2023

• Ao Ding, Yong Qin, Biao Wang*, Xiaoqing Cheng, Limin Jia. An elastic expandable fault diagnosis method of three-phase motors using continual learning for class-added sample accumulations [J]. IEEE Transactions on Industrial Electronics, 2023, 1-10. DOI: 10.1109/TIE.2023.3301546 （New Work!）

• Ao Ding, Yong Qin, Biao Wang*, et al. A class-added continual learning method for motor fault diagnosis based on knowledge distillation of representation proximity behavior[C]. 2023 IEEE International Conference on Prognostics and Health Management (ICPHM). IEEE, 2023: 224-231. （优秀论文奖）

• Biao Wang, Xiangyu Ren, Yong Qin*, et al. A new convolutional prognostics network with adaptive kernels for estimating remaining useful life of bearings considering variable speed[C]. 2023 Prognostics and Health Management Conference (PHM). IEEE, 2023: 122-127.

• Xiangyu Ren, Haiquan Qiu, Dawei Chen, et al. A continual learning framework with adaptive synapses for remaining useful life prediction[C]. 2023 IEEE Global Reliability & Prognostics and Health Management Conference (PHM-HangZhou 2023). IEEE, 2023.

2022

• 王彪, 秦勇*，贾利民，程晓卿，曾春平，高一凡. 监测数据驱动的城轨列车轴箱轴承剩余寿命预测[J]. 西南交通大学学报, 2023, 58(3): 1-9.

• 任翔宇，秦勇，王彪*，贾利民，程晓卿. 基于博弈映射学习的多传感源信息融合三相电机智能故障诊断方法[J]. 电工技术学报, 2022, 1-14.

• Ao Ding, Yong Qin, Biao Wang*, Limin Jia, and Xiaoqing Cheng. Lightweight multiscale convolutional networks with adaptive pruning for intelligent fault diagnosis of train bogie bearings in edge computing scenarios [J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-13.（New Work!）

• Xiangyu Ren, Biao Wang*, Yong Qin, Limin Jia. Adversarial Embedding Fusion Network for Multi-sensor Fusion Fault Diagnosis of Wheelset Bearings[C]. 2022 Global Reliability and Prognostics and Health Management Conference (PHM-Yantai), 2022.

2021

• Biao Wang, Yaguo Lei*, Naipeng Li, and Wenting Wang. Multi-scale convolutional attention network for predicting remaining useful life of machinery [J]. IEEE Transactions on Industrial Electronics, 2021, 68(8): 7496-7504.（ESI热点论文、ESI高被引论文）

2020

• Biao Wang, Yaguo Lei*, Naipeng Li, and Ningbo Li. A hybrid prognostics approach for estimating remaining useful life of rolling element bearings [J]. IEEE Transactions on Reliability, 2020, 69(1): 401-412.（ESI热点论文、ESI高被引论文）

• Biao Wang, Yaguo Lei*, Tao Yan, Naipeng Li, and Liang Guo. Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery [J]. Neurocomputing, 2020, 379: 117-129.（ESI国际学术研究前沿、ESI高被引论文）

• Xinwei Jiang, Biao Wang, Yaguo Lei*, and Naipeng Li. An adaptable cost-sensitive imbalanced fault diagnosis method considering sample-significance information [C]. 2020 International Conference on Sensing, Diagnostics, Prognostics and Control, 2020.（Best Paper Award）

2019

• Biao Wang, Yaguo Lei*, Naipeng Li, and Tao Yan. Deep separable convolutional network for remaining useful life prediction of machinery [J]. Mechanical Systems and Signal Processing, 2019, 134: 106330.（ESI国际学术研究前沿、ESI高被引论文）

• Biao Wang, Tianyu Han, Yaguo Lei*, and Naipeng Li. Remaining useful life prediction based on deep residual attention network [C]. 2019 International Conference on Sensing, Diagnostics, Prognostics and Control, 2019.

• 雷亚国*，韩天宇，王彪，李乃鹏，闫涛，杨军．XJTU-SY滚动轴承加速寿命试验数据集解读 [J]．机械工程学报，2019，55(16)：1-6．（封面论文）

2017

• Biao Wang, Yaguo Lei*, Naipeng Li, and Jin Lin. An improved fusion prognostics method for remaining useful life prediction of bearings [C]. 2017 IEEE International Conference on Prognostics and Health Management, 2017.