| 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 | 1921 | 2018 |
| A review on empirical mode decomposition in fault diagnosis of rotating machinery Y Lei, J Lin, Z He, MJ Zuo Mechanical systems and signal processing 35 (1-2), 108-126, 2013 | 1793 | 2013 |
| Applications of machine learning to machine fault diagnosis: A review and roadmap Y Lei, B Yang, X Jiang, F Jia, N Li, AK Nandi Mechanical Systems and Signal Processing 138, 106587, 2020 | 1721 | 2020 |
| Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data F Jia, Y Lei, J Lin, X Zhou, N Lu Mechanical systems and signal processing 72, 303-315, 2016 | 1704 | 2016 |
| An intelligent fault diagnosis method using unsupervised feature learning towards mechanical big data Y Lei, F Jia, J Lin, S Xing, SX Ding IEEE Transactions on Industrial Electronics 63 (5), 3137-3147, 2016 | 1136 | 2016 |
| A hybrid prognostics approach for estimating remaining useful life of rolling element bearings B Wang, Y Lei, N Li, N Li IEEE Transactions on Reliability 69 (1), 401-412, 2018 | 1071 | 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 | 1066 | 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 | 942 | 2018 |
| Condition monitoring and fault diagnosis of planetary gearboxes: A review Y Lei, J Lin, MJ Zuo, Z He Measurement 48, 292-305, 2014 | 722 | 2014 |
| An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings B Yang, Y Lei, F Jia, S Xing Mechanical Systems and Signal Processing 122, 692-706, 2019 | 676 | 2019 |
| Application of the EEMD method to rotor fault diagnosis of rotating machinery Y Lei, Z He, Y Zi Mechanical Systems and Signal Processing 23 (4), 1327-1338, 2009 | 661 | 2009 |
| An improved exponential model for predicting remaining useful life of rolling element bearings N Li, Y Lei, J Lin, SX Ding IEEE Transactions on Industrial Electronics 62 (12), 7762-7773, 2015 | 552 | 2015 |
| Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs Y Lei, Z He, Y Zi, Q Hu Mechanical systems and signal processing 21 (5), 2280-2294, 2007 | 551 | 2007 |
| Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods Z Zhang, X Si, C Hu, Y Lei European Journal of Operational Research 271 (3), 775-796, 2018 | 530 | 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 | 507 | 2018 |
| Application of an improved kurtogram method for fault diagnosis of rolling element bearings Y Lei, J Lin, Z He, Y Zi Mechanical systems and signal processing 25 (5), 1738-1749, 2011 | 504 | 2011 |
| Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization F Jia, Y Lei, N Lu, S Xing Mechanical Systems and Signal Processing 110, 349-367, 2018 | 500 | 2018 |
| A model-based method for remaining useful life prediction of machinery Y Lei, N Li, S Gontarz, J Lin, S Radkowski, J Dybala IEEE Transactions on reliability 65 (3), 1314-1326, 2016 | 500 | 2016 |
| A new approach to intelligent fault diagnosis of rotating machinery Y Lei, Z He, Y Zi Expert Systems with applications 35 (4), 1593-1600, 2008 | 494 | 2008 |
| EEMD method and WNN for fault diagnosis of locomotive roller bearings Y Lei, Z He, Y Zi Expert Systems with Applications 38 (6), 7334-7341, 2011 | 341 | 2011 |
