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Xiang Li
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Remaining useful life estimation in prognostics using deep convolution neural networks
X Li, Q Ding, JQ Sun
Reliability Engineering & System Safety 172, 1-11, 2018
13662018
Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction
X Li, W Zhang, Q Ding
Reliability engineering & system safety 182, 208-218, 2019
4532019
Multi-layer domain adaptation method for rolling bearing fault diagnosis
X Li, W Zhang, Q Ding, JQ Sun
Signal processing 157, 180-197, 2019
3832019
Cross-domain fault diagnosis of rolling element bearings using deep generative neural networks
X Li, W Zhang, Q Ding
IEEE Transactions on Industrial Electronics 66 (7), 5525-5534, 2018
3572018
Deep residual learning-based fault diagnosis method for rotating machinery
W Zhang, X Li, Q Ding
ISA transactions 95, 295-305, 2019
3092019
Understanding and improving deep learning-based rolling bearing fault diagnosis with attention mechanism
X Li, W Zhang, Q Ding
Signal processing 161, 136-154, 2019
3012019
Machinery fault diagnosis with imbalanced data using deep generative adversarial networks
W Zhang, X Li, XD Jia, H Ma, Z Luo, X Li
Measurement 152, 107377, 2020
2862020
Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation
X Li, W Zhang, Q Ding, JQ Sun
Journal of Intelligent Manufacturing 31 (2), 433-452, 2020
2822020
Diagnosing rotating machines with weakly supervised data using deep transfer learning
X Li, W Zhang, Q Ding, X Li
IEEE transactions on industrial informatics 16 (3), 1688-1697, 2019
2542019
A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning
X Li, W Zhang, Q Ding
Neurocomputing 310, 77-95, 2018
2242018
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision
W Zhang, X Li, H Ma, Z Luo, X Li
Knowledge-Based Systems 213, 106679, 2021
2012021
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning
K Yu, TR Lin, H Ma, X Li, X Li
Mechanical Systems and Signal Processing 146, 107043, 2021
1942021
Deep learning-based machinery fault diagnostics with domain adaptation across sensors at different places
X Li, W Zhang, NX Xu, Q Ding
IEEE Transactions on Industrial Electronics 67 (8), 6785-6794, 2019
1782019
Universal domain adaptation in fault diagnostics with hybrid weighted deep adversarial learning
W Zhang, X Li, H Ma, Z Luo, X Li
IEEE Transactions on Industrial Informatics 17 (12), 7957-7967, 2021
1772021
Open-set domain adaptation in machinery fault diagnostics using instance-level weighted adversarial learning
W Zhang, X Li, H Ma, Z Luo, X Li
IEEE Transactions on Industrial Informatics 17 (11), 7445-7455, 2021
1572021
Deep learning-based partial domain adaptation method on intelligent machinery fault diagnostics
X Li, W Zhang
IEEE Transactions on Industrial Electronics 68 (5), 4351-4361, 2020
1512020
Deep learning-based prognostic approach for lithium-ion batteries with adaptive time-series prediction and on-line validation
W Zhang, X Li, X Li
Measurement 164, 108052, 2020
1472020
Partial transfer learning in machinery cross-domain fault diagnostics using class-weighted adversarial networks
X Li, W Zhang, H Ma, Z Luo, X Li
Neural Networks 129, 313-322, 2020
1402020
Federated transfer learning for intelligent fault diagnostics using deep adversarial networks with data privacy
W Zhang, X Li
IEEE/ASME Transactions on Mechatronics 27 (1), 430-439, 2021
1232021
Quality analysis in metal additive manufacturing with deep learning
X Li, X Jia, Q Yang, J Lee
Journal of Intelligent Manufacturing 31 (8), 2003-2017, 2020
1192020
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Artikelen 1–20