| Fault diagnosis based on deep learning F Lv, C Wen, Z Bao, M Liu 2016 American control conference (ACC), 6851-6856, 2016 | 237 | 2016 |
| A review of data driven-based incipient fault diagnosis CL Wen, FY Lv, ZJ Bao, MQ Liu Acta Automatica Sinica 42 (9), 1285-1299, 2016 | 134 | 2016 |
| Weighted time series fault diagnosis based on a stacked sparse autoencoder F Lv, C Wen, M Liu, Z Bao Journal of Chemometrics 31 (9), e2912, 2017 | 78 | 2017 |
| Representation learning based adaptive multimode process monitoring F Lv, C Wen, M Liu Chemometrics and Intelligent Laboratory Systems 181, 95-104, 2018 | 23 | 2018 |
| Interpretable fault detection using projections of mutual information matrix F Lv, S Yu, C Wen, JC Principe Journal of the Franklin Institute 358 (7), 4028-4057, 2021 | 11 | 2021 |
| Higher‐order correlation–based multivariate statistical process monitoring F Lv, C Wen, M Liu, Z Bao Journal of Chemometrics 32 (8), e3033, 2018 | 11 | 2018 |
| A review of fault diagnosis methods based on deep learning C Wen, F Lv Acta Electronica Sinica 42 (1), 234-248, 2020 | 6 | 2020 |
| Dynamic reconstruction based representation learning for multivariable process monitoring F Lv, C Wen, M Liu Journal of Process Control 81, 112-125, 2019 | 6 | 2019 |
| Stacked sparse auto encoder network based multimode process monitoring F Lv, X Fan, C Wen, Z Bao 2018 International Conference on Control, Automation and Information …, 2018 | 5 | 2018 |
| A Review of Data-Driven Micro-Fault Diagnosis Methods C Wen, F Lv, Z Bao Acta Automatica Sinica 42 (09), 1285-1299, 2016 | 5 | 2016 |
| On-line monitoring transformer’s bushing insulation based on its tap capacitive divider. J Y Liu, FC Lv, CG Li High Voltage Apparatus 40 (2), 121-123, 2004 | 5 | 2004 |
| Causality-embedded reconstruction network for high-resolution fault identification in chemical process F Lv, X Bi, Z Xu, J Zhao Process Safety and Environmental Protection 186, 1011-1033, 2024 | 4 | 2024 |
| Adaptive learning region importance for region‐based image retrieval X Yang, F Lv, L Cai, D Li IET Computer Vision 9 (3), 368-377, 2015 | 4 | 2015 |
| Incipient fault detection and isolation with Cauchy–Schwarz divergence: A probabilistic approach F Lv, S Yu, H Ye, J Zhao, C Wen Journal of the Franklin Institute 361 (15), 107114, 2024 | 2 | 2024 |
| Unsupervised transfer learning for fault diagnosis across similar chemical processes R Qin, F Lv, H Ye, J Zhao Process Safety and Environmental Protection 190, 1011-1027, 2024 | 2 | 2024 |
| Recommender system for telecom packages based on the deep & cross network C Shi, W Wang, S Wei, F Lv | 2 | 2021 |
| Mutual information matrix for interpretable fault detection F Lv, S Yu, C Wen, JC Principe arXiv preprint arXiv:2007.10692, 2020 | 1 | 2020 |
| A unified model integrating Granger causality-based causal discovery and fault diagnosis in chemical processes F Lv, B Yang, S Yu, S Zou, X Wang, J Zhao, C Wen Computers & Chemical Engineering, 109028, 2025 | | 2025 |
| A new rotating machinery fault diagnosis method based on data driven and expert knowledge Z Li, N Zhang, F Lv, J Yang, R Wang International Journal of Quality Engineering and Technology 10 (1), 1-18, 2024 | | 2024 |
| A fault diagnosis online method of railway track based on knowledge transfer learning Z Li, F Lv, J Yang, X Li IET Conference Proceedings CP850 2023 (23), 69-75, 2023 | | 2023 |