Bearing fault diagnosis research based on entropy optimization

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Bearing fault diagnosis research based on entropy optimization

QU Hong-chun,WANG Tao,HUANG Yuan-qiang

(College of Aeronautiocal Enginering,CAUC,Tianjin 300300,China)

Received:2014-06-30 Revised:2014-09-16 Online:2015-10-21 Published:2015-11-10

Abstract

Abstract:

The fault type of bearing can be detected quickly through grey relevance computed by the characteristic frequency of signal and standard fault modes. The bearing fault mode can be confirmed and the faulty parts of rotating machinery can be isolated with the combination of grey relation theory and signal analysis. Furthermore,the application of grey incidence analysis in the diagnostic system makes it easier to detect the fault mode generated by two or more failure forms. The detection accuracy is higher due to the bigger discrimination of grey relation ranks with entropy optimization.

Key words: aero engine, bearing fault diagnosis, grey incidence analysis, entropy optimization, rotating machinery

CLC Number:

QU Hong-chun,WANG Tao,HUANG Yuan-qiang. Bearing fault diagnosis research based on entropy optimization[J]. .

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