Author:
Hu Yao,Xiong Qingyu,Zhu Qiwu,Yang Zhengyi,Zhang Zhiyuan,Wu Dan,Wu Zihui
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials
Reference38 articles.
1. A. H. Aljemely, J. Xuan, F. K. J. Jawad, O. AlAzzawi and A. S. Alhumaima, A novel unsupervised learning method for intelligent fault diagnosis of rolling element bearing based on deep functional auto-encoder, Journal of Mechanical Science and Technology, 34 (11) (2020) 4367–4381.
2. C. Lessmeier, J. K. Kimotho, D. Zimmer and W. Sextro, Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: a benchmark data set for data-driven classifification, PHM Society European Conference, 3 (1) (2016) 5–8.
3. S. Riaz, H. Elahi, K. Javaid and T. Shahzad, Vibration feature extraction and analysis for fault diagnosis of rotating machinery-a literature survey, Asia Pacific Journal of Multidisciplinary Research, 5 (1) (2017) 103–110.
4. L. Liu, S. Wang, D. Liu and Y. Peng, Quantitative selection of sensor data based on improved permutation entropy for system remaining useful life prediction, Microelectronics Reliability, 75 (2017) 264–270.
5. H. Zhang, Q. Miao, X. Zhang and Z. Liu, An improved unscented particle filter approach for lithium-ion battery remaining useful life prediction, Microelectronics Reliability, 81 (2018) 288–298.
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