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  • [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)