Ali Saud Al Tobi, Maamer

Bevan, Geraint

Harrison, David

Ramachandran, K. P.

Wallace, Peter

English

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

ResearchOnline@GCU

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

https://researchonline.gcu.ac.uk/files/24654630/G.Bevan_A_review_on_applications_of_wavelet_transform_and_artificial_intelligence_systems_in_fault_diagnosis_of_rotating_machinery2_3_.pdf

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

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