| A novel deep autoencoder feature learning method for rotating machinery fault diagnosis H Shao, H Jiang, H Zhao, F Wang Mechanical Systems and Signal Processing 95, 187-204, 2017 | 629 | 2017 |
| Rolling bearing fault diagnosis using an optimization deep belief network H Shao, H Jiang, X Zhang, M Niu Measurement Science and Technology 26 (11), 115002, 2015 | 502 | 2015 |
| A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders H Shao, H Jiang, Y Lin, X Li Mechanical Systems and Signal Processing 102, 278-297, 2018 | 441 | 2018 |
| Electric locomotive bearing fault diagnosis using a novel convolutional deep belief network H Shao, H Jiang, H Zhang, T Liang IEEE Transactions on Industrial Electronics 65 (3), 2727-2736, 2017 | 434 | 2017 |
| Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing H Shao, H Jiang, H Zhang, W Duan, T Liang, S Wu Mechanical systems and signal processing 100, 743-765, 2018 | 371 | 2018 |
| Intelligent fault diagnosis of rotor-bearing system under varying working conditions with modified transfer convolutional neural network and thermal images H Shao, M Xia, G Han, Y Zhang, J Wan IEEE Transactions on Industrial Informatics 17 (5), 3488-3496, 2020 | 332 | 2020 |
| Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine S Haidong, J Hongkai, L Xingqiu, W Shuaipeng Knowledge-Based Systems 140, 1-14, 2018 | 324 | 2018 |
| An enhancement deep feature fusion method for rotating machinery fault diagnosis H Shao, H Jiang, F Wang, H Zhao Knowledge-Based Systems 119, 200-220, 2017 | 305 | 2017 |
| Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet H Shao, H Jiang, F Wang, Y Wang ISA transactions 69, 187-201, 2017 | 269 | 2017 |
| Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder H Zhiyi, S Haidong, J Lin, C Junsheng, Y Yu Measurement 152, 107393, 2020 | 222 | 2020 |
| Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning M Xia, H Shao, D Williams, S Lu, L Shu, CW de Silva Reliability Engineering & System Safety 215, 107938, 2021 | 220 | 2021 |
| Ensemble transfer CNNs driven by multi-channel signals for fault diagnosis of rotating machinery cross working conditions Z He, H Shao, X Zhong, X Zhao Knowledge-Based Systems 207, 106396, 2020 | 204 | 2020 |
| An adaptive deep convolutional neural network for rolling bearing fault diagnosis W Fuan, J Hongkai, S Haidong, D Wenjing, W Shuaipeng Measurement Science and Technology 28 (9), 095005, 2017 | 197 | 2017 |
| Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples Z He, H Shao, P Wang, JJ Lin, J Cheng, Y Yang Knowledge-Based Systems 191, 105313, 2020 | 196 | 2020 |
| Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain Y Xiao, H Shao, SY Han, Z Huo, J Wan IEEE/ASME Transactions on Mechatronics 27 (6), 5254-5263, 2022 | 194 | 2022 |
| Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing S Haidong, C Junsheng, J Hongkai, Y Yu, W Zhantao Knowledge-Based Systems 188, 105022, 2020 | 194 | 2020 |
| A stacked GRU-RNN-based approach for predicting renewable energy and electricity load for smart grid operation M Xia, H Shao, X Ma, CW de Silva IEEE Transactions on Industrial Informatics 17 (10), 7050-7059, 2021 | 192 | 2021 |
| A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance H Shao, J Lin, L Zhang, D Galar, U Kumar Information Fusion 74, 65-76, 2021 | 188 | 2021 |
| Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds H Cao, H Shao, X Zhong, Q Deng, X Yang, J Xuan Journal of Manufacturing Systems 62, 186-198, 2022 | 181 | 2022 |
| Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework W Li, X Zhong, H Shao, B Cai, X Yang Advanced Engineering Informatics 52, 101552, 2022 | 173 | 2022 |
