| Multisensor feature fusion for bearing fault diagnosis using sparse autoencoder and deep belief network Z Chen, W Li IEEE Transactions on Instrumentation and Measurement 66 (7), 1693-1702, 2017 | 817 | 2017 |
| A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges W Li, R Huang, J Li, Y Liao, Z Chen, G He, R Yan, K Gryllias Mechanical Systems and Signal Processing 167, 108487, 2022 | 411 | 2022 |
| State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network F Yang, W Li, C Li, Q Miao Energy 175, 66-75, 2019 | 379 | 2019 |
| A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks Z Chen, A Mauricio, W Li, K Gryllias Mechanical Systems and Signal Processing 140, 106683, 2020 | 341 | 2020 |
| Mechanical fault diagnosis using convolutional neural networks and extreme learning machine Z Chen, K Gryllias, W Li Mechanical systems and signal processing 133, 106272, 2019 | 293 | 2019 |
| Bearing performance degradation assessment using long short-term memory recurrent network B Zhang, S Zhang, W Li Computers in Industry 106, 14-29, 2019 | 285 | 2019 |
| State-of-charge estimation of lithium-ion batteries using LSTM and UKF F Yang, S Zhang, W Li, Q Miao Energy 201, 117664, 2020 | 268 | 2020 |
| Intelligent fault diagnosis for rotary machinery using transferable convolutional neural network Z Chen, K Gryllias, W Li IEEE Transactions on Industrial Informatics 16 (1), 339-349, 2019 | 244 | 2019 |
| Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery Z Chen, G He, J Li, Y Liao, K Gryllias, W Li IEEE Transactions on Instrumentation and Measurement 69 (11), 8702-8712, 2020 | 199 | 2020 |
| Deep decoupling convolutional neural network for intelligent compound fault diagnosis R Huang, Y Liao, S Zhang, W Li Ieee Access 7, 1848-1858, 2018 | 173 | 2018 |
| A two-stage transfer adversarial network for intelligent fault diagnosis of rotating machinery with multiple new faults J Li, R Huang, G He, Y Liao, Z Wang, W Li IEEE/ASME Transactions on Mechatronics 26 (3), 1591-1601, 2020 | 140 | 2020 |
| Deep semisupervised domain generalization network for rotary machinery fault diagnosis under variable speed Y Liao, R Huang, J Li, Z Chen, W Li IEEE Transactions on Instrumentation and Measurement 69 (10), 8064-8075, 2020 | 139 | 2020 |
| Deep adversarial capsule network for compound fault diagnosis of machinery toward multidomain generalization task R Huang, J Li, Y Liao, J Chen, Z Wang, W Li IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020 | 130 | 2020 |
| A novel weighted adversarial transfer network for partial domain fault diagnosis of machinery W Li, Z Chen, G He IEEE Transactions on Industrial Informatics 17 (3), 1753-1762, 2020 | 125 | 2020 |
| Semisupervised distance-preserving self-organizing map for machine-defect detection and classification W Li, S Zhang, G He IEEE Transactions on Instrumentation and Measurement 62 (5), 869-879, 2013 | 110 | 2013 |
| A novel order tracking method for wind turbine planetary gearbox vibration analysis based on discrete spectrum correction technique G He, K Ding, W Li, X Jiao Renewable Energy 87, 364-375, 2016 | 101 | 2016 |
| Feature denoising and nearest–farthest distance preserving projection for machine fault diagnosis W Li, S Zhang, S Rakheja IEEE Transactions on Industrial Informatics 12 (1), 393-404, 2016 | 100 | 2016 |
| A deep adversarial transfer learning network for machinery emerging fault detection J Li, R Huang, G He, S Wang, G Li, W Li IEEE Sensors Journal 20 (15), 8413-8422, 2020 | 99 | 2020 |
| A robust weight-shared capsule network for intelligent machinery fault diagnosis R Huang, J Li, S Wang, G Li, W Li IEEE Transactions on Industrial Informatics 16 (10), 6466-6475, 2020 | 99 | 2020 |
| Feature extraction and classification of gear faults using principal component analysis W Li, T Shi, G Liao, S Yang Journal of Quality in Maintenance Engineering 9 (2), 132-143, 2003 | 83 | 2003 |
Zhuyun Chen / 陈祝云School of Mechanical & Automotive Engineering, South China University of Technology在 scut.edu.cn 的电子邮件经过验证
