Author:
Lei Chunli,Wang Lu,Zhang Qiyue,Li Xinjie,Feng Ruicheng,Li Jianhua
Publisher
Springer Science and Business Media LLC
Reference26 articles.
1. L. Zhao, Y. X. Zhang and D. C. Zhu, Review on rolling bearing fault diagnosis and prognostic for complex equipment, China Measurement and Testing Technology, 46 (2020) 17–25.
2. W. T. Zhang, X. F. Ji, J. Huang and S. T. Lou, Compound fault diagnosis of aero-engine rolling element bearing based on CCA blind extraction, IEEE Access, 9 (2021) 159873–159881.
3. M. Iqbal and A. K. Madan, CNC machine-bearing fault detection based on convolutional neural network using vibration and acoustic signal, Journal of Vibration Engineering & Technologies, 10 (2022) 1613–1621.
4. Z. Xu, C. Li and Y. Yang, Fault diagnosis of rolling bearings using an improved multi-scale convolutional neural network with feature attention mechanism, ISA Transactions, 110 (2021) 379–393.
5. X. F. Chen, X. W. Zhang and H. R. Cao, Advances in condition monitoring, diagnosis and vibration control of smart spindles, Journal of Mechanical Engineering, 54 (2018) 58–69.