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李响

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代表性期刊论文 Selected Journal Publications

  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、高被引论文]
  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, 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、高被引论文]
  4. 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
  5. 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]
  6. 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]
  7. 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、高被引论文、研究前沿] [自动化学报报道链接]
  8. 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.
  9. 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、研究前沿]
  10. 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、高被引论文]
  11. 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.
  12. 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、高被引论文、研究前沿]
  13. 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、高被引论文、研究前沿]
  14. 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、研究前沿]
  15. 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、研究前沿]
  16. 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.
  17. 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、研究前沿]
  18. 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、研究前沿]
  19. Wei Zhang, Xiang Li*, “Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions”, Structural Health Monitoring, 2021.
  20. 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、研究前沿]
  21. 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]
  22. 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、研究前沿]
  23. 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.
  24. 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.
  25. 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.
  26. 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、高被引论文、研究前沿]
  27. 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.
  28. 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.
  29. 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高被引论文、热点论文、研究前沿]
  30. 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、高被引论文、研究前沿]
  31. 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、高被引论文、研究前沿]
  32. 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、研究前沿]
  33. 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]
  34. 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、研究前沿] [单篇引用1000+]
  35. 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、研究前沿]
  36. Xiang Li, and Jian-Qiao Sun*, “Signal Multiobjective Optimization for Urban Traffic Network”, IEEE Transactions on Intelligent Transportation Systems, 2018, 19:11, 3529-3537.
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