| 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 | 471 | 2022 |
| Deep decoupling convolutional neural network for intelligent compound fault diagnosis R Huang, Y Liao, S Zhang, W Li Ieee Access 7, 1848-1858, 2018 | 180 | 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 | 148 | 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 | 145 | 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 | 144 | 2020 |
| 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 | 104 | 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 | 100 | 2020 |
| A multi-source weighted deep transfer network for open-set fault diagnosis of rotary machinery Z Chen, Y Liao, J Li, R Huang, L Xu, G Jin, W Li IEEE Transactions on Cybernetics 53 (3), 1982-1993, 2022 | 97 | 2022 |
| Deep ensemble capsule network for intelligent compound fault diagnosis using multisensory data R Huang, J Li, W Li, L Cui IEEE Transactions on Instrumentation and Measurement 69 (5), 2304-2314, 2019 | 84 | 2019 |
| Multiscale convolutional neural network with feature alignment for bearing fault diagnosis J Chen, R Huang, K Zhao, W Wang, L Liu, W Li IEEE Transactions on Instrumentation and Measurement 70, 1-10, 2021 | 79 | 2021 |
| Federated transfer learning for bearing fault diagnosis with discrepancy-based weighted federated averaging J Chen, J Li, R Huang, K Yue, Z Chen, W Li IEEE Transactions on Instrumentation and Measurement 71, 1-11, 2022 | 73 | 2022 |
| 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 | 60 | 2023 |
| WavCapsNet: An interpretable intelligent compound fault diagnosis method by backward tracking W Li, H Lan, J Chen, K Feng, R Huang IEEE Transactions on Instrumentation and Measurement 72, 1-11, 2023 | 52 | 2023 |
| Aero-engine remaining useful life prediction method with self-adaptive multimodal data fusion and cluster-ensemble transfer regression J Chen, D Li, R Huang, Z Chen, W Li Reliability Engineering & System Safety 234, 109151, 2023 | 38 | 2023 |
| Compound fault diagnosis for rotating machinery: State-of-the-art, challenges, and opportunities R Huang, J Xia, B Zhang, Z Chen, W Li Journal of dynamics, monitoring and diagnostics, 13-29, 2023 | 36 | 2023 |
| Dynamic distribution adaptation based transfer network for cross domain bearing fault diagnosis Y Liao, R Huang, J Li, Z Chen, W Li Chinese Journal of Mechanical Engineering 34 (1), 52, 2021 | 32 | 2021 |
| Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions J Li, R Huang, Z Chen, G He, KC Gryllias, W Li Advanced Engineering Informatics 55, 101883, 2023 | 31 | 2023 |
| Generalized open-set domain adaptation in mechanical fault diagnosis using multiple metric weighting learning network Z Chen, J Xia, J Li, J Chen, R Huang, G Jin, W Li Advanced Engineering Informatics 57, 102033, 2023 | 25 | 2023 |
| Deep self-supervised domain adaptation network for fault diagnosis of rotating machine with unlabeled data J Li, R Huang, J Chen, J Xia, Z Chen, W Li IEEE Transactions on Instrumentation and Measurement 71, 1-9, 2022 | 24 | 2022 |
| Intelligent fault diagnosis for machinery based on enhanced transfer convolutional neural network 陈祝云， 钟琪， 黄如意， 廖奕， 李霁蒲， 李巍华 Journal of Mechanical Engineering 57 (21), 96-105, 2021 | 22 | 2021 |
Weihua LiProf. with School of Mechanical & Automotive Engineering, South China University of Technology在 scut.edu.cn 的电子邮件经过验证
