标题/作者	年份
Applications of machine learning to machine fault diagnosis: A review and roadmap Y Lei, B Yang, X Jiang, F Jia, N Li, AK Nandi Mechanical Systems and Signal Processing 138, 106587	2020
Deep learning algorithms for bearing fault diagnostics—A comprehensive review S Zhang, S Zhang, B Wang, TG Habetler IEEE Access 8, 29857-29881	2020
A transfer convolutional neural network for fault diagnosis based on ResNet-50 L Wen, X Li, L Gao Neural Computing and Applications 32 (10), 6111-6124	2020
A novel deeper one-dimensional CNN with residual learning for fault diagnosis of wheelset bearings in high-speed trains D Peng, Z Liu, H Wang, Y Qin, L Jia Ieee Access 7, 10278-10293	2018
Online fault diagnosis method based on transfer convolutional neural networks G Xu, M Liu, Z Jiang, W Shen, C Huang IEEE Transactions on Instrumentation and Measurement 69 (2), 509-520	2019
A two-stage approach for the remaining useful life prediction of bearings using deep neural networks M Xia, T Li, T Shu, J Wan, CW De Silva, Z Wang IEEE Transactions on Industrial Informatics 15 (6), 3703-3711	2018
Bearing fault diagnosis method based on deep convolutional neural network and random forest ensemble learning G Xu, M Liu, Z Jiang, D Söffker, W Shen Sensors 19 (5), 1088	2019
Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network J Wu, K Hu, Y Cheng, H Zhu, X Shao, Y Wang ISA transactions 97, 241-250	2020
An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder C Shen, Y Qi, J Wang, G Cai, Z Zhu Engineering Applications of Artificial Intelligence 76, 170-184	2018
Knowledge transfer for rotary machine fault diagnosis R Yan, F Shen, C Sun, X Chen IEEE Sensors Journal 20 (15), 8374-8393	2019
Reliable intelligent path following control for a robotic airship against sensor faults Y Wang, W Zhou, J Luo, H Yan, H Pu, Y Peng IEEE/ASME Transactions on Mechatronics 24 (6), 2572-2582	2019
An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems T Han, C Liu, L Wu, S Sarkar, D Jiang Mechanical Systems and Signal Processing 117, 170-187	2019
Understanding and learning discriminant features based on multiattention 1DCNN for wheelset bearing fault diagnosis H Wang, Z Liu, D Peng, Y Qin IEEE Transactions on Industrial Informatics 16 (9), 5735-5745	2019
A review on deep learning applications in prognostics and health management L Zhang, J Lin, B Liu, Z Zhang, X Yan, M Wei Ieee Access 7, 162415-162438	2019
Multiple wavelet coefficients fusion in deep residual networks for fault diagnosis M Zhao, M Kang, B Tang, M Pecht IEEE Transactions on Industrial Electronics 66 (6), 4696-4706	2018
A comprehensive review on convolutional neural network in machine fault diagnosis J Jiao, M Zhao, J Lin, K Liang Neurocomputing 417, 36-63	2020
Deep coupled dense convolutional network with complementary data for intelligent fault diagnosis J Jiao, M Zhao, J Lin, C Ding IEEE Transactions on Industrial Electronics 66 (12), 9858-9867	2019
Data-driven fault diagnosis method based on compressed sensing and improved multiscale network ZX Hu, Y Wang, MF Ge, J Liu IEEE Transactions on Industrial Electronics 67 (4), 3216-3225	2019
A novel deep learning method for intelligent fault diagnosis of rotating machinery based on improved CNN-SVM and multichannel data fusion W Gong, H Chen, Z Zhang, M Zhang, R Wang, C Guan, Q Wang Sensors 19 (7), 1693	2019
Deep learning for prognostics and health management: State of the art, challenges, and opportunities B Rezaeianjouybari, Y Shang Measurement 163, 107929	2020

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