Fault diagnosis of rolling element bearings using basis pursuit
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The task of condition monitoring and fault diagnosis of rolling element bearing is often cumbersome and labour intensive. Various techniques have been proposed for rolling bearing fault detection and diagnosis. The challenge however, is to efficiently and accurately extract features from signals acquired from these elements, particularly in the time–frequency domain. A new time–frequency technique, known as basis pursuit, was recently developed. This paper presents an application of this new basis pursuit method in the extraction of features from signals collected from faulty rolling bearings with inner race and outer race faults. Results obtained using this new technique were compared with discrete wavelet packet analysis (DWPA) and the matching pursuit technique. Basis pursuit represents features with very fine resolution and sparsity in the time–frequency domain thus rendering easier interpretation of the analysed results. The technique also improves the signal to noise ratio so that subsequent fault detection and identification can be conducted with confidence.
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|Item Type:||Journal Article|
|Additional Information:||For more information, please refer to the journal's website (see hypertext link) or contact the author.|
|Keywords:||Fault diagnosis, Feature extraction, Basis pursuit, Discrete wavelet packet analysis, Matching pursuit|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300)
|Divisions:||Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)|
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2005 Elsevier|
|Deposited On:||17 Feb 2009 12:23|
|Last Modified:||29 Feb 2012 23:05|
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