Assessment of bearing performance degradation via extension and EEMD combined approach

Author:

Liu Yu-mei,Zhao Cong-cong,Xiong Ming-ye,Zhao Ying-hui,Qiao Ning-guo,Tian Guang-dong

Publisher

Springer Science and Business Media LLC

Subject

Metals and Alloys,General Engineering

Reference23 articles.

1. ZHANG Chao, CHEN Jian-jun, XU Ya-lan. A bearing fault diagnosis method based on EMD and difference spectrum theory of singular value [J]. Journal of Vibration Engineering, 2011, 24(5): 539–545. (in Chinese)

2. PENG Tao, YANG Hui-bin, LI Jian-bao, JIANG Hai-yan, WEI Wei. Mixed-domain feature extraction approach to rolling bearings faults based on kernek principle component analysis [J]. Journal of Central South University (Science and Technology), 2011, 42(11): 3384–3391. (in Chinese)

3. HU Chao, YOUN B D, WANG Ping-feng, TAEK Y Y. Ensemble of data-driven prongostic algorithms for robust prediction of remaining useful life [J]. Reliability Engineering and System Safety, 2012, 103: 120–135.

4. TABRIZI A, GARIBALDI L, FASANA A, MARCHESIELLO S. Early damage detection of roller bearings using wavelet packet decomposition, ensemble empirical mode decomposition and support vector machine [J]. Meccanica, 2015; 50(3): 865–874.

5. WANG Xia, LIU Cheng-wen, BI Feng-rong, BI Xiao-yang, SHAO Kang. Fault diagnosis of diesel engine based on adaptive wavelet packets and EEMD-fractal dimension [J]. Mechanical Systems and Signal Processing, 2013, 41: 581–597.

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