郁明，男，1979年生，教授，博士生导师。2012年获新加坡南洋理工大学电气与电子工程博士学位，2011年1月-2013年8月新加坡南洋理工大学智能机器人实验室担任Research Fellow, 2013年9月-2014年10月在新加坡南洋理工大学Rolls-Royce@NTU联合实验室担任Research Fellow。2014年11月在合肥工业大学电气与自动化工程学院担任研究员（黄山青年学者），2016年担任博士生导师，2020年12月担任教授。教育部学位中心抽检学位论文评审专家，国家自然科学基金通讯评审专家。主要从事复杂系统故障诊断、剩余寿命预测、容错控制、预防性维护等方面的研究工作。主持国家自然科学基金、校应用科技成果培育计划等项目。发表学术论文50余篇，授权国家发明专利10余项。在Springer出版社出版学术专著一部。欢迎自动化、机器人、电气等专业的同学报考我的研究生。
科研项目：
国家自然科学基金面上项目，62173119，基于相干函数嵌入有限状态机的间歇故障下混杂系统异构元件健康监测，在研，主持，2022.01 – 2025.12
国家自然科学基金面上项目，61673154，基于灵敏度特征的混杂系统在线多故障诊断与预测方法研究，结题，主持，2017.01 – 2020.12
代表性论文：
[1] Junjie Chen, Ming Yu*, Bin Zhang, and Rensheng Zhu, “Remaining useful life prediction for hybrid systems under intermittent fault using doubly stochastic process model,” IEEE Transactions on Automation Science and Engineering, 2025, Conditionally Accepted.
[2] Ming Yu* and Haotian Lu, “Dynamic prognosis of hybrid systems under imperfect maintenance and intermittent faults with unknown features,” IEEE Transactions on Industrial Electronics, 2025, Accepted.
[3] Dun Lan, Ming Yu*, Hai Wang, and Bin Zhang, “Competitive degradation process based monitoring of steer-by-wire system under unknown degradation features,” Measurement Science and Technology, 2025, 36(1), art. no. 016216.
[4] Haotian Lu, Ming Yu*, and Bin Zhang, “Multistage prognosis for nonlinear electromechanical system with degradation coupling and maintenance,” IEEE Transactions on Industrial Informatics, 2024, 20(4): 6009-6018.
[5] Ming Yu*, Xianle Wu, Haotian Lu, and Bin Zhang, “Monitoring of electric scooter with intermittent faults and imperfect maintenance: A dynamic observation window approach,” IEEE Transactions on Instrumentation and Measurement, 2024, 73, art. no. 3504512.
[6] Ming Yu, Zhicheng Wang, Hai Wang*, Wuhua Jiang, and Rensheng Zhu, “Intermittent fault diagnosis and prognosis for steer-by-wire system using composite degradation model,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023, 13(2): 557-571.
[7] Ming Yu*, Jie Meng, Rensheng Zhu, Wuhua Jiang, and Qiang Shen, “Sensor fault diagnosis for uncertain dissimilar redundant actuation system of more electric aircraft via bond graph and improved principal component analysis,” Measurement Science and Technology, 2023, 34(1), art. no. 015120.
[8] Chenyu Xiao, Ming Yu*, Hai Wang, Bin Zhang, and Danwei Wang, “Prognosis of electric scooter with intermittent faults: Dual degradation processes approach,” IEEE Transactions on Vehicular Technology, 2022, 71(2): 1411-1425.
[9] Ming Yu*, Dun Lan, Canghua Jiang, Bin Xu, Danwei Wang, and Rensheng Zhu, “Hybrid condition monitoring of nonlinear mechatronic system using biogeography-based optimization particle filter and optimized extreme learning machine,” ISA Transactions, 2022, 120, 342-359.
[10] Chenyu Xiao, Ming Yu*, Bin Zhang, Hai Wang, and Canghua Jiang, “Discrete component prognosis for hybrid systems under intermittent faults,” IEEE Transactions on Automation Science and Engineering, 2021, 18(4): 1766-1777.
[11] Ming Yu*, Chenyu Xiao, and Bin Zhang, “Event-triggered discrete component prognosis of hybrid systems using degradation model selection,” IEEE Transactions on Industrial Electronics, 2021, 68(11):11470-11481.
[12] Ming Yu*, Dun Lan, Yunzhi Huang, Hai Wang, Canghua Jiang, and Linfeng Zhao, “Event-based sequential prognosis for uncertain hybrid systems with intermittent faults,” IEEE Transactions on Industrial Informatics, 2019, 15(8): 4455-4468.
[13] Ming Yu*, Chenyu Xiao, Wuhua Jiang, Shuanglong Yang, and Hai Wang, “Fault diagnosis for electromechanical system via extended analytical redundancy relations,” IEEE Transactions on Industrial Informatics, 2018, 14(12): 5233-5244.
[14] Ming Yu*, Hao Xia, Yigang He, Hai Wang, Canghua Jiang, Si Chen, Mengxin Li, and Juan Xu, “Scheduled health monitoring of hybrid systems with multiple distinct faults,” IEEE Transactions on Industrial Electronics, 2017, 64(2): 1517-1528.
[15] Ming Yu, Danwei Wang*, and Ming Luo, “An integrated approach to prognosis of hybrid systems with unknown mode changes,” IEEE Transactions on Industrial Electronics, 2015, 61(1): 503-515.
[16] Ming Yu, Danwei Wang*, and Ming Luo, “Model based prognosis for hybrid systems with mode-dependent degradation behaviors,” IEEE Transactions on Industrial Electronics, 2014, 61(1): 546-554.
[17] Ming Yu and Danwei Wang*, “Model-based health monitoring for a vehicle steering system with multiple faults of unknown types,” IEEE Transactions on Industrial Electronics, 2014, 61(7): 3574-3586.
[18] Ming Yu, Danwei Wang*, Ming Luo, Danhong Zhang, and Qijun Chen, “Fault detection, isolation and identification for hybrid systems with unknown mode changes and fault patterns,” Expert Systems with Applications, 2012, 39(11): 9955-9965.
[19] Ming Yu, Danwei Wang*, Ming Luo, and Lei Huang, “Prognosis of hybrid systems with multiple incipient faults: Augmented global analytical redundancy relations approach,” IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 2011, 41(3): 540-551.
[20] Ming Yu, Ming Luo, Shai Arogeti, Danwei Wang*, and Xinzheng Zhang, “Simultaneous fault and mode switching identification for hybrid systems based on particle swarm optimization,” Expert Systems with Applications, 2010, 37(4): 3000-3012.
[21] 郁明，程区奇，程瑞，非完美维修下线控转向系统间歇故障预测，仪器仪表学报，2024.
[22] 郁明，李旺林，蓝盾， 基于优化自适应阈值的非线性机电系统传感器故障检测和主动容错控制，仪器仪表学报，2022.
授权专利：
[1] 郁明，王志成，蓝盾， 程瑞，曾庆王； 一种线控转向系统的间歇故障诊断和剩余寿命预测方法，国家发明专利， ZL202310357486.3
[2] 郁明，杨柳，蓝盾，黄云志，平兆武；一种电动代步车系统的主动容错控制方法，国家发明专利，ZL202210237197.5
[3] 郁明，李旺林，黄云志，肖晨雨，卢昊天；一种非线性机电系统的主动容错控制方法，国家发明专利，ZL202210237180.X
[4] 郁明，孙路路，王海，姜苍华，赵林峰；基于双时间尺度无迹卡尔曼滤波的系统故障参数估计方法, 国家发明专利，ZL201811093396.3
[5] 郁明，李航，杨双龙，王海，姜苍华；基于双时间尺度粒子滤波的机电系统剩余寿命预测方法，国家发明专利，ZL201811081075.1
[6] 郁明，刘鑫，赵林峰，姜苍华，王海；一种基于BG-LFT模型的机电系统的多故障隔离方法，国家发明专利，ZL201811086082.0
[7] 郁明，肖晨雨，蓝盾，姜苍华；不确定混杂电路系统的渐变故障诊断和寿命预测方法，国家发明专利，ZL201910569868.6
[8] 郁明，肖晨雨，姜苍华，王海，杨双龙；一种电路系统的分布式故障诊断方法，国家发明专利，ZL201811082945.7
[9] 郁明，李航，王海，姜苍华，李梦昕，夏浩，陈思，肖晨雨；一种非线性机电系统的故障诊断方法，国家发明专利，ZL201810083967.9
[10] 郁明，孙路路，姜苍华，王海，夏浩，李梦昕，肖晨雨；一种基于键合图模型的电动代步车故障诊断和估计方法，国家发明专利，ZL201810083969.8
