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《Proceedings of the CSEE》 2012-11
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Rolling Bearing Fault Feature Extraction Method Based on Ensemble Empirical Mode Decomposition and Kurtosis Criterion

HU Aijun,MA Wanli,TANG Guiji(Mechanical Engineering Department,North China Electric Power University,Baoding 071003,Hebei Province,China)  
In order to realize the precise fault diagnosis of rolling bearing,an envelope demodulation method was proposed based on ensemble empirical mode decomposition(EEMD) and kurtosis criterion.EEMD was used to decompose the vibration signal into several Intrinsic Mode Functions(IMFs) first,and then an envelope demodulation was adopted with the IMF which selected by the maximal kurtosis criterion to extract the fault information.This method can not only restrain the mode mixing phenomenon caused by empirical mode decomposition(EMD),but also avoid the selection of center frequency and filter band in resonance demodulation method,so it has good adaptability.On the basis of discussing inner and outer vibration fault mechanism of rolling bearing,the proposed method was used to analyze the vibration signal of the actual fault rolling bearings.The result shows that this method can efficiently extract the fault information and realize the precise fault diagnosis of rolling bearing.
【Fund】: 国家自然科学基金项目(11072078);; 中央高校基本科研业务费专项资金资助~~
【CateGory Index】: TH165.3
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