A Review of Application of Signal Processing Techniques for Fault Diagnosis of Induction Motors – Part I

Document Type : Review Article

Authors

1 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran

2 Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada

Abstract

Abstract - Use of efficient signal processing tools (SPTs) to extract proper indices for fault detection in induction motors (IMs) is the essential part of any fault recognition procedure. The Part1 of the two parts paper focuses on Fourier-based techniques including fast Fourier transform and short time Fourier transform. In this paper, all utilized SPTs which have been employed for fault fetection in IMs are analyzed in details. Then, their competency and their drawbacks for extracting indices in transient and steady state modes are criticized from different aspects. The considerable experimental results are used to certificate demonstrated discussion. Different kinds of faults, including eccentricity, broken bar and bearing faults as major internal faults, in IMs are investigated.
The use of efficient signal processing tools (SPTs) to extract proper indices for fault
detection in induction motors (IMs) is the essential part of any fault recognition procedure. In the
first part of the present paper, we focus on Fourier-based techniques, including fast Fourier transform
and short time Fourier transform. In this paper, all utilized SPTs which have been employed for
fault detection in IMs are analyzed in detail. Then, their competency and their drawbacks to extract
indices in transient and steady state modes are criticized from different aspects. Different kinds of
faults, namely, eccentricity, broken bar, and bearing faults as the major internal faults in IMs, are
investigated.

Keywords

Main Subjects

References

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AUT Journal of Electrical Engineering
Volume 49, Issue 2
December 2017
Pages 109-122

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