学术专著                                                                                                                                                                                                                                   

• 雷亚国, 杨彬. 大数据驱动的机械装备智能运维理论及应用[M]. 北京: 电子工业出版社, 2022. (工信学术出版基金资助)

• Yaguo Lei, Naipeng Li, Xiang Li. Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems[M]. Berlin: Springer, 2022. (参编第3、4章，国家科学技术出版基金资助)

  期刊论文                                                                                                                                                                                                                                                                   

• Bin Yang, Yaguo Lei, Xiang Li*, Naipeng Li. Targeted transfer learning through distribution barycenter medium for intelligent fault diagnosis of machines with data decentralization[J]. Expert Systems With Applications, 2024, 244: 122997. (中科院一区Top)

• Bin Yang, Yaguo Lei*, Xiang Li, Naipeng Li, Asoke K. Nandi. Label recovery and trajectory designable network for transfer fault diagnosis of machines with incorrect annotation[J]. IEEE/CAA Journal of Automatica Sinica, 2024, 11(4): 932-945. (中科院一区Top)

• Bin Yang, Yaguo Lei*, Xiang Li, Clive Roberts. Deep targeted transfer learning along designable adaptation trajectory for fault diagnosis across different machines[J]. IEEE Transactions on Industrial Electronics, 2023, 70(9): 9463-9473. (ESI热点论文, 中科院一区Top)

• Bin Yang, Yaguo Lei*, Songci Xu, Chi-Guhn Lee. An optimal transport-embedded similarity measure for diagnostic knowledge transferability analytics across machines[J]. IEEE Transactions on Industrial Electronics, 2022, 69(7): 7372-7382. (中科院一区Top)

• Bin Yang, Songci Xu, Yaguo Lei*, Chi-Guhn Lee, Edward Stewart, Clive Roberts. Multi-source transfer learning network to complement knowledge for intelligent diagnosis of machines with unseen faults[J]. Mechanical Systems and Signal Processing, 2022, 162: 108095. (中科院一区Top)

• Bin Yang, Chi-Guhn Lee, Yaguo Lei*, Naipeng Li, Na Lu. Deep partial transfer learning network: A method to selectively transfer diagnostic knowledge across related machines[J]. Mechanical Systems and Signal Processing, 2021, 156: 108095. (中科院一区Top)

• Bin Yang, Yaguo Lei*, Feng Jia, Naipeng Li, Zhaojun Du. A polynomial kernel induced distance metric to improve deep transfer learning for fault diagnosis of machines[J]. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9747-9757. (ESI高被引, 中科院一区Top)

• Bin Yang, Yaguo Lei*, Feng Jia, Saibo Xing. An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings[J]. Mechanical Systems and Signal Processing, 2019, 122: 692-706. (ESI热点论文, 中国百篇最具影响国际学术论文, 陕西省自然科学优秀论文二等奖, 中科院一区Top)

• Yaguo Lei*, Bin Yang, Xinwei Jiang, Feng Jia, Naipeng Li, Asoke K. Nandi. Applications of machine learning to machine fault diagnosis: A review and roadmap[J]. Mechanical Systems and Signal Processing, 2020, 138: 106587. (ESI热点论文, 中科院一区Top)

• Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang*. Intelligent Machinery Fault Diagnosis With Event-Based Camera[J]. IEEE Transactions on Industrial Informatics, 2024, 20(1): 380-389. (中科院一区Top)

• Shuhui Wang, Yaguo Lei, Bin Yang*, Xiang Li, Yue Shu, Na Lu. A graph neural network-based data cleaning method to prevent intelligent fault diagnosis from data contamination[J]. Engineering Applications of Artificial Intelligence, 2023, 126, Part C: 106905. (中科院二区Top)

• 雷亚国*, 杨彬, 李乃鹏, 李响, 武通海. 跨设备的机械故障靶向迁移诊断方法[J]. 机械工程学报, 2022, 58(12): 1-9.

• 雷亚国*, 杨彬, 杜兆钧, 吕娜. 大数据下机械装备故障的深度迁移诊断方法[J]. 机械工程学报, 2019, 55(7): 1-8. (中国精品科技期刊顶尖学术论文, 第七届中国科协优秀科技论文, 中国机械工程学会优秀论文)

  发明专利                                                                                                                                                                                                                                   

• 杨彬, 雷亚国, 李乃鹏, 司小胜. 域不对称因子加权的滚动轴承故障深度局部迁移诊断方法: 中国, ZL202010226934.2[P]. 授权日期: 2020-12-29.

• 雷亚国, 杨彬, 贾峰, 邢赛博. 基于正交化局部连接网络的机械装备健康状态识别方法: 中国, ZL201710784356.2[P]. 授权日期: 2020-03-24.

• 雷亚国, 杨彬, 李熹伟, 李乃鹏, 武通海. 一种滚动轴承诊断知识的跨设备可迁移性度量方法: 中国, ZL202110759629.4[P]. 授权日期: 2023-01-18.

• 雷亚国, 杜兆钧, 杨彬, 李乃鹏. 一种基于适配共享深度残差网络的机械故障迁移诊断方法: 中国, ZL201810920158.9[P]. 授权日期: 2021-05-04.

• 雷亚国, 王远, 杨彬, 李乃鹏. 多项式核植入特征分布适配的滚动轴承故障迁移诊断方法: 中国, ZL201910619506.3[P]. 授权日期: 2020-05-26.

• 雷亚国, 赵军, 杨彬, 李乃鹏, 王文彬, 何平. 一种多源滚动轴承健康状态融合的迁移智能诊断方法: 中国, ZL202110449135.6[P]. 授权日期: 2023-01-18.