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《China Mechanical Engineering》 2004-10
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Roller Bearing Fault Diagnosis Method Based on EMD

Yang Yu Yu Dejie Cheng Junsheng Hunan University, Changsha, 410082  
Roller bearing fault diagnosis method based on Empirical Mode Decomposition (EMD) was put forward and the concept of EMD energy entropy was introduced. The analysis results from energy entropy of different vibration signals show that the energy of acceleration vibration signal will vary in different frequencies bands when bearing faults occured. To identify roller bearing fault patterns, energy feature parameters extracted from a number of IMFs which contained main fault informations can be served as input parameters of the neural network to identify fault patterns. The analysis results from roller bearing signals with inner-race and out-race faults show that the diagnosis approach of neural network based on EMD extracting energy of different frequencies bands as features is superior to that based on wavelet packet decomposition and reconstruction and would identify roller bearing fault patterns accurately and effectively.
【Fund】: 国家自然科学基金资助项目 ( 5 0 2 75 0 5 0 ) ;; 高等学校博士学科点专项科研基金资助项目 ( 2 0 0 2 0 5 3 2 0 2 4)
【CateGory Index】: TH133.3
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