An initial fault diagnosis method of rolling element bearing based on MED and Hilbert transform
WANG Zhiyang
ZHANG Yongxin
CHEN Lan
SONG Xiaoqing
Abstract：Initial fault detection of the rolling element bearing is very important for prognostic and health management.However,it is difficult to extract the initial fault from rolling element bearings for the influence of environmental noise,transmission path,signal attenuation and weakness of source signal.In order to solve this problem,a method based on minimum entropy deconvolution (MED)and Hilbert transform (HT)is proposed.The signals from sensors are firstly proceeded with MED algorithm to improve signal to noise ratio (SNR),then demodulated by Hilbert transform to get the impulse energy signal.Finally,the fault is confirmed by spectrum frequency analysis of the impulse energy signal.The proposed method can detect and enhance the weak fault feature successfully compared with the envelope analysis method only.The effectiveness of the proposed method is verified by the simulations and experiments of the rolling element bearing.
Keywords：fault diagnosisfeature extractionMEDHilbert transformfeature enhancing
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 91-96 )