【Monograph】Yaguo Lei, Naipeng Li, and Xiang Li, “Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems”, Springer, 2022.

[国家科学技术出版基金资助] [入选输出版优秀图书榜单] [出版社宣传报道链接]

【Textbook】Yaguo Lei, Xiang Li, Zhiliang Liu, Bin Yang, Ming J. Zuo. "Theories and Practices of Rotating Machinery Fault Diagnosis", Xi'an Jiaotong University Press, 2026.

1. Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang*, "Intelligent Machinery Fault Diagnosis With Event-Based Camera", IEEE Transactions on Industrial Informatics, 2024, 20(1): 380-389. [ESI热点论文]

2. 雷亚国，李熹伟，李响*，李乃鹏，杨彬，面向机械设备通用健康管理的智能运维大模型，机械工程学报，2025

3. Xiang Li, Yongxin Lin, Shaojie Yang, and Wei Zhang. "Intelligent domain-generalized second-life EV battery state-of-health estimation." Journal of Energy Storage 140 (2025): 118989.

4. Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang*, "Dynamic Vision-Based Machinery Fault Diagnosis With Cross-Modality Feature Alignment", IEEE/CAA Journal of Automatica Sinica, 2024, 11(10), 2068–2081. [ESI热点论文] [钱学森论文奖]

5. Xiang Li, Shupeng Yu, Xinrui Chen, Yaguo Lei, Bin Yang, and Naipeng Li. "XJTU-DV: Open-Source Dynamic Vision Dataset for Non-Contact Vibration Measurement and Fault Diagnosis of Mechanical Systems." Chinese Journal of Mechanical Engineering (2025): 100163. [公开发布动态视觉数据集]

6. Shupeng Yu, Xiang Li*, Yaguo Lei, Bin Yang, and Naipeng Li. "Dynamic Vision-Enabled Intelligent Micro-Vibration Estimation Method with Spatiotemporal Pattern Consistency." IEEE/CAA Journal of Automatica Sinica 12, no. 11 (2025): 2359-2361.

7. 李响，徐宜销，雷亚国*，李熹伟，李乃鹏，杨彬，面向旋转机械装备的智能故障诊断通用基础模型研究，西安交通大学学报，2025

8. Changhao Liu, Xiang Li, Xinrui Chen, and Samir Khan. "Neuromorphic computing-enabled generalized machine fault diagnosis with dynamic vision." Advanced Engineering Informatics 65 (2025): 103300. [ESI高被引论文]

9. Xinrui Chen, Xiang Li*, Shupeng Yu, Yaguo Lei, Naipeng Li, and Bin Yang. "Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing", IEEE/CAA Journal of Automatica Sinica, 2024, 11 (3): 788-790. [ESI高被引论文] [Prophesee官网报道]

10. Ruiyi Guang, Xiang Li, Yaguo Lei, Bin Yang, and Naipeng Li. "Dynamic vision-based machine vibration sensing and fault diagnosis with signal alignment and feature clustering." Engineering Applications of Artificial Intelligence 162 (2025): 112445.

11. 李响, 付春霖, 雷亚国, 李乃鹏*, 杨彬. 保证数据隐私的装备协同智能故障诊断联邦迁移学习方法. 机械工程学报, 2023, 59(6): 1-9. [机械工程学报报道链接]

12. Xiang Li, Yixiao Xu, Naipeng Li*, Bin Yang, Yaguo Lei, "Remaining useful life prediction with partial sensor malfunctions using deep adversarial networks", IEEE/CAA Journal of Automatica Sinica, 2023. [ESI热点论文][自动化学报报道链接]

13. Xiang Li, Wei Zhang*, Hui Ma, Zhong Luo, Xu Li, “Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning”, IEEE Transactions on Neural Networks and Learning Systems, 2022.

14. Wei Zhang, Ziwei Wang, Xiang Li*, "Blockchain-based decentralized federated transfer learning methodology for collaborative machinery fault diagnosis", Reliability Engineering & System Safety 229 (2023): 108885. [ESI高被引论文]

15. Xiang Li, Wei Zhang*, Xu Li, Hongshen Hao, "Partial Domain Adaptation in Remaining Useful Life Prediction With Incomplete Target Data", Journal of Manufacturing Systems, IEEE/ASME Transactions on Mechatronics, 2024. [ESI热点论文]

16. Xu Li, Chi Zhang, Xiang Li*, Wei Zhang, "Federated transfer learning in fault diagnosis under data privacy with target self-adaptation", Journal of Manufacturing Systems, 2023, 68: 523-535.

17. Wei Zhang, Xiang Li*, “Federated Transfer Learning for Intelligent Fault Diagnostics Using Deep Adversarial Networks with Data Privacy”, IEEE/ASME Transactions on Mechatronics, 2021. [ESI热点论文]

18. Wei Zhang, Xiang Li*, Hui Ma, Zhong Luo, Xu Li, “Universal Domain Adaptation in Fault Diagnostics with Hybrid Weighted Deep Adversarial Learning ”, IEEE Transactions on Industrial Informatics, 2021. [ESI热点论文]

19. Wei Zhang, Xiang Li*, Hui Ma, Zhong Luo, Xu Li, “Transfer Learning Using Deep Representation Regularization In Remaining Useful Life Prediction Across Operating Conditions”, Reliability Engineering & System Safety, 2021, 211, 107556. [ESI高被引论文]

20. Wei Zhang, Xiang Li*, Hui Ma, Zhong Luo, Xu Li, “Open Set Domain Adaptation In Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning”, IEEE Transactions on Industrial Informatics, 2021, 17: 11, 7445-7455. [ESI高被引论文]

21. 李杰, 李响, 许元铭, 杨绍杰, 孙可意. 工业人工智能及应用研究现状及展望. 自动化学报, 2020, 46(10): 2031−2044.

22. Wei Zhang, Xiang Li*, Hui Ma, Zhong Luo, Xu Li, “Federated Learning for Machinery Fault Diagnosis with Dynamic Validation and Self-Supervision”, Knowledge-Based Systems, 2021, 213, 106679. [ESI高被引论文]

23. Xiang Li, Wei Zhang, Qian Ding, and Xu Li*, “Diagnosing Rotating Machines with Weakly Supervised Data Using Deep Transfer Learning”, IEEE Transactions on Industrial Informatics, 2020, 16 (3), 1688-1697. [ESI高被引论文]

24. Wei Zhang, Xiang Li*, “Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions”, Structural Health Monitoring, 2021.

25. Xiang Li*, Wei Zhang, Nan-Xi Xu, and Qian Ding, “Deep Learning-Based Machinery Fault Diagnostics with Domain Adaptation Across Sensors At Different Places”, IEEE Transactions on Industrial Electronics, 2020, 67 (8), 6785-6794. [ESI高被引论文]

26. Xiang Li*, Wei Zhang, Qian Ding, and Jian-Qiao Sun, “Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation”, Journal of Intelligent Manufacturing, 2020, 31, 433-452. [ESI高被引论文]

27. Wei Zhang, Xiang Li*, Xiao-Dong Jia, Hui Ma, Zhong Luo, and Xu Li, “Machinery fault diagnosis with imbalanced data using deep generative adversarial networks”, Measurement, 2020, 152, 107377. [ESI高被引论文]

28. Xiang Li, Wei Zhang*, Hui Ma, Zhong Luo, Xu Li, “Partial Transfer Learning in Machinery Cross-Domain Fault Diagnostics Using Class-Weighted Adversarial Networks”, Neural Networks, 2020, 129, 313-322.

29. Xiang Li*, Xiaodong Jia, Yinglu Wang, Shaojie Yang, Haodong Zhao, Jay Lee, “Industrial Remaining Useful Life Prediction by Partial Observation Using Deep Learning with Supervised Attention”, IEEE/ASME Transactions on Mechatronics, 2020, 25 (5), 2241-2251.

30. Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li*, “Domain Generalization In Rotating Machinery Fault Diagnostics Using Deep Neural Networks”, Neurocomputing, 2020, 403, 409-420.

31. Xiang Li, Wei Zhang*, “Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics”, IEEE Transactions on Industrial Electronics, 2020, 0, 0. [ESI热点论文]

32. Xiang Li, Xu Li, Hui Ma*, “Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery”, Mechanical Systems and Signal Processing, 2020, 143, 106825.

33. Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li*, “Data Alignments in Machinery Remaining Useful Life Prediction Using Deep Adversarial Neural Networks”, Knowledge-Based Systems, 2020, 197, 105843.

34. Xiang Li*, Wei Zhang, and Qian Ding, “Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks”, IEEE Transactions on Industrial Electronics, 2019, 66:7, 5525-5534. [ESI热点论文]

35. Xiang Li*, Wei Zhang, and Qian Ding, “Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction”, Reliability Engineering & System Safety, 2019, 182, 208-218. [ESI热点论文]

36. Xiang Li*, Wei Zhang, Qian Ding, and Jian-Qiao Sun, “Multi-Layer domain adaptation method for rolling bearing fault diagnosis”, Signal Processing, 2019, 157, 180-197. [ESI热点论文]

37. Wei Zhang, Xiang Li*, and Qian Ding, “Deep residual learning-based fault diagnosis method for rotating machinery”, ISA Transactions, 2019, 95, 295-305. [ESI高被引论文]

38. Xiang Li*, Wei Zhang, and Qian Ding, “Understanding and Improving Deep Learning-Based Rolling Bearing Fault Diagnosis with Attention Mechanism”, Signal Processing, 2019, 161, 136-154. [ESI高被引论文]

39. Xiang Li*, Qian Ding, and Jian-Qiao Sun, “Remaining useful life estimation in prognostics using deep convolution neural networks”, Reliability Engineering & System Safety, 2018, 172, 1-11. [ESI高被引论文] [单篇引用1000+]

40. Xiang Li*, Wei Zhang, and Qian Ding, “A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning”, Neurocomputing, 2018, 310, 77-95. [ESI高被引论文]

41. Xiang Li, and Jian-Qiao Sun*, “Signal Multiobjective Optimization for Urban Traffic Network”, IEEE Transactions on Intelligent Transportation Systems, 2018, 19:11, 3529-3537.

• 智能服务 预测性维护 算法测评方法，GB/T 43555-2023
• 工业机器人 运行维护 第1部分：在线监测，GB/T 42983.1-2023
• 工业机器人 运行维护 第4部分：预测性维护，GB/T 42983.4-2023

硕士论文

1. 李响，俞舒鹏，雷亚国，李乃鹏，武通海，曹军义，王硕，杨彬，一种基于事件相机的滚动轴承故障诊断方法，2022，2022111619537

2. 李响，徐宜销，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于振动的旋转机械智能故障诊断大模型建模方法，2024，2024107341782

3. 李响，俞舒鹏，雷亚国，李乃鹏，杨彬，曹军义，武通海，动态视觉赋能的非接触式机械微振动特性分析与测量方法，2024，2024104955142

4. 李响，熊杰，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于事件相机数据统计的机械微振动视觉测量方法，2024，2024104955119

5. 李响，广睿祎，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于事件相机的非接触式机械振动监测与故障诊断方法，2023，2023105369863

6. 李响，陈欣瑞，雷亚国，李乃鹏，杨彬，曹军义，武通海，动态视觉赋能的非接触式装备迁移故障诊断方法，2023，202311624722X

7. 李响，陈欣瑞，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于事件相机与脉冲神经网络的变工况机械故障诊断方法，2023，2023111193609

8. 李响，王家辉，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于声发射信号的航空飞行器结构健康指标智能构建方法，2024，2024104317014

9. 李响，鲁凡，雷亚国，李乃鹏，杨彬，曹军义，武通海，航空飞行器结构声发射数据质量评估与智能损伤识别方法，2024，2024104955161

10. 李响，林永鑫，雷亚国，李乃鹏，杨彬，曹军义，武通海，杨慧欣，固体火箭发动机跨模态时序数据智能生成方法，2024，2024104955157

11. 李响，林永鑫，雷亚国，李乃鹏，杨彬，曹军义，武通海，杨慧欣，固体火箭发动机推力压强数据协同智能生成方法，2024，2024103779158

12. 李响，付春霖，雷亚国，李乃鹏，杨彬，曹军义，武通海，一种智能制造产线设备健康指标智能构建方法，2024，2024104226119

13. 李响，付春霖，雷亚国，李乃鹏，杨彬，曹军义，武通海，一种智能制造产线低质量监测大数据智能清洗方法，2023，2023115756716

14. 李响，陈欣瑞，雷亚国，李乃鹏，杨彬，曹军义，武通海，一种基于动态视觉与类脑计算的非接触式故障诊断方法，2023，2023108430670

15. 李响，徐宜销，雷亚国，李乃鹏，杨彬，曹军义，武通海，旋转机械装备状态监测大数据轻量化表征与智能诊断方法，2023，2023111451314

16. 李响，陈欣瑞，雷亚国，李乃鹏，杨彬，曹军义，武通海，基于增强事件视觉数据的滚动轴承智能故障诊断方法及系统，2023，2023104733227

17. 李响，何平，雷亚国，杨彬，李乃鹏，曹军义，武通海，一种轻量化通信的滚动轴承多用户协同智能 故障诊断方法, 2022, ZL202111551544.3

• 雷亚国，杨彬，李响，李乃鹏，高端装备智能诊断与预测，电子工业出版社，2024