Usama Haba, Fengshou Gu, Andrew D. Ball

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

6 Citations (Scopus)

Abstract

As a primer driver, induction motors are the most electric energy consuming component in industry. The exposure of the motor to stator winding asymmetry, combined with broken rotor bar fault significantly increases the temperature and reduces the efficiency and life of the motor. Accurate and timely diagnosis of these faults will help to maintain motors operating under optimal statues and avoid excessive energy consumption and severe damage to systems. This paper examines the performance of diagnosing the effect of asymmetry stator winding on broken rotor bar faults under closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum and modulation signal bispectrum analysis (MSBA). Evaluation results show that the combined faults cause an additional increase in the sideband amplitude and this increase in sideband can be observed in both the current and voltage signals under the sensorless control mode. MSB analysis has a good noise reduction capability and produces a more accurate and reliable diagnosis in that it gives more correct indication of the fault severity and location for all operating conditions.

Original languageEnglish
Title of host publication2016 22nd International Conference on Automation and Computing, ICAC 2016
Subtitle of host publicationTackling the New Challenges in Automation and Computing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages306-312
Number of pages7
ISBN (Electronic)9781862181311
DOIs
Publication statusPublished - 24 Oct 2016
Event22nd International Conference on Automation and Computing - Colchester, United Kingdom
Duration: 7 Sep 20168 Sep 2016
Conference number: 22

Conference

Conference22nd International Conference on Automation and Computing
Abbreviated titleICAC 2016
CountryUnited Kingdom
CityColchester
Period7/09/168/09/16

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    Shaeboub, A., Lane, M., Haba, U., Gu, F., & Ball, A. D. (2016). Detection and diagnosis of compound faults in induction motors using electric signals from variable speed drives. In 2016 22nd International Conference on Automation and Computing, ICAC 2016: Tackling the New Challenges in Automation and Computing (pp. 306-312). [7604937] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IConAC.2016.7604937