| Machinery health prognostics: A systematic review from data acquisition to RUL prediction Y Lei, N Li, L Guo, N Li, T Yan, J Lin Mechanical systems and signal processing 104, 799-834, 2018 | 2021 | 2018 |
| A recurrent neural network based health indicator for remaining useful life prediction of bearings L Guo, N Li, F Jia, Y Lei, J Lin Neurocomputing 240, 98-109, 2017 | 1115 | 2017 |
| Deep convolutional transfer learning network: A new method for intelligent fault diagnosis of machines with unlabeled data L Guo, Y Lei, S Xing, T Yan, N Li IEEE Transactions on Industrial Electronics 66 (9), 7316-7325, 2018 | 987 | 2018 |
| A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines F Jia, Y Lei, L Guo, J Lin, S Xing Neurocomputing 272, 619-628, 2018 | 524 | 2018 |
| Machinery health indicator construction based on convolutional neural networks considering trend burr L Guo, Y Lei, N Li, T Yan, N Li Neurocomputing 292, 142-150, 2018 | 252 | 2018 |
| A new bearing fault diagnosis method based on modified convolutional neural networks J Zhang, S Yi, GUO Liang, GAO Hongli, H Xin, S Hongliang Chinese Journal of Aeronautics 33 (2), 439-447, 2020 | 240 | 2020 |
| Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery B Wang, Y Lei, T Yan, N Li, L Guo Neurocomputing 379, 117-129, 2020 | 239 | 2020 |
| Multifeatures fusion and nonlinear dimension reduction for intelligent bearing condition monitoring L Guo, H Gao, H Huang, X He, SC Li Shock and Vibration 2016 (1), 4632562, 2016 | 116 | 2016 |
| Remaining useful life prediction based on a general expression of stochastic process models N Li, Y Lei, L Guo, T Yan, J Lin IEEE Transactions on Industrial Electronics 64 (7), 5709-5718, 2017 | 105 | 2017 |
| YOLO-SLAM: A semantic SLAM system towards dynamic environment with geometric constraint W Wu, L Guo, H Gao, Z You, Y Liu, Z Chen Neural Computing and Applications, 1-16, 2022 | 91 | 2022 |
| Deep focus parallel convolutional neural network for imbalanced classification of machinery fault diagnostics A Duan, L Guo, H Gao, X Wu, X Dong IEEE Transactions on Instrumentation and Measurement 69 (11), 8680-8689, 2020 | 84 | 2020 |
| Instance-based ensemble deep transfer learning network: A new intelligent degradation recognition method and its application on ball screw L Zhang, L Guo, H Gao, D Dong, G Fu, X Hong Mechanical Systems and Signal Processing 140, 106681, 2020 | 67 | 2020 |
| Similarity-measured isolation forest: Anomaly detection method for machine monitoring data C Li, L Guo, H Gao, Y Li IEEE Transactions on Instrumentation and Measurement 70, 1-12, 2021 | 61 | 2021 |
| Online remaining useful life prediction of milling cutters based on multisource data and feature learning L Guo, Y Yu, H Gao, T Feng, Y Liu IEEE Transactions on Industrial Informatics 18 (8), 5199-5208, 2021 | 51 | 2021 |
| Pareto-optimal adaptive loss residual shrinkage network for imbalanced fault diagnostics of machines Y Yu, L Guo, H Gao, Y Liu, T Feng IEEE Transactions on Industrial Informatics 18 (4), 2233-2243, 2021 | 47 | 2021 |
| Deep convolution feature learning for health indicator construction of bearings L Guo, Y Lei, N Li, S Xing 2017 prognostics and system health management conference (phm-harbin), 1-6, 2017 | 47 | 2017 |
| On-line milling cutter wear monitoring in a wide field-of-view camera Z You, H Gao, L Guo, Y Liu, J Li Wear 460, 203479, 2020 | 45 | 2020 |
| Deep coupled joint distribution adaptation network: A method for intelligent fault diagnosis between artificial and real damages Y Tan, L Guo, H Gao, L Zhang IEEE Transactions on Instrumentation and Measurement 70, 1-12, 2020 | 42 | 2020 |
| Deep cost adaptive convolutional network: A classification method for imbalanced mechanical data X Dong, H Gao, L Guo, K Li, A Duan IEEE Access 8, 71486-71496, 2020 | 37 | 2020 |
| A data-flow oriented deep ensemble learning method for real-time surface defect inspection Y Liu, H Gao, L Guo, A Qin, C Cai, Z You IEEE Transactions on Instrumentation and Measurement 69 (7), 4681-4691, 2019 | 33 | 2019 |
