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Application of the Wavelet Multi-resolution Analysis and Hilbert transform for the prediction of gear tooth defects
Date Issued
01 October 2012
Date Available
12T10:24:18Z February 2013
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
Journal
Meccanica
Volume
47
Issue
7
Start Page
1601
End Page
1612
Copyright (Published Version)
2012, Springer Science+Business Media B.V
Language
English
Status of Item
Not peer reviewed
ISSN
1572-9648
0025-6455
This item is made available under a Creative Commons License
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