Title :
Rotor bar fault feature extraction of induction motor base on FFT and MUSIC
Author :
Wang Hongxi ; Yang Weidong
Author_Institution :
Sch. of Autom., Univ. of Sci. & Technol., Beijing, China
Abstract :
In this paper, the rotor broken-bar faults feature component are difficult to detect because it always hides behind the strong supply frequency component in the spectrum of the stator current .So a method is put forward that uses FFT algorithm to pre-estimate the frequencies of a signal then uses MUSIC (Multiple Signal Classification) algorithm to complete the frequency search. This method overcomes spectral leakage and fence effect of FFT and shortens peak search time of MUSIC. Simulation results show that fault characteristic components can be obtained accurately through the method presented even with small samples.
Keywords :
electric machine analysis computing; fast Fourier transforms; feature extraction; frequency estimation; induction motors; rotors; signal classification; FFT algorithm; MUSIC; frequency component; frequency preestimation; frequency search; induction motor; multiple signal classification; rotor bar fault feature extraction; rotor broken-bar fault feature component; stator current; Bars; Equations; Frequency estimation; Induction motors; Mathematical model; Multiple signal classification; Rotors; FFT; Fault diagnosis; MUSIC; Rotor broken-bar fault;
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
DOI :
10.1109/MEC.2011.6025416