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

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2 Author(s)
Mahdi Gordi Armaki ; Engineering Department, Sabzevar Tarbiat Moallem University, Iran ; Reza Roshanfekr

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.

Published in:

2010 18th Iranian Conference on Electrical Engineering

Date of Conference:

11-13 May 2010