A review on applications of wavelet transform and artificial intelligence systems in fault diagnosis of rotating machinery

Maamer Ali Saud Al Tobi*, Geraint Bevan, Peter Wallace, David Harrison, K. P. Ramachandran

*Corresponding author for this work

Research output: Contribution to journalArticle

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Abstract

Rotating machines play a vital role in many process industries. Vibration analysis is a common form of monitoring their condition. This paper reviews the application of wavelet transforms and artificial intelligence, an advanced form of vibration analysis, for condition monitoring of rotating machines. The review considers different feature extraction methods and shows how wavelet transforms have been applied as a preprocessor for feature extraction with different families of mother wavelet function; and how different artificial intelligence methods have been used for fault classification. It concludes with remarks on the advantages and disadvantages of the applied methods and consideration of future developments to address the current gaps.
Original languageEnglish
Pages (from-to)70-82
Number of pages13
JournalInternational Journal of Industrial Electronics and Electrical Engineering
Volume4
Issue number9
Early online date30 Sep 2016
Publication statusPublished - 24 Oct 2016

Keywords

  • rotating machinery
  • wavelet transform
  • artificial intelligence
  • genetic algorithm
  • accuracy rate

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