NDLI: A new approach for fault detection of broken rotor bars in induction motor based on support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Armaki, M.G. Roshanfekr, R.
Copyright Year	2010
Description	Author affiliation: Engineering Department, Sabzevar Tarbiat Moallem University, Iran (Armaki, M.G.; Roshanfekr, R.)
Abstract	In this paper, a new approach is proposed to perform broken rotor bar fault detection in induction motors using of support vector machine (SVM) classifier. New features such as harmonic curve area, harmonic crest angle and harmonic amplitude have been extracted from power spectral density (PSD) of stator current in steady state condition using of Fast Fourier Transform (FFT). It is shown that combination of the first couple of these features had very better results compare with the harmonic amplitude feature in fault detection of motor. The proposed method was applied to a 1.5kW standard three phase induction motor using of different rotors that had various types of broken rotor bars. Experimental results confirmed the high efficiency of the proposed method for broken rotor fault detection in induction motors.
Starting Page	732
Ending Page	738
File Size	209291
Page Count	7
File Format	PDF
ISBN	9781424467600
e-ISBN	9781424467600
DOI	10.1109/IRANIANCEE.2010.5506976
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-11
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction motors Rotors Rotor broken bar Power system harmonics Steady-state Support vector machine Support vector machines Induction motor Fast Fourier transforms Fault detection Support vector machine classification Stators Bars
Content Type	Text
Resource Type	Article

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