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

Authors

  • 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

DOI:

https://doi.org/10.5755/j01.mech.24.6.22471

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

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Published

2018-12-29

Issue

Vol. 24 No. 6 (2018)

Section

Articles

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The copyright for the articles in this journal is retained by the author(s) with the first publication right granted to the journal. The journal is licensed under the Creative Commons Attribution License 4.0 (CC BY 4.0).