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A New Approach to Diagnose Rolling Bearing Faults Based on AFD

  • Yu Liang
  • Li min Jia
  • Guo qiang Cai
  • Jin zhao Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 288)

Abstract

A new fault diagnosis method of rolling bearing based on adaptive Fourier decomposition (AFD) is proposed. The new approach extracts the meaningful bearing vibration signal based on AFD algorithm instead of traditional band-pass filter; AFD decomposes the original bearing vibration signal into a series of mono-components, the kurtosis of each mono-component is calculated and clustered into two classes by fuzzy C-mean clustering (FCM). The mean of the two cluster centers is taken as threshold and the mono-components with large kurtosis is summed as bearing fault carrier signal because the bearing fault is sensitive to kurtosis; Then demodulated resonance technique is used to diagnose and locate the fault. The new approach can diagnose all kinds of rolling bearings’ fault. Finally, the proposed approach is used to analysis the outer ring fault in case of N205EM type rolling bearing; the experiments indicates that the effectiveness and accuracy are significantly approved.

Keywords

Fault diagnosis Adaptive Fourier decomposition Mono-component Resonant demodulation 

Notes

Acknowledgments

This work is supported by the National High Technology Research and Development Program of China (863 Program) (2011AA110501).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Yu Liang
    • 1
  • Li min Jia
    • 1
  • Guo qiang Cai
    • 1
  • Jin zhao Liu
    • 2
  1. 1.Beijing Jiaotong UniversityBeijingChina
  2. 2.China Academy of Railway SciencesBeijingChina

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