Multi-stages helical gearbox fault detection using vibration signal and Morlet wavelet transform adapted by information entropy difference

Fathalla Elbarghathi, Xiang Tian, Van Tung Tran, Fengshou Gu, Andrew Ball

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Abstract

Although the wavelet analysis is a powerful tool and has been widely used for the vibration signal based gearbox fault diagnosis, there are some limitations that undermine its application. The results of the wavelet transform do not possess time invariant property, which may result in the loss of useful information and decrease the accuracy of fault diagnosis. Other limitations in wavelet transform are the selection of the suitable threshold and the wavelet function. A main challenge of wavelet analysis is the adaptability of the parameters of the mother wavelet to the time variance of the given signal. To overcome this deficiency, an adaptive Morlet wavelet transform method based on the information entropy optimization is proposed in this study. The proposed wavelet transform method is applied for analyzing the vibration signals to detect and diagnose the faults of a helical gearbox. A comparative study of the proposed method and the previous study which used the kurtosis maximization to adapt the wavelet parameters are also carried out to evaluate the proposed method.
Original languageEnglish
Number of pages7
Publication statusPublished - 2013
Externally publishedYes
EventInternational Congress of Condition Monitoring and Diagnostic Engineering Management, COMADEM 2013 - Helsinki, Finland
Duration: 11 Jun 201313 Jun 2013
http://maintworld.mycashflow.fi/product/5/comadem-2013-proceedings

Conference

ConferenceInternational Congress of Condition Monitoring and Diagnostic Engineering Management, COMADEM 2013
Abbreviated titleCOMADEM 2013
CountryFinland
CityHelsinki
Period11/06/1313/06/13
Internet address

Keywords

  • Helical gearbox diagnosis
  • Condition monitoring
  • Vibration analysis
  • Adaptive Morlet wavelet
  • Information entropy

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