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Modulation signal bispectrum analysis of electric signals for the detection and diagnosis of compound faults in induction motors with sensorless drives

Shaeboub, Abdulkarim, Gu, Fengshou, Lane, Mark, Haba, Usama, Wu, Zhifei and Ball, Andrew (2017) Modulation signal bispectrum analysis of electric signals for the detection and diagnosis of compound faults in induction motors with sensorless drives. Systems Science & Control Engineering, 5 (1). pp. 252-267. ISSN 2164-2583

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Abstract

As a prime driver, induction motor is 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 status and avoid excessive energy consumption and severe damages to systems. This paper examines the performance of diagnosing the effect of asymmetry stator winding on broken rotor bar (BRB) faults under closed loop operation modes. It examines the effectiveness of conventional diagnostic 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 a more correct indication of the fault severity and its location for all operating conditions.

Item Type: Article
Uncontrolled Keywords: Induction motor, stator winding asymmetry and broken rotor bar, variable speed drive (VSD), motor current and voltage signatures analysis
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
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Depositing User: Sally Hughes
Date Deposited: 06 Jun 2017 13:36
Last Modified: 06 Jun 2017 13:36
URI: http://eprints.hud.ac.uk/id/eprint/32141

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