An improved initialization method of D-KSVD algorithm for bearing fault diagnosis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials
Link
http://link.springer.com/article/10.1007/s12206-017-1010-7/fulltext.html
Reference38 articles.
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3. Q. Xiong, Y. H. Xu, Y. Q. Peng, W. H. Zhang, Y. J. Li and L. Tang, Low-speed rolling bearing fault diagnosis based on EMD denoising and parameter estimate with alpha stable distribution, J. of Mechanical Science and Technology, 31 (4) (2017) 1587–1601.
4. R. B. Randall, J. Antoni and S. Chobsaard, The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals, Mechanical Systems and Signal Processing, 15 (5) (2001) 945–962.
5. C. H. Chen, R. J. Shyu and C. K. Ma, Rotating machinery diagnosis using wavelet packets-fractal technology and neural networks, Journal of Mechanical Science and Technology, 21 (7) (2007) 1058–1065.
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