1998.9-2002.6 哈尔滨工业大学自动化专业学士学位 2002.9-2005.3 东北大学信息科学与工程学院电力电子与电力传动硕士学位 2006.3-2009.1东北大学信息科学与工程学院控制理论与控制工程专业博士学位

2005.3-2009.1 东北大学信息科学与工程学院助教 2009.1-2011.12 东北大学信息科学与工程学院讲师 2012.1-2017.12 东北大学信息科学与工程学院副教授 2018.1-至今东北大学信息科学与工程学院教授博士生导师

项目 1.国家自然科学基金面上基金：基于异构场的深海管道进化缺陷故障诊断方法研究，61973071，2020.1-2023.12. 2.国家重点研发计划：深海油气管道内外检测与故障诊断装备开发与示范应用， 2017YFF0108804，2017YFF0108802-1，2017.7-2021.6. 3.国家重大科研仪器研制项目子课题：基于电磁全息协同的海洋在役油气管道内检测仪器研制-电磁全息检测原理及缺陷智能故障诊断，61627809-2，2017.1-2021.12. 4.企业重大课题:深海管道ᠦ୔

期刊论文 1.Mingrui Fu, Jinhai Liu*, Huaguang Zhang, Senxiang Lu. Multi-sensor Fusion for MFL Defect Characterization Under Information Incompletion. IEEE Transactions on Industrial Electronics, DOI：10.1109/TIE.2020.2984444 2.Mingrui Fu, Jinhai Liu*, Dong Zang, Senxiang Lu. Anomaly Detection of Complex MFL Measurements Using Low-rank Recovery in Pipeline Transportation Inspection.IEEE Transactions on Instrumentation & Measurement, DOI：10.1109/TIM.2020.2974543 3.Fuming Qu, Jinhai Liu*, Hongfei Zhu, Bowen Zhou. Wind Turbine Fault Detection Based on Expanded Linguistic Terms and Rules Using Non-singleton Fuzzy Logic. Applied Energy. DOI：https://doi.org/10.1016/j.apenergy.2019.114469 4.Fuming Qu, Jinhai Liu*, et al. Wind Turbine Condition Monitoring Based on Assembled Multidimensional Membership Functions Using Fuzzy Inference System, IEEE Transactions on Industrial Informatics. 16(6): 4028-4037, 2020. 5.Jinhai Liu*, Fuming Qu, et.al. A Small-sample Wind Turbine Fault Detection Method with Synthetic Fault Data Using Generative Adversarial Nets. IEEE Transactions on Industrial Informatics. 15(7) : 3877-3888 ，2019 6.Jinhai Liu*, Dong Zang, et. al. A Leak Detection Method for Oil Pipeline Based on Markov Feature and Two-stage Decision Scheme. Measurement. 138 : 433-445, 2019. 7.Jinhai Liu*, Mingrui Fu, Feilong Liu, et.al. Window Feature Based 2-stage Defect Identication Using Magnetic Flux Leakage (MFL) Measurements. IEEE Transactions on Instrumentation & Measurement. 2018，67（1）:12-23. 8.Jinhai Liu*, Yanjuan Ma, Huaguang Zhang, et.al. A modified fuzzy min–max neural network for data clustering and its application on pipeline internal inspection data. Neurocomputing 238(2017)56-66. 9.Liu Jinhai*, Ma Yanjuan, Wu Zhengning, Wang Gang. Real-time pressure based diagnosis method for oil pipeline leakage. Journal of Shanghai Jiao Tong University (Science) 2017,22(2):233-239. 10.Jinhai Liu*, Hanguang Su, Yanjuan Ma, et.al. Chaos characteristics and least squares support vector machines based online pipeline small leakages detection. Chaos, Solitons and Fractals, 91 (2016) 656–669.

专利 1.一种管道漏磁内检测器数据的自适应滤波方法，ZL201610844081.2，2019 2.基于KNN-SVR的海底管道漏磁数据缺失插补方法，专利号：CN107842713B，2019. 3.一种管道缺陷漏磁信号的特征提取方法，专利号：CN106870957B，2019. 4.一种海底管道内检测器的实时跟踪与定位系统及方法，CN107166174B，2019 5.一种基于无源RFID的实验室设备动态管理系统，CN103996097B，2017 6.一种基于组合滤波和动态阈值的管道压力异ᠦ୔