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Wavelet decomposition for the detection and diagnosis of faults in rolling element bearings

Jalel, chebil (2009) Wavelet decomposition for the detection and diagnosis of faults in rolling element bearings. Jordan Journal of Mechanical and Industrial Engineering, 3 (4). pp. 260-267. ISSN 1995-6665

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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.

Item Type: Article (Journal)
Additional Information: 6110/9029
Uncontrolled Keywords: discrete wavelets transform; discrete wavelet packet transform; ball bearing fault detection
Subjects: T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Mrs Siti Hawa Darus
Date Deposited: 24 Dec 2011 17:03
Last Modified: 24 Dec 2011 17:03
URI: http://irep.iium.edu.my/id/eprint/9029

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