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吴云凯 副教授

自动化学院

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个人邮箱：wuyunkaigxy@163.com

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  • 个人简介

  • 研究方向

  • 科研团队

  • 科研项目

  • 获奖动态

  • 教学随笔

  • 教育经历

  • 课程教学

  • 论文著作

  • 科研论文

  • 科研横向项目

  • 科研纵向项目

  • 科研专利

  • 科研动物专利

  • 吴云凯(1989-)，男，江苏镇江人，南京航空航天大学控制理论与控制工程专业博士毕业，澳大利亚阿德莱德大学访问学者，现任江苏科技大学自动化学院副教授，博士/硕士研究生导师，学科办公室主任。

            主要研究方向为故障检测、诊断与可靠性理论在交通控制系统中的应用。近年来发表学术专著1部，在国内外权威期刊及重要的国际学术会议上发表论文30余篇 (ESI高被引论文3篇)。主持国家自然科学基金-面上项目2项、国家自然科学基金-青年基金1项、科技部国际合作项目1项、江苏省自然科学基金-面上项目1项、市厅级基础研究专项1项，获省部级科技进步奖3项，江苏省“青蓝工程”优秀青年骨干教师。现担任江苏省自动化学会理事、中国自动化学会青年工作委员会委员、中国自动化学会技术过程的故障诊断与安全性专业委员会委员、江苏省自动化学会自主无人系统专业委员会委员。


    科技/竞赛奖项
            [1] 2024年河南省科学技术进步二等奖. 大尺寸硬质合金部件高效钎焊技术与装备. 
            [2] 2024“华为杯”第二十一届中国研究生数学建模竞赛，国赛三等奖，指导教师.
            [3] 2025“华为杯”第二十二届中国研究生数学建模竞赛，国赛二等奖，指导教师.
            [4] 2025中国自动化学会自然科学奖二等奖. 网络环境下多无人艇协同控制及应用. 


    学术兼职
            [1] 江苏省自动化学会理事
            [2] 中国自动化学会青年工作委员会委员（第九、十届）
            [3] 中国自动化学会技术过程的故障诊断与安全性专业委员会委员
            [4] 江苏省自动化学会自主无人系统专业委员会委员


    指导学生
            [1] 江苏科技大学2022届本科优秀毕业设计（论文）指导教师
            [2] 2022年江苏科技大学校级“优秀研究生学位论文” 指导教师


    人才项目/头衔
            [1] 2022年度镇江市青年科技人才托举工程；
            [2] 2023年江苏省“青蓝工程”优秀青年骨干教师
            [3] 2024年江苏科技大学“深蓝杰出人才”


    个人主页及相关报道
            [1] 江苏科技大学2024年校级高水平科研成果刊登：http://www.just.edu.cn/news/2024/1113/c11145a352998/page.htm


    （团队实行周例会制度，单数周个人线下交流课题、双数周团队集体例会；鼓励有读博深造和企业就业意向的考生报考）


  • [1]高速列车牵引控制系统的故障诊断与容错控制

    [2]无人艇/船的故障检测、诊断与预测





    • 科研项目

      科研项目情况

      [1]基于ToMFIR残差架构的高速列车牵引传动系统早期故障诊断研究，国家自然科学基金-面上项目，2026.1-2029.12，项目经费：50 万元，项目编号：62573213，主持

      [2]复杂工况下高速列车牵引系统早期故障智能诊断与预测方法研究，国家自然科学基金-面上项目，2022.1-2025.12，项目经费：58 万元，项目编号：62173164，主持

      [3]基于ToMFIR与键合图理论的动车组牵引传动系统早期故障诊断方法研究，国家自然科学基金-青年基金，2019.1-2021.12，项目经费：27 万元，项目编号：61803185，主持

      [4]CRH动车组列车牵引控制系统早期故障诊断与预测方法，科技部-中国北马其顿科技合作委员会第6届例会人员交流项目 (科技部国际合作项目)，2020.1-2021.12，项目经费：9 万元，项目编号：19-6-3，主持

      [5]基于图论与解析模型相结合的高速列车信息控制系统早期故障实时诊断与应用验证，江苏省自然科学基金-面上项目，2020.7-2023.6，项目经费：10 万元，项目编号：BK20201451，主持

      [6]动车组电力牵引系统早期故障智能诊断与性能退化评估机理研究，2024年度镇江市基础研究专项，2024.9-2026.8，项目经费：10 万元，项目编号：JC2024014，主持

      [7]L921A低碳中合金调质钢激光-MIG复合焊接机理分析及疲劳性能研究，企业横向课题（沪东中华造船（集团）有限公司），2023.03-2025.03，项目经费：82万，主持；

      [8]不平衡样本下基于定量质量评价的搅拌摩擦焊系统故障诊断方法研究，国家自然科学基金-青年基金，2023.1-2025.12，项目经费：30 万元，项目编号：62203192，参研

      [9]高速列车信息控制系统微小和复合故障的实时诊断理论与预测方法，国家自然科学基金-重大项目，2015.1-2019.12，项目经费：320 万元，项目编号：61490703，参与人 (5/10，已结题)

      [10]高速列车牵引系统闭环结构下的故障诊断与容错控制研究, 国家自然科学基金-面上项目，2016.1-2019.12，项目经费：65 万元，项目编号：61573180，参与人 (3/8，已结题)

      [11]基于不确定信息的轧制过程故障预测与诊断关键技术研究，国家自然科学基金-面上项目，2014.1-2017.12，项目经费：60 万元，项目编号：61374141，参与人 (3/7，已结题)


    • 论文著作

      论文

      [1] Yunkai Wu, Bin Jiang and Ningyun Lu. A descriptor system approach for estimation of incipient faults with application to high-speed railway traction devices. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(10): 2108~2118. (ESI高被引论文，中科院一区，SCI收录，IF:13.451)
      [2] Yunkai Wu, Bin Jiang and Yulong Wang. Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains, ISA Transactions, 2020, 99: 488~495. (ESI高被引论文，中科院二区，SCI收录，IF:4.343)
      [3] Yunkai Wu, Bin Jiang and Peng Shi. Incipient fault diagnosis for T-S fuzzy systems with application to high-speed railway traction devices. IET Control Theory & Applications, 2016, 10(17): 2286~2297.  (SCI收录，IF:2.048)
      [4] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Multiple incipient sensor fault diagnosis with application to high-speed railway traction devices. ISA Transactions, 2017, 67: 183~192.
      (SCI收录，IF:2.600)
      [5] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. ToMFIR-based incipient fault detection and estimation for high-speed rail vehicle suspension system. Journal of the Franklin Institute, 2015, 352(4): 1672~1692. (SCI收录，IF:2.327)
      [6] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Bayesian network based fault prognosis via bond graph modeling of high-speed railway traction device. Mathematical Problems in Engineering, 2015, 1~12. (SCI收录，IF:0.644)
      [7] 姜斌, 吴云凯, 陆宁云, 冒泽慧. 高速列车牵引系统故障诊断与预测技术综述. 控制与决策, 2018, 33(5): 841~855. (EI收录)
      [8] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. ToMFIR-based detection and estimation for incipient actuator faults in a class of closed-loop nonlinear systems. IFAC Proceedings Volumes, 2014, 47(3): 1096~1101.
      [9] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. Detection and isolation of multiple incipient sensor faults with application to high-speed railway traction motors. Proceedings of the 35st Chinese Control Conference, Chengdu, China, July 27-29, 2016: 6558~6563.
      [10] Yunkai Wu, Bin Jiang and Ningyun Lu. Incipient winding fault detection and isolation for induction motors of high-speed trains. Prognostics and System Health Management Conference (PHM-2017 Harbin), Harbin, China, July 9-12, 2017: 10.1109/PHM.2017.8079108.
      [11] Yunkai Wu, Bin Jiang, Zhiyu Zhu and Qingjun Zeng. Data-driven based ToMFIR design with application to incipient fault detection in high-speed rail vehicle suspension system. 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Process, Xiamen, China, July 5-7, 2019: 645-650.
      [12] 柳春, 姜斌, 张柯, 吴云凯. 带扰动的线性系统微小故障早期诊断方法. 上海交通大学学报（自然科学版）, 2015, 49(6): 889~896.
      [13] 吴国政, 吴云凯, 张兆田, 韩军伟. 浅析人工智能学科基金项目申请资助情况及展望. 自动化学报, 2020, 46(12): 2711~2718.
      [14] 苏宇, 吴云凯*, 付俊, Gorjan Nadzinski. 基于数据驱动的CRH 高速列车悬挂系统早期故障检测. 控制与决策, 2022, 37(4): 982-988. (EI收录)
      [15] 吴云凯, 胡大海, 朱志宇, 曾庆军. 基于自适应阈值与扩张状态滑模观测器的AUV 执行机构故障检测与估计. 控制理论与应用, 2023, 40(7): 1216-1223. (EI收录)
      [16] Dahai Hu, Yunkai Wu, Yang Zhou, et al. Actuator Fault Detection for Automation Underwater Vehicle via Extended State Observer and Adaptive Threshold[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4106-4111.
      [17] Xiangqian Liu, Yunkai Wu, Yang Zhou, et al. Improved Deep PCA based Incipient Fault Detection with Application on CRH Traction System[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4118-4123.
      [18] Yunkai Wu, Xiangqian Liu, Yang Zhou. Deep PCA-based Incipient Fault Diagnosis and Diagnosability Analysis of High-Speed Railway Traction System via FNR Enhancement[J]. Machines, 2023, 11(4): 475. (ESI高被引论文，中科院三区，SCI收录)
      [19] Yunkai Wu, Xiangqian Liu, Yu-Long Wang, et al. Improved Deep PCA and Kullback-Leibler Divergence based Incipient Fault Detection and Isolation of High-speed Railway Traction Devices [J]. Sustainable Energy Technologies and Assessments, 2023, 57(10):103208. (中科院二区，SCI收录)
      [20] 吴云凯, 胡大海, 付俊，周扬. 基于故障描述因子与多观测器同步协作的AUV执行机构故障隔离与辨识[J]. 控制与决策, 2024, 39(6):2005-2012.
      [21] Yunkai Wu, Aodong Wang, Yang Zhou*, et al. Fault Diagnosis of Autonomous Underwater Vehicle with Missing Data Based on Multi-Channel Full Convolutional Neural Network [J]. Machines, 2023, 11(10): 960. (中科院三区，SCI收录)
      [22] Kangyue Fang, Yunkai Wu, Yang Zhou, et al. Incipient Fault Detection of CRH Suspension system based on PRPCA and Wasserstein Distance[C]//2023 42st Chinese Control Conference (CCC). IEEE, 2023: 5082-5087.
      [23] Yunkai Wu, Yu Su, Yu-Long Wang and Peng Shi*. T-S Fuzzy Data-Driven ToMFIR with Application to Incipient Fault Detection and Isolation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(7):7921-7932. (中科院一区，SCI收录)
      [24] Zimu Zhang, Yunkai Wu*, Yang Zhou and Dahai Hu. Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints. Sensors, 2024, 24(10): 3029. (中科院三区，SCI收录)
      [25] Yunkai Wu, Tianxiang Ji, Yang Zhou* and Yijin Zhou. Support Vector Machine-Based Fault Diagnosis under Data Imbalance with Application to High-Speed Train Electric Traction Systems [J]. Machines, 2024, 12(8): 582. (中科院三区，SCI收录)
      [26] Yunkai Wu, Yu Su and Peng Shi*. Data-Driven ToMFIR-Based Incipient Fault Detection and Estimation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Industrial Informatics, 2025, 21(1): 613-622. (中科院一区，SCI收录)
      [27] Zefan Zhu, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and YengChai Soh. ToMFIR and Auxiliary Signals based Active Incipient Fault Detection for Autonomous Underwater Vehicle Thrusters[C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4900-4905.
      [28] Xuansen Wang, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and Qingjun Zeng. Fault Prediction of High-Speed Train Suspension Systems based on Transformer with Improved Temporal Distribution Matching Algorithm [C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4949-4954.
      [29] Kang Feng, Yunkai Wu*, Yang Zhou and Yijin Zhou. Incipient Fault Detection and Recognition of China Railway High-Speed (CRH) Suspension System Based on Probabilistic Relevant Principal Component Analysis (PRPCA) and Support Vector Machine (SVM) [J]. Machines, 2024, 12(12): 832. (中科院三区，SCI收录)

      [30]Yunkai Wu, Yu Tian, Yang Zhou*. KICA-DPCA-Based Fault Detection of High-Speed Train Traction Motor Bearings [J]. Machines, 2025, 13(7): 552. (中科院三区，SCI收录)

      [31]Yunkai Wu*, Zefan Zhu, Peng Shi and Yueyang Li.  Active fault diagnosis for AUV over-actuated systems based on UIOs and control allocation[J]. ISA Transactions, 2025, 166: 80-88. (中科院二区，SCI收录)

      [32]Kang Feng, Yunkai Wu*, Yang Zhou and Zhoujie Lian. Data-Driven ToMFIR-based Active Incipient Fault Detection for the Suspension System of High-Speed Trains[J]. IEEE Access, 2025, 14: 9851-9858.  (中科院四区，SCI收录)

      [33]Yunkai Wu*, Yu Tian, Yang Zhou, Xiangqian Liu. Deep-PCA and MSPCA based fault diagnosis of high-speed train traction systems under missing data conditions[J]. ISA Transactions, 2025, 10.1016/j.isatra.2025.10.051 (中科院二区，SCI收录)











    • 科研项目

      科研项目情况

      [1]基于ToMFIR残差架构的高速列车牵引传动系统早期故障诊断研究，国家自然科学基金-面上项目，2026.1-2029.12，项目经费：50 万元，项目编号：62573213，主持

      [2]复杂工况下高速列车牵引系统早期故障智能诊断与预测方法研究，国家自然科学基金-面上项目，2022.1-2025.12，项目经费：58 万元，项目编号：62173164，主持

      [3]基于ToMFIR与键合图理论的动车组牵引传动系统早期故障诊断方法研究，国家自然科学基金-青年基金，2019.1-2021.12，项目经费：27 万元，项目编号：61803185，主持

      [4]CRH动车组列车牵引控制系统早期故障诊断与预测方法，科技部-中国北马其顿科技合作委员会第6届例会人员交流项目 (科技部国际合作项目)，2020.1-2021.12，项目经费：9 万元，项目编号：19-6-3，主持

      [5]基于图论与解析模型相结合的高速列车信息控制系统早期故障实时诊断与应用验证，江苏省自然科学基金-面上项目，2020.7-2023.6，项目经费：10 万元，项目编号：BK20201451，主持

      [6]动车组电力牵引系统早期故障智能诊断与性能退化评估机理研究，2024年度镇江市基础研究专项，2024.9-2026.8，项目经费：10 万元，项目编号：JC2024014，主持

      [7]L921A低碳中合金调质钢激光-MIG复合焊接机理分析及疲劳性能研究，企业横向课题（沪东中华造船（集团）有限公司），2023.03-2025.03，项目经费：82万，主持；

      [8]不平衡样本下基于定量质量评价的搅拌摩擦焊系统故障诊断方法研究，国家自然科学基金-青年基金，2023.1-2025.12，项目经费：30 万元，项目编号：62203192，参研

      [9]高速列车信息控制系统微小和复合故障的实时诊断理论与预测方法，国家自然科学基金-重大项目，2015.1-2019.12，项目经费：320 万元，项目编号：61490703，参与人 (5/10，已结题)

      [10]高速列车牵引系统闭环结构下的故障诊断与容错控制研究, 国家自然科学基金-面上项目，2016.1-2019.12，项目经费：65 万元，项目编号：61573180，参与人 (3/8，已结题)

      [11]基于不确定信息的轧制过程故障预测与诊断关键技术研究，国家自然科学基金-面上项目，2014.1-2017.12，项目经费：60 万元，项目编号：61374141，参与人 (3/7，已结题)


    • 论文著作

      论文

      [1] Yunkai Wu, Bin Jiang and Ningyun Lu. A descriptor system approach for estimation of incipient faults with application to high-speed railway traction devices. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(10): 2108~2118. (ESI高被引论文，中科院一区，SCI收录，IF:13.451)
      [2] Yunkai Wu, Bin Jiang and Yulong Wang. Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains, ISA Transactions, 2020, 99: 488~495. (ESI高被引论文，中科院二区，SCI收录，IF:4.343)
      [3] Yunkai Wu, Bin Jiang and Peng Shi. Incipient fault diagnosis for T-S fuzzy systems with application to high-speed railway traction devices. IET Control Theory & Applications, 2016, 10(17): 2286~2297.  (SCI收录，IF:2.048)
      [4] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Multiple incipient sensor fault diagnosis with application to high-speed railway traction devices. ISA Transactions, 2017, 67: 183~192.
      (SCI收录，IF:2.600)
      [5] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. ToMFIR-based incipient fault detection and estimation for high-speed rail vehicle suspension system. Journal of the Franklin Institute, 2015, 352(4): 1672~1692. (SCI收录，IF:2.327)
      [6] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Bayesian network based fault prognosis via bond graph modeling of high-speed railway traction device. Mathematical Problems in Engineering, 2015, 1~12. (SCI收录，IF:0.644)
      [7] 姜斌, 吴云凯, 陆宁云, 冒泽慧. 高速列车牵引系统故障诊断与预测技术综述. 控制与决策, 2018, 33(5): 841~855. (EI收录)
      [8] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. ToMFIR-based detection and estimation for incipient actuator faults in a class of closed-loop nonlinear systems. IFAC Proceedings Volumes, 2014, 47(3): 1096~1101.
      [9] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. Detection and isolation of multiple incipient sensor faults with application to high-speed railway traction motors. Proceedings of the 35st Chinese Control Conference, Chengdu, China, July 27-29, 2016: 6558~6563.
      [10] Yunkai Wu, Bin Jiang and Ningyun Lu. Incipient winding fault detection and isolation for induction motors of high-speed trains. Prognostics and System Health Management Conference (PHM-2017 Harbin), Harbin, China, July 9-12, 2017: 10.1109/PHM.2017.8079108.
      [11] Yunkai Wu, Bin Jiang, Zhiyu Zhu and Qingjun Zeng. Data-driven based ToMFIR design with application to incipient fault detection in high-speed rail vehicle suspension system. 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Process, Xiamen, China, July 5-7, 2019: 645-650.
      [12] 柳春, 姜斌, 张柯, 吴云凯. 带扰动的线性系统微小故障早期诊断方法. 上海交通大学学报（自然科学版）, 2015, 49(6): 889~896.
      [13] 吴国政, 吴云凯, 张兆田, 韩军伟. 浅析人工智能学科基金项目申请资助情况及展望. 自动化学报, 2020, 46(12): 2711~2718.
      [14] 苏宇, 吴云凯*, 付俊, Gorjan Nadzinski. 基于数据驱动的CRH 高速列车悬挂系统早期故障检测. 控制与决策, 2022, 37(4): 982-988. (EI收录)
      [15] 吴云凯, 胡大海, 朱志宇, 曾庆军. 基于自适应阈值与扩张状态滑模观测器的AUV 执行机构故障检测与估计. 控制理论与应用, 2023, 40(7): 1216-1223. (EI收录)
      [16] Dahai Hu, Yunkai Wu, Yang Zhou, et al. Actuator Fault Detection for Automation Underwater Vehicle via Extended State Observer and Adaptive Threshold[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4106-4111.
      [17] Xiangqian Liu, Yunkai Wu, Yang Zhou, et al. Improved Deep PCA based Incipient Fault Detection with Application on CRH Traction System[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4118-4123.
      [18] Yunkai Wu, Xiangqian Liu, Yang Zhou. Deep PCA-based Incipient Fault Diagnosis and Diagnosability Analysis of High-Speed Railway Traction System via FNR Enhancement[J]. Machines, 2023, 11(4): 475. (ESI高被引论文，中科院三区，SCI收录)
      [19] Yunkai Wu, Xiangqian Liu, Yu-Long Wang, et al. Improved Deep PCA and Kullback-Leibler Divergence based Incipient Fault Detection and Isolation of High-speed Railway Traction Devices [J]. Sustainable Energy Technologies and Assessments, 2023, 57(10):103208. (中科院二区，SCI收录)
      [20] 吴云凯, 胡大海, 付俊，周扬. 基于故障描述因子与多观测器同步协作的AUV执行机构故障隔离与辨识[J]. 控制与决策, 2024, 39(6):2005-2012.
      [21] Yunkai Wu, Aodong Wang, Yang Zhou*, et al. Fault Diagnosis of Autonomous Underwater Vehicle with Missing Data Based on Multi-Channel Full Convolutional Neural Network [J]. Machines, 2023, 11(10): 960. (中科院三区，SCI收录)
      [22] Kangyue Fang, Yunkai Wu, Yang Zhou, et al. Incipient Fault Detection of CRH Suspension system based on PRPCA and Wasserstein Distance[C]//2023 42st Chinese Control Conference (CCC). IEEE, 2023: 5082-5087.
      [23] Yunkai Wu, Yu Su, Yu-Long Wang and Peng Shi*. T-S Fuzzy Data-Driven ToMFIR with Application to Incipient Fault Detection and Isolation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(7):7921-7932. (中科院一区，SCI收录)
      [24] Zimu Zhang, Yunkai Wu*, Yang Zhou and Dahai Hu. Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints. Sensors, 2024, 24(10): 3029. (中科院三区，SCI收录)
      [25] Yunkai Wu, Tianxiang Ji, Yang Zhou* and Yijin Zhou. Support Vector Machine-Based Fault Diagnosis under Data Imbalance with Application to High-Speed Train Electric Traction Systems [J]. Machines, 2024, 12(8): 582. (中科院三区，SCI收录)
      [26] Yunkai Wu, Yu Su and Peng Shi*. Data-Driven ToMFIR-Based Incipient Fault Detection and Estimation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Industrial Informatics, 2025, 21(1): 613-622. (中科院一区，SCI收录)
      [27] Zefan Zhu, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and YengChai Soh. ToMFIR and Auxiliary Signals based Active Incipient Fault Detection for Autonomous Underwater Vehicle Thrusters[C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4900-4905.
      [28] Xuansen Wang, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and Qingjun Zeng. Fault Prediction of High-Speed Train Suspension Systems based on Transformer with Improved Temporal Distribution Matching Algorithm [C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4949-4954.
      [29] Kang Feng, Yunkai Wu*, Yang Zhou and Yijin Zhou. Incipient Fault Detection and Recognition of China Railway High-Speed (CRH) Suspension System Based on Probabilistic Relevant Principal Component Analysis (PRPCA) and Support Vector Machine (SVM) [J]. Machines, 2024, 12(12): 832. (中科院三区，SCI收录)

      [30]Yunkai Wu, Yu Tian, Yang Zhou*. KICA-DPCA-Based Fault Detection of High-Speed Train Traction Motor Bearings [J]. Machines, 2025, 13(7): 552. (中科院三区，SCI收录)

      [31]Yunkai Wu*, Zefan Zhu, Peng Shi and Yueyang Li.  Active fault diagnosis for AUV over-actuated systems based on UIOs and control allocation[J]. ISA Transactions, 2025, 166: 80-88. (中科院二区，SCI收录)

      [32]Kang Feng, Yunkai Wu*, Yang Zhou and Zhoujie Lian. Data-Driven ToMFIR-based Active Incipient Fault Detection for the Suspension System of High-Speed Trains[J]. IEEE Access, 2025, 14: 9851-9858.  (中科院四区，SCI收录)

      [33]Yunkai Wu*, Yu Tian, Yang Zhou, Xiangqian Liu. Deep-PCA and MSPCA based fault diagnosis of high-speed train traction systems under missing data conditions[J]. ISA Transactions, 2025, 10.1016/j.isatra.2025.10.051 (中科院二区，SCI收录)











    • 科研项目

      [1]基于ToMFIR残差架构的高速列车牵引传动系统早期故障诊断研究，国家自然科学基金-面上项目，2026.1-2029.12，项目经费：50 万元，项目编号：62573213，主持

      [2]复杂工况下高速列车牵引系统早期故障智能诊断与预测方法研究，国家自然科学基金-面上项目，2022.1-2025.12，项目经费：58 万元，项目编号：62173164，主持

      [3]基于ToMFIR与键合图理论的动车组牵引传动系统早期故障诊断方法研究，国家自然科学基金-青年基金，2019.1-2021.12，项目经费：27 万元，项目编号：61803185，主持

      [4]CRH动车组列车牵引控制系统早期故障诊断与预测方法，科技部-中国北马其顿科技合作委员会第6届例会人员交流项目 (科技部国际合作项目)，2020.1-2021.12，项目经费：9 万元，项目编号：19-6-3，主持

      [5]基于图论与解析模型相结合的高速列车信息控制系统早期故障实时诊断与应用验证，江苏省自然科学基金-面上项目，2020.7-2023.6，项目经费：10 万元，项目编号：BK20201451，主持

      [6]动车组电力牵引系统早期故障智能诊断与性能退化评估机理研究，2024年度镇江市基础研究专项，2024.9-2026.8，项目经费：10 万元，项目编号：JC2024014，主持

      [7]L921A低碳中合金调质钢激光-MIG复合焊接机理分析及疲劳性能研究，企业横向课题（沪东中华造船（集团）有限公司），2023.03-2025.03，项目经费：82万，主持；

      [8]不平衡样本下基于定量质量评价的搅拌摩擦焊系统故障诊断方法研究，国家自然科学基金-青年基金，2023.1-2025.12，项目经费：30 万元，项目编号：62203192，参研

      [9]高速列车信息控制系统微小和复合故障的实时诊断理论与预测方法，国家自然科学基金-重大项目，2015.1-2019.12，项目经费：320 万元，项目编号：61490703，参与人 (5/10，已结题)

      [10]高速列车牵引系统闭环结构下的故障诊断与容错控制研究, 国家自然科学基金-面上项目，2016.1-2019.12，项目经费：65 万元，项目编号：61573180，参与人 (3/8，已结题)

      [11]基于不确定信息的轧制过程故障预测与诊断关键技术研究，国家自然科学基金-面上项目，2014.1-2017.12，项目经费：60 万元，项目编号：61374141，参与人 (3/7，已结题)


    • 论文著作

      [1] Yunkai Wu, Bin Jiang and Ningyun Lu. A descriptor system approach for estimation of incipient faults with application to high-speed railway traction devices. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(10): 2108~2118. (ESI高被引论文，中科院一区，SCI收录，IF:13.451)
      [2] Yunkai Wu, Bin Jiang and Yulong Wang. Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains, ISA Transactions, 2020, 99: 488~495. (ESI高被引论文，中科院二区，SCI收录，IF:4.343)
      [3] Yunkai Wu, Bin Jiang and Peng Shi. Incipient fault diagnosis for T-S fuzzy systems with application to high-speed railway traction devices. IET Control Theory & Applications, 2016, 10(17): 2286~2297.  (SCI收录，IF:2.048)
      [4] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Multiple incipient sensor fault diagnosis with application to high-speed railway traction devices. ISA Transactions, 2017, 67: 183~192.
      (SCI收录，IF:2.600)
      [5] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. ToMFIR-based incipient fault detection and estimation for high-speed rail vehicle suspension system. Journal of the Franklin Institute, 2015, 352(4): 1672~1692. (SCI收录，IF:2.327)
      [6] Yunkai Wu, Bin Jiang, Ningyun Lu, et al. Bayesian network based fault prognosis via bond graph modeling of high-speed railway traction device. Mathematical Problems in Engineering, 2015, 1~12. (SCI收录，IF:0.644)
      [7] 姜斌, 吴云凯, 陆宁云, 冒泽慧. 高速列车牵引系统故障诊断与预测技术综述. 控制与决策, 2018, 33(5): 841~855. (EI收录)
      [8] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. ToMFIR-based detection and estimation for incipient actuator faults in a class of closed-loop nonlinear systems. IFAC Proceedings Volumes, 2014, 47(3): 1096~1101.
      [9] Yunkai Wu, Bin Jiang, Donghua Zhou, et al. Detection and isolation of multiple incipient sensor faults with application to high-speed railway traction motors. Proceedings of the 35st Chinese Control Conference, Chengdu, China, July 27-29, 2016: 6558~6563.
      [10] Yunkai Wu, Bin Jiang and Ningyun Lu. Incipient winding fault detection and isolation for induction motors of high-speed trains. Prognostics and System Health Management Conference (PHM-2017 Harbin), Harbin, China, July 9-12, 2017: 10.1109/PHM.2017.8079108.
      [11] Yunkai Wu, Bin Jiang, Zhiyu Zhu and Qingjun Zeng. Data-driven based ToMFIR design with application to incipient fault detection in high-speed rail vehicle suspension system. 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Process, Xiamen, China, July 5-7, 2019: 645-650.
      [12] 柳春, 姜斌, 张柯, 吴云凯. 带扰动的线性系统微小故障早期诊断方法. 上海交通大学学报（自然科学版）, 2015, 49(6): 889~896.
      [13] 吴国政, 吴云凯, 张兆田, 韩军伟. 浅析人工智能学科基金项目申请资助情况及展望. 自动化学报, 2020, 46(12): 2711~2718.
      [14] 苏宇, 吴云凯*, 付俊, Gorjan Nadzinski. 基于数据驱动的CRH 高速列车悬挂系统早期故障检测. 控制与决策, 2022, 37(4): 982-988. (EI收录)
      [15] 吴云凯, 胡大海, 朱志宇, 曾庆军. 基于自适应阈值与扩张状态滑模观测器的AUV 执行机构故障检测与估计. 控制理论与应用, 2023, 40(7): 1216-1223. (EI收录)
      [16] Dahai Hu, Yunkai Wu, Yang Zhou, et al. Actuator Fault Detection for Automation Underwater Vehicle via Extended State Observer and Adaptive Threshold[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4106-4111.
      [17] Xiangqian Liu, Yunkai Wu, Yang Zhou, et al. Improved Deep PCA based Incipient Fault Detection with Application on CRH Traction System[C]//2022 41st Chinese Control Conference (CCC). IEEE, 2022: 4118-4123.
      [18] Yunkai Wu, Xiangqian Liu, Yang Zhou. Deep PCA-based Incipient Fault Diagnosis and Diagnosability Analysis of High-Speed Railway Traction System via FNR Enhancement[J]. Machines, 2023, 11(4): 475. (ESI高被引论文，中科院三区，SCI收录)
      [19] Yunkai Wu, Xiangqian Liu, Yu-Long Wang, et al. Improved Deep PCA and Kullback-Leibler Divergence based Incipient Fault Detection and Isolation of High-speed Railway Traction Devices [J]. Sustainable Energy Technologies and Assessments, 2023, 57(10):103208. (中科院二区，SCI收录)
      [20] 吴云凯, 胡大海, 付俊，周扬. 基于故障描述因子与多观测器同步协作的AUV执行机构故障隔离与辨识[J]. 控制与决策, 2024, 39(6):2005-2012.
      [21] Yunkai Wu, Aodong Wang, Yang Zhou*, et al. Fault Diagnosis of Autonomous Underwater Vehicle with Missing Data Based on Multi-Channel Full Convolutional Neural Network [J]. Machines, 2023, 11(10): 960. (中科院三区，SCI收录)
      [22] Kangyue Fang, Yunkai Wu, Yang Zhou, et al. Incipient Fault Detection of CRH Suspension system based on PRPCA and Wasserstein Distance[C]//2023 42st Chinese Control Conference (CCC). IEEE, 2023: 5082-5087.
      [23] Yunkai Wu, Yu Su, Yu-Long Wang and Peng Shi*. T-S Fuzzy Data-Driven ToMFIR with Application to Incipient Fault Detection and Isolation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(7):7921-7932. (中科院一区，SCI收录)
      [24] Zimu Zhang, Yunkai Wu*, Yang Zhou and Dahai Hu. Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints. Sensors, 2024, 24(10): 3029. (中科院三区，SCI收录)
      [25] Yunkai Wu, Tianxiang Ji, Yang Zhou* and Yijin Zhou. Support Vector Machine-Based Fault Diagnosis under Data Imbalance with Application to High-Speed Train Electric Traction Systems [J]. Machines, 2024, 12(8): 582. (中科院三区，SCI收录)
      [26] Yunkai Wu, Yu Su and Peng Shi*. Data-Driven ToMFIR-Based Incipient Fault Detection and Estimation for High-Speed Rail Vehicle Suspension Systems. IEEE Transactions on Industrial Informatics, 2025, 21(1): 613-622. (中科院一区，SCI收录)
      [27] Zefan Zhu, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and YengChai Soh. ToMFIR and Auxiliary Signals based Active Incipient Fault Detection for Autonomous Underwater Vehicle Thrusters[C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4900-4905.
      [28] Xuansen Wang, Yunkai Wu, Yang Zhou, Zhiyu Zhu, and Qingjun Zeng. Fault Prediction of High-Speed Train Suspension Systems based on Transformer with Improved Temporal Distribution Matching Algorithm [C]//2024 43rd Chinese Control Conference (CCC). IEEE, 2024: 4949-4954.
      [29] Kang Feng, Yunkai Wu*, Yang Zhou and Yijin Zhou. Incipient Fault Detection and Recognition of China Railway High-Speed (CRH) Suspension System Based on Probabilistic Relevant Principal Component Analysis (PRPCA) and Support Vector Machine (SVM) [J]. Machines, 2024, 12(12): 832. (中科院三区，SCI收录)

      [30]Yunkai Wu, Yu Tian, Yang Zhou*. KICA-DPCA-Based Fault Detection of High-Speed Train Traction Motor Bearings [J]. Machines, 2025, 13(7): 552. (中科院三区，SCI收录)

      [31]Yunkai Wu*, Zefan Zhu, Peng Shi and Yueyang Li.  Active fault diagnosis for AUV over-actuated systems based on UIOs and control allocation[J]. ISA Transactions, 2025, 166: 80-88. (中科院二区，SCI收录)

      [32]Kang Feng, Yunkai Wu*, Yang Zhou and Zhoujie Lian. Data-Driven ToMFIR-based Active Incipient Fault Detection for the Suspension System of High-Speed Trains[J]. IEEE Access, 2025, 14: 9851-9858.  (中科院四区，SCI收录)

      [33]Yunkai Wu*, Yu Tian, Yang Zhou, Xiangqian Liu. Deep-PCA and MSPCA based fault diagnosis of high-speed train traction systems under missing data conditions[J]. ISA Transactions, 2025, 10.1016/j.isatra.2025.10.051 (中科院二区，SCI收录)











  • [1]自动化专业导论

    [2]自动控制原理(留学生)

    [3]专业写作与表达


  		•