Classification of machinery vibration signals based on group sparse representation
Author:
Publisher
JVE International Ltd.
Subject
Mechanical Engineering,General Materials Science
Link
http://www.jvejournals.com/Vibro/fulltextpdf/JVE-2016-18-3/JVE01816051989.pdf
Reference26 articles.
1. Harris F. J. Rolling Bearing Analysis 2. John Wiley, New York, 2000.
2. Shin Younghak, Lee Seungchan, Ahn Minkyu, et al. Noise robustness analysis of sparse representation based classification method for non-stationary EEG signal classification. Biomedical Signal Processing and Control, Vol. 21, 2015, p. 8-18.
3. Rafiee J., Tse P. W., Harifi A., et al. A novel technique for selecting mother wavelet function using an intelligent fault diagnosis system. Expert Systems with Applications, Vol. 36, 2009, p. 4862-4875.
4. Wang D., Tse P. W., Tsui K. L. An enhanced kurtogram method for fault diagnosis of rolling element bearings. Mechanical Systems and Signal Processing, Vol. 35, 2013, p. 176-199.
5. Tang G., Yang Qin, Wang Hua-Qing, et al. Sparse classification of rotating machinery faults based on compressive sensing strategy. Mechatronics, 2015, (in Press).
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