Application of the Wavelet Multi-resolution Analysis and Hilbert transform for the prediction of gear tooth defects

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Title: Application of the Wavelet Multi-resolution Analysis and Hilbert transform for the prediction of gear tooth defects
Authors: Djebala, A.
Ouelaa, N.
Benchaabane, C.
Laefer, Debra F.
Permanent link: http://hdl.handle.net/10197/4094
Date: 1-Oct-2012
Abstract: In machine defect detection, namely those of gears, the major problem is isolating the defect signature from the measured signal, especially where there is significant background noise or multiple machine components. This article presents a method of gear defect detection based on the combination of Wavelet Multi-resolution Analysis and the Hilbert transform. The pairing of these techniques allows simultaneous filtering and denoising, along with the possibility of detecting transitory phenomena, as well as a demodulation. This paper presents a numerical simulation of the requisite mathematical model followed by its experimental application of acceleration signals measured on defective gears on a laboratory test rig. Signals were collected under various gear operating conditions, including defect size, rotational speed, and frequency bandwidth. The proposed method compares favourably to commonly used analysis tools, with the advantage of enabling defect frequency isolation, thereby allowing detection of even small or combined defects.
Type of material: Journal Article
Publisher: Springer Verlag
Copyright (published version): 2012, Springer Science+Business Media B.V
Keywords: Vibratory analysis;Gears defects;Wavelet multi-resolution analysis;Hilbert transform;Demodulation
DOI: 10.1007/s11012-012-9538-1
Language: en
Status of Item: Not peer reviewed
Appears in Collections:Civil Engineering Research Collection

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