| Artificial intelligence for fault diagnosis of rotating machinery: A review R Liu, B Yang, E Zio, X Chen Mechanical Systems and Signal Processing 108, 33-47, 2018 | 1785 | 2018 |
| Dislocated time series convolutional neural architecture: An intelligent fault diagnosis approach for electric machine R Liu, G Meng, B Yang, C Sun, X Chen IEEE Transactions on Industrial Informatics 13 (3), 1310-1320, 2016 | 340 | 2016 |
| Remaining useful life prediction based on a double-convolutional neural network architecture B Yang, R Liu, E Zio IEEE Transactions on Industrial Electronics 66 (12), 9521-9530, 2019 | 306 | 2019 |
| Multiscale kernel based residual convolutional neural network for motor fault diagnosis under nonstationary conditions R Liu, F Wang, B Yang, SJ Qin IEEE Transactions on Industrial Informatics 16 (6), 3797-3806, 2019 | 260 | 2019 |
| Fault diagnosis for a wind turbine generator bearing via sparse representation and shift-invariant K-SVD B Yang, R Liu, X Chen IEEE Transactions on Industrial Informatics 13 (3), 1321-1331, 2017 | 203 | 2017 |
| Time-frequency atoms-driven support vector machine method for bearings incipient fault diagnosis R Liu, B Yang, X Zhang, S Wang, X Chen Mechanical Systems and Signal Processing 75, 345-370, 2016 | 174 | 2016 |
| Simultaneous bearing fault recognition and remaining useful life prediction using joint-loss convolutional neural network R Liu, B Yang, AG Hauptmann IEEE Transactions on industrial informatics 16 (1), 87-96, 2019 | 153 | 2019 |
| Sparse time-frequency representation for incipient fault diagnosis of wind turbine drive train B Yang, R Liu, X Chen IEEE Transactions on Instrumentation and Measurement 67 (11), 2616-2627, 2018 | 82 | 2018 |
| Feature identification with compressive measurements for machine fault diagnosis Z Du, X Chen, H Zhang, H Miao, Y Guo, B Yang IEEE Transactions on Instrumentation and Measurement 65 (5), 977-987, 2016 | 53 | 2016 |
| Acoustic emission analysis for wind turbine blade bearing fault detection under time-varying low-speed and heavy blade load conditions Z Liu, B Yang, X Wang, L Zhang IEEE Transactions on Industry Applications 57 (3), 2791-2800, 2021 | 37 | 2021 |
| Compressed-sensing-based periodic impulsive feature detection for wind turbine systems Z Du, X Chen, H Zhang, B Yang IEEE Transactions on Industrial Informatics 13 (6), 2933-2945, 2017 | 34 | 2017 |
| Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection Z Du, X Chen, H Zhang, B Yang, Z Zhai, R Yan Journal of Sound and Vibration 400, 270-287, 2017 | 33 | 2017 |
| Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis H Zhang, X Chen, Z Du, B Yang Mechanical Systems and Signal Processing 94, 499-524, 2017 | 29 | 2017 |
| Fast nonlinear chirplet dictionary-based sparse decomposition for rotating machinery fault diagnosis under nonstationary conditions B Yang, Z Yang, R Sun, Z Zhai, X Chen IEEE Transactions on Instrumentation and Measurement 68 (12), 4736-4745, 2019 | 9 | 2019 |
| Self-supervised contrastive learning approach for bearing fault diagnosis with rare labeled data J Chen, B Yang, R Liu 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE …, 2022 | 5 | 2022 |
| Sparse components separation-based operational reliability assessment approach R Liu, B Yang, M Ma, X Chen, G Meng 2016 Prognostics and System Health Management Conference (PHM-Chengdu), 1-5, 2016 | 1 | 2016 |
| Sparse representation based on redundant dictionary and basis pursuit denoising for wind turbine gearbox fault diagnosis B Yang, R Liu, R Li, X Chen 2016 International Symposium on Flexible Automation (ISFA), 103-107, 2016 | 1 | 2016 |
| Industrial Big Data Analytical System in Industrial Cyber-Physical Systems Based on Coarse-to-Fine Deep Network R Liu, Q Zhang, Y Wang, Z Li, D Chen, SX Ding, Q Hu, B Yang IEEE Transactions on Industrial Cyber-Physical Systems 1, 359-370, 2023 | | 2023 |
Xuefeng ChenProfessor of Mechanical Engineering, Xi'an Jiaotong University在 mail.xjtu.edu.cn 的电子邮件经过验证
