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

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 Par 1 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 tocertificate 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 faultdetection in induction motors (IMs) is the essential part of any fault recognitionprocedure. 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.