Rolling Bearing Fault Detection Using Autocorrelation Based Morpho-logical Filtering and Empirical Mode Decomposition

  • Jingyue WANG Shenyang Ligong University, Shenyang, 110159, China
  • Haotian WANG Shenyang Aerospace University, Shenyang, 110136, China
  • Lixin GUO Northeastern University, Shenyang, 110819, China
  • Diange YANG State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Keywords: rolling bearing, pitting failure, autocorrelation, morphologi-cal filter, empirical mode decomposition

Abstract

In order to identify incipient rolling bearing pitting fault characteristics, an autocorrelation based multi-structure elements difference morphological filter and empirical mode decomposition method of fault diagnosis is presented in this paper. Through the experiment of rolling bearing inner and outer ring pitting failure, the fault vibration frequency is extracted to verify the feasibility of this method. The superiority of this method is verified by comparing with the empirical mode decomposition method with autocorrelation based multi-structure element mixed morphological filter and without filter.

DOI: http://dx.doi.org/10.5755/j01.mech.24.6.22471

Published
2019-01-10
Section
Articles