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| Method of Rotating Machinery Fault Diagnosis Based on Gabor Transform and Blind Source Separation |
| MENG Zong1,2,WANG Xiao-yan1,ZHOU Ming-jun1,YIN Na1 |
1. Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao,Hebei 066004，China
2. National Engineering Research Center for Equipment and Technology of Cold Rolling Strip, Qinhuangdao, Hebei 066004,China |
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Abstract In the traditional blind source separation (BSS), the condition of actual mechanical equipment is very difficult to satisfy that the source signals must be mutually statistically independent. A new method of rotating machinery fault diagnosis based on Gabor transform and BSS is proposed. Firstly, the common frequency components of source signals can be obtained by the ratios of the coefficients of the mixed signals in Gabor transform coefficient. Then, the new observed signals are obtained by filtering, and the jointly approximate diagonalization of eigen-matrix (JADE) is applied to the new observed signals. Even if the source signals are correlative, or there is more than one Gaussian signal in the sources, the new method can get better separation performance. Simulation and experiment results verify the effectiveness and feasibility of the proposed method.
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2016, Vol. 37 
