| Predicting remaining useful life of rolling bearings based on deep feature representation and transfer learning W Mao, J He, MJ Zuo IEEE Transactions on Instrumentation and Measurement 69 (4), 1594-1608, 2019 | 254 | 2019 |
| Imbalanced fault diagnosis of rolling bearing based on generative adversarial network: A comparative study W Mao, Y Liu, L Ding, Y Li Ieee Access 7, 9515-9530, 2019 | 229 | 2019 |
| Online sequential prediction of bearings imbalanced fault diagnosis by extreme learning machine W Mao, L He, Y Yan, J Wang Mechanical Systems and Signal Processing 83, 450-473, 2017 | 199 | 2017 |
| A new deep auto-encoder method with fusing discriminant information for bearing fault diagnosis W Mao, W Feng, Y Liu, D Zhang, X Liang Mechanical Systems and Signal Processing 150, 107233, 2021 | 183 | 2021 |
| A novel deep output kernel learning method for bearing fault structural diagnosis W Mao, W Feng, X Liang Mechanical Systems and Signal Processing 117, 293-318, 2019 | 125 | 2019 |
| Bearing fault diagnosis with auto-encoder extreme learning machine: A comparative study W Mao, J He, Y Li, Y Yan Proceedings of the Institution of Mechanical Engineers, Part C: Journal of …, 2017 | 119 | 2017 |
| Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network W Mao, J He, J Tang, Y Li Advances in Mechanical Engineering 10 (12), 1687814018817184, 2018 | 116 | 2018 |
| A new online detection approach for rolling bearing incipient fault via self-adaptive deep feature matching W Mao, J Chen, X Liang, X Zhang IEEE Transactions on Instrumentation and Measurement 69 (2), 443-456, 2019 | 105 | 2019 |
| Hybrid Particle Swarm and Grey Wolf Optimizer and its application to clustering optimization X Zhang, Q Lin, W Mao, S Liu, Z Dou, G Liu Applied Soft Computing 101, 107061, 2021 | 104 | 2021 |
| Online detection for bearing incipient fault based on deep transfer learning W Mao, L Ding, S Tian, X Liang Measurement 152, 107278, 2020 | 100 | 2020 |
| Fire recognition based on multi-channel convolutional neural network W Mao, W Wang, Z Dou, Y Li Fire technology 54, 531-554, 2018 | 77* | 2018 |
| A new structured domain adversarial neural network for transfer fault diagnosis of rolling bearings under different working conditions W Mao, Y Liu, L Ding, A Safian, X Liang IEEE Transactions on Instrumentation and Measurement 70, 1-13, 2020 | 74 | 2020 |
| Online detection of bearing incipient fault with semi-supervised architecture and deep feature representation W Mao, S Tian, J Fan, X Liang, A Safian Journal of Manufacturing Systems 55, 179-198, 2020 | 74 | 2020 |
| A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system K Feng, JC Ji, Q Ni, Y Li, W Mao, L Liu Wear 522, 204697, 2023 | 65 | 2023 |
| An adaptive stochastic dominant learning swarm optimizer for high-dimensional optimization Q Yang, WN Chen, T Gu, H Jin, W Mao, J Zhang IEEE Transactions on Cybernetics 52 (3), 1960-1976, 2020 | 59 | 2020 |
| An ELM-based model with sparse-weighting strategy for sequential data imbalance problem W Mao, J Wang, Z Xue International Journal of Machine Learning and Cybernetics 8, 1333-1345, 2017 | 51 | 2017 |
| Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective J Chen, R Huang, Z Chen, W Mao, W Li Mechanical Systems and Signal Processing 193, 110239, 2023 | 48 | 2023 |
| An interpretable deep transfer learning-based remaining useful life prediction approach for bearings with selective degradation knowledge fusion W Mao, J Liu, J Chen, X Liang IEEE Transactions on Instrumentation and Measurement 71, 1-16, 2022 | 40 | 2022 |
| A fast and robust model selection algorithm for multi-input multi-output support vector machine W Mao, J Xu, C Wang, L Dong Neurocomputing 130, 10-19, 2014 | 33 | 2014 |
| Leave-one-out cross-validation-based model selection for multi-input multi-output support vector machine W Mao, X Mu, Y Zheng, G Yan Neural Computing and Applications 24, 441-451, 2014 | 31 | 2014 |
