基于机械装备状态监测大数据，采用深度学习方法，构建“端到端”的智能故障诊断模型，实现从原始监测数据智能提取故障特征并完成高精度诊断。

代表性论文 Selected publications:

1. 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 ESI highly cited and hot paper]
2. 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高被引论文、热点论文 ESI highly cited and hot paper]
3. 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 ESI highly cited paper]
4. 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, 0, 0. [ESI高被引论文、热点论文 ESI highly cited and hot paper]
5. 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.
6. 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 ESI highly cited paper]

基于机械装备状态监测大数据，采用深度学习方法，构建“端到端”的智能健康状态评估与预测模型，实现从原始监测数据智能提取装备退化特征并完成高精度剩余寿命预测。

代表性论文 Selected publications:

1. 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 ESI highly cited paper]
2. 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, 2022.
3. 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, 2021, 0, 0. 
4. 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高被引论文、热点论文 ESI highly cited and hot paper]
5. 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.
6. 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.

为解决大数据驱动的智能运维模型泛化能力不强的问题，提出深度迁移学习算法，提升变工况、变装备、变测点等状态的智能运维模型泛化性。

代表性论文 Selected publications:

1. 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 ESI highly cited and hot paper]
2. 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高被引论文、热点论文 ESI highly cited and hot paper]
3. 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 ESI highly cited paper]
4. 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 ESI highly cited paper]
5. 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高被引论文、热点论文 ESI highly cited and hot paper]
6. 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]
7. 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.

代表性论文 Selected publications:

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.

锂电池状态预测 Battery prognostics

1. Wei Zhang, Xiang Li*, Xu Li, “Deep Learning-Based Prognostic Approach for Lithium-ion Batteries with Adaptive Time-Series Prediction and On-Line Validation”, Measurement, 2020,164, 108052.

增材制造 Additive manufacturing

1. Xiang Li*, Xiaodong Jia, Qibo Yang, Jay Lee, “Quality Analysis in Metal Additive Manufacturing with Deep Learning”, Journal of Intelligent Manufacturing, 2020, 31 (8), 2003-2017.

核工业 Nuclear industry

1. Xiang Li*, Xin-Min Fu, Fu-Rui Xiong, Xiao-Ming Bai, “Deep Learning-Based Unsupervised Representation Clustering Methodology for Automatic Nuclear Reactor Operating Transient Identification”, Knowledge-Based Systems, 2020, 204, 106178.

半导体制造 Semiconductor manufacturing

1. Moslem Azamfar, Xiang Li*, Jay Lee, “Deep Learning-Based Domain Adaptation Method for Fault Diagnosis in Semiconductor Manufacturing”, IEEE Transactions on Semiconductor Manufacturing, 2020, 33 (3), 445-453.
2. Feng Zhu, Xiaodong Jia*, Marcella Miller, Xiang Li, Fei Li, Yinglu Wang, Jay Lee, “Methodology for Important Sensor Screening for Fault Detection and Classification in Semiconductor Manufacturing”, IEEE Transactions on Semiconductor Manufacturing, 2021, 34 (1), 65-73.
3. Haoshu Cai, Jianshe Feng*, Qibo Yang, Wenzhe Li, Xiang Li and Jay Lee, “A virtual metrology method with prediction uncertainty based on Gaussian process for chemical mechanical planarization”, Computers in Industry, 2020, 119, 103228.

工业机器人 Industrial robots

1. Qibo Yang, Xiang Li*, Haoshu Cai, Yuan-Ming Hsu, Jay Lee, Chun Hung Yang, Zong Li Li, Ming Yi Lin, “Fault prognosis of industrial robots in dynamic working regimes: find degradation in variations”, Measurement, 2020, 0, 0.

滚珠丝杠 Ball screw

1. Moslem Azamfar, Xiang Li*, Jay Lee, “Intelligent Ball Screw Fault Diagnosis Using A Deep Domain Adaptation Methodology”, Mechanism and Machine Theory, 2020, 151C, 103932.
2. Vibhor Pandhare*, Xiang Li, Marcella Miller, Xiaodong Jia, Jay Lee, “Intelligent Diagnostics of Ball Screw Fault through Indirect Sensing using Deep Domain Adaptation”, IEEE Transactions on Instrumentation & Measurement, 2020, 0, 0.

齿轮箱 Gearbox

1. Moslem Azamfar*, Jaskaran Singh, Xiang Li, Jay Lee, “Cross-domain gearbox diagnostics under variable working conditions with deep convolutional transfer learning”, Journal of Vibration and Control, 2020, 0, 0.

为解决多用户协同智能故障诊断与预测问题中数据隐私性等问题，提出多用户数据不出本地、仅交互模型的联邦学习方法，实现保证数据隐私性的协同建模。

代表性论文 Selected publications:

1. Wei Zhang, Xiang Li*, “Federated Transfer Learning for Intelligent Fault Diagnostics Using Deep Adversarial Networks with Data Privacy”, IEEE/ASME Transactions on Mechatronics, 2021, 0, 0. [ESI高被引论文 ESI highly cited paper]
2. 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 ESI highly cited paper]
3. 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.
4. Wei Zhang, Xiang Li*, “Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions”, Structural Health Monitoring, 2021, 0, 0.
5. 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 ESI highly cited paper]

建立基于视觉信号的装备智能运维、缺陷检测、故障诊断、寿命预测等方法，形成产线部署的软件与系统。

代表性论文 Selected 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, 2023.
2. 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.
3. Xiang Li*, Shahin Siahpour, Jay Lee, Yachao Wang and Jing Shi, “Deep Learning-Based Intelligent Process Monitoring of Directed Energy Deposition in Additive Manufacturing with Thermal Images”, Procedia Manufacturing, 48: 643-649, 48th North American Manufacturing Research Conference (NAMRC), Cincinnati, OH, US, 2020.
4. Shaojie Yang, Xiang Li*, Xiaodong Jia, Yinglu Wang, Haodong Zhao and Jay Lee, “Deep Learning-Based Intelligent Defect Detection of Cutting Wheels with Industrial Images in Manufacturing”, Procedia Manufacturing, 48: 902-907, 48th North American Manufacturing Research Conference (NAMRC), Cincinnati, OH, US, 2020.

代表性论文 Selected publications:

1. Xiang Li, and Jian-Qiao Sun*, “Signal Multiobjective Optimization for Urban Traffic Network”, IEEE Transactions on Intelligent Transportation Systems, 2018, 19:11, 3529-3537.
2. Xiang Li*, and Jian-Qiao Sun, “Multi-objective Optimal Predictive Control of Signals in Urban Traffic Network”, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 2019, 23:4, 370-388.
3. Xiang Li*, and Jian-Qiao Sun, “Turning Lane and Signal Optimization at Intersections with Multiple Objectives”, Engineering Optimization, 2019, 51:3, 484-502.

代表性论文 Selected publications:

1. Xiang Li, and Jian-Qiao Sun*, “Signal Multiobjective Optimization for Urban Traffic Network”, IEEE Transactions on Intelligent Transportation Systems, 2018, 19:11, 3529-3537.
2. Wei Zhang, Bing-Bing Han, Xiang Li, Qian Ding* and Jian-Qiao Sun, “Multiple-objective Design Optimization of Squirrel Cage for Squeeze Film Damper by Using Cell Mapping Method and Experimental Validation”, Mechanism and Machine Theory, 2019, 132, 66-79.
3. Xiang Li*, and Jian-Qiao Sun, “Intersection multi-objective optimization on signal setting and lane assignment”, Physica A: Statistical Mechanics and its Applications, 2019, 525, 1233-1246.