Wavelet Decomposition for the Detection and Diagnosis of Faults in Rolling Element Bearings

Chebil, J., Noel, G., Mesbah, M. and Deriche, M. (2009) Wavelet Decomposition for the Detection and Diagnosis of Faults in Rolling Element Bearings. Jordan Journal of Mechanical and Industrial Engineering, 3 4: 260-267.

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Author Chebil, J.
Noel, G.
Mesbah, M.
Deriche, M.
Title Wavelet Decomposition for the Detection and Diagnosis of Faults in Rolling Element Bearings
Journal name Jordan Journal of Mechanical and Industrial Engineering
ISSN 1995-6665
Publication date 2009-12
Sub-type Article (original research)
Open Access Status File (Publisher version)
Volume 3
Issue 4
Start page 260
End page 267
Total pages 7
Place of publication Jordan
Publisher Hashemite University
Language eng
Subject 09 Engineering
Abstract Condition monitoring and fault diagnosis of equipment and processes are of great concern in industries. Early fault detection in machineries can save millions of dollars in emergency maintenance costs. This paper presents a wavelet-based analysis technique for the diagnosis of faults in rotating machinery from its mechanical vibrations. The choice between the discrete wavelet transform and the discrete wavelet packet transform is discussed, along with the choice of the mother wavelet and some of the common extracted features. It was found that the peak locations in spectrum of the vibration signal could also be efficiently used in the detection of a fault in ball bearings. For the identification of fault location and its size, best results were obtained with the root mean square extracted from the terminal nodes of a wavelet tree of Symlet basis fed to Bayesian classier.
Keyword Discrete Wavelets Transform
Discrete Wavelet Packet Transform
Ball Bearing Fault Detection
Q-Index Code C1
Q-Index Status Provisional Code

Document type: Journal Article
Sub-type: Article (original research)
Collection: UQ Centre for Clinical Research Publications
 
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Created: Wed, 22 Sep 2010, 14:13:09 EST by Laura McTaggart on behalf of UQ Centre for Clinical Research