Title :
A new approach for fault detection of broken rotor bars in induction motor based on support vector machine
Author :
Armaki, Mahdi Gordi ; Roshanfekr, Reza
Author_Institution :
Eng. Dept., Sabzevar Tarbiat Moallem Univ., Sabzevar, Iran
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.
Keywords :
Bars; Fast Fourier transforms; Fault detection; Induction motors; Power system harmonics; Rotors; Stators; Steady-state; Support vector machine classification; Support vector machines; Fault detection; Induction motor; Support vector machine; rotor broken bar;
Conference_Titel :
Electrical Engineering (ICEE), 2010 18th Iranian Conference on
Conference_Location :
Isfahan, Iran
Print_ISBN :
978-1-4244-6760-0
DOI :
10.1109/IRANIANCEE.2010.5506976