DocumentCode :
537872
Title :
Method of EMD and ZOOM-FFT to detect the broken bars fault in induction motor
Author :
Yiguang, Chen ; Hongxia, Zhang ; Yonghuan, Shen
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
fYear :
2010
fDate :
10-13 Oct. 2010
Firstpage :
1387
Lastpage :
1391
Abstract :
For the fault signal processing of induction motor with broken rotor, a new processing method is proposed, which is based on Empirical Mode Decomposition(EMD) and zoom fast Fourier transform (ZOOM-FFT). Using this method can make up the shortcomings that the frequency resolution of the general Fast Fourier transform (FFT) has a certain limit in the frequency range of interest. And the EMD adopted in this method has better adaptability. The stator current signal which is after low-pass filter processed is firstly decomposed with Empirical Mode Decomposition, and a series Intrinsic Mode Function (IMF) components which include different features scale are gained. Then, the IMF component which contains the broken bar fault feature is spectrum analyzed by using ZOOM-FFT. At last the fault feature frequency component can be picked up to judge the broken bars fault according to the amplitude of the fault component. The stator current analysis result from the simulation and actual measurement demonstrate the validity of the proposed method.
Keywords :
fast Fourier transforms; fault diagnosis; induction motors; stators; EMD; ZOOM-FFT; broken bars fault; broken rotor; empirical mode decomposition; fast Fourier transforms; fault signal processing; induction motor; intrinsic mode function components; zoom fast Fourier transform; Bars; Circuit faults; Induction motors; Rotors; Stator windings; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2010 International Conference on
Conference_Location :
Incheon
Print_ISBN :
978-1-4244-7720-3
Type :
conf
Filename :
5663741
Link To Document :
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