关键词: 滚动轴承, 稀疏度, 最大相关峭度解卷积, 故障诊断

Abstract:

Early fault  features of rolling  bearings  are   very weak and are  affected by environment  noise  seriously,so it  is difficult to draw fault features.Aiming at solving this problem,MCKD  was tried to diagnose faults  for bearings,and sparsity of envelope spectrum was used to select the optimal deconvolution period parameter,then incipient  fault diagnosis method for  rolling bearings was proposed  based on sparsity of envelope spectrum and MCKD.MCKD  method corresponding to  the optimal parameter was used to process the original signals  and the envelope spectrum of deconvolution signals was obtained,the bearing faults were  judged by analyzing the envelope spectrum.Simulated incipient fault signals and full lifetime datasets of  rolling bearings  were used  to  examine  the  feasibility  of this method and the results show  the new method can  be  applied  to  diagnose the incipient fault effectively. 

Key words: rolling bearing;sparsity;maximum correlated kurtosis , deconvolution(MCKD);fault , diagnosis