The fault feature of rolling element bearing in early failure period is so weak and susceptible to random noise and other signal interference that it’s very difficult to be extracted，so combined maximum correlated kurtosis deconvolution with variational mode decomposition for extracting rolling element bearing fault feature. Firstly enhanced the signal by MCKD and decomposed into several modes by VMD，then reconstructed and reduced noise with the mode，which selected by the comparative correlation coefficient and kurtosis criterion，finally used the envelope demodulation to extract fault feature. The simulating signal analysis and bearing fault simulator show the validity of the method：this method can accurately separate different frequency components of bearing fault vibration signals．
XIA Jun-zhong，ZHAO Lei，BAI Yun-chuan，YU Ming-qi，WANG Zhi-an.
Feature extraction for rolling element bearing weak fault based on MCKD and VMD[J]. Journal of Vibration and Shock, 2017, 36(20): 78-83
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