AN INCIPIENT FAULT DIAGNOSIS METHOD FOR ROLLING BEARING BASED ON MCKD AND LMD

Abstract

Aiming at the problem that the Local mean decomposition（LMD） method is difficult to draw early weak fault,a fault diagnosis method for the roller bearing based on maximum correlated kurtosis deconvolution（MCKD） and LMD was proposed.Firstly,the fault signal was de-noised and meantime periodic impact components were enhanced by MCKD method,Then,that result is decomposed by LMD to get PF,the correlation coefficient between the PF and the signal is used as the standard of judgment,so that the redundant low-frequency PF can be rejected.Finally,the effective PF is selected to analyze the spectrum and extract the fault feature.The experiment of the simulation data and the actual roller bearing fault diagnosis data show that the method can effectively extract the feature frequency information of incipient fault and has a certain reliability.

Keywords

• Rolling bearing;Fault diagnosis;LMD;MCKD