人物經歷
教育背景
2011/09 – 2015/06:清華大學,能源與動力工程系,工學學士
2015/09 – 2020/06:清華大學,能源與動力工程系,工學博士
2019/03 – 2019/09:阿爾伯塔大學,機械工程系,博士聯合培養
工作經歷
2020/09 – 2023/02: 清華大學,工業工程系,博士後
2023/02至今 北京理工大學,管理與經濟學院,預聘副教授(特別研究員)
研究興趣
複雜系統智慧型運維管理
大數據驅動的裝備故障診斷與智慧型運維
智慧能源管理
科學機器學習
人工智慧與工程管理
論著發表
[1] Han Te, Tian Jinpeng*, Chung C. Y.*, Wei Yi-Ming. Challenges and opportunities for battery health estimation: Bridging laboratory research and real-world applications. Journal of Energy Chemistry, 2024, 89, 434-436. (SCI, JCR1區, 中科院分區表Top 期刊)
[2] Yao Yuantao, Han Te*, Yu Jie, Xie Min. Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems. Energy, 2024, 291, 130419. (SCI, JCR1區, 中科院分區表Top 期刊)
[3] Yao Jiachi and Han Te*. Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data. Energy, 2023, 271, 127033. (SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[4] Xie Wenzhen, Han Te*, Pei Zhongyi and Xie Min. A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems. Engineering Applications of Artificial Intelligence, 2023, 125, 106707. (SCI, JCR1區, 中科院分區表Top 期刊)
[5] Han Te, Xie Wenzhen*, Pei Zhongyi. Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine. Information Sciences, 2023, 648, 119496. (SCI, JCR1區, 中科院分區表Top 期刊)
[6] Wang Zhe, Wu Zhiying, Li Xingqiu, Shao Haidong, Han Te*, Xie Min. Attention-aware temporal-spatial graph neural network with multi-sensor information fusion for fault diagnosis. Knowledge-Based Systems, 2023, 278, 110891. (SCI, JCR1區, 中科院分區表Top 期刊)
[7] Miao Yonghao, Li Chenhui, Shi Huifang and Han Te*. Deep network-based maximum correlated kurtosis deconvolution: A novel deep deconvolution for bearing fault diagnosis. Mechanical Systems and Signal Processing, 2023, 189: 110110. (SCI, JCR1區, 中科院分區表Top 期刊)
[8] Meng Huixing, Geng Mengyao and Han Te*. Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis. Reliability Engineering & System Safety, 2023, 236, 109288. (SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[9] Zhou Taotao, Han Te* and Enrique Lopez Droguett. Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework. Reliability Engineering & System Safety, 2022, 224: 108525. (SCI, JCR1區, 中科院分區表Top 期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[10] Han Te and Li Yan-Fu*. Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles. Reliability Engineering & System Safety, 2022, 226, 108648. (SCI, JCR1區, 中科院分區表Top 期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[11] Han Te, Wang Zhe* and Meng Huixing. End-to-end capacity estimation of Lithium-ion batteries with an enhanced long short-term memory network considering domain adaptation. Journal of Power Sources, 2022, 520: 230823. (SCI, JCR1區, 中科院分區表Top 期刊)
[12] Han Te, Li Yan-Fu* and Qian Min. A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 3520011.( SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[13] Han Te, Liu Chao*, Wu Rui and Jiang Dongxiang. Deep transfer learning with limited data for machinery fault diagnosis. Applied Soft Computing, 2021, 103: 107150. (SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[14] Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. Deep transfer network with joint distribution adaptation: a new intelligent fault diagnosis framework for industry application. ISA Transactions, 2020, 97: 269-281. (SCI, JCR1區, 中科院分區表Top 期刊, Top 0.1% ESI熱點論文,Top 1% ESI高被引論文)
[15] Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults. Knowledge-Based Systems, 2019, 165: 474-487. (SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[16] Han Te, Liu Chao*, Wu Linjiang, Sarkar Soumik and Jiang Dongxiang. An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems. Mechanical Systems and Signal Processing, 2019, 117: 170-187. (SCI, JCR1區, 中科院分區表Top 期刊, Top 1% ESI高被引論文)
[17] Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions. ISA Transactions, 2019, 93: 341-353. (SCI, JCR1區, 中科院分區表Top 期刊)
[18] Han Te, Jiang Dongxiang*, Sun Yankui, Wang Nanfei and Yang Yizhou. Intelligent fault diagnosis method for rotating machinery via dictionary learning and sparse representation-based classification. Measurement, 2018, 118: 181-193. (SCI, JCR1區, 中科院分區表Top 期刊)
[19] Han Te*, Jiang Dongxiang, Zhao Qi, Wang Lei and Yin Kai. Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery. Transactions of the Institute of Measurement and Control, 2018, 40(8): 2681-2693. (SCI, JCR3區, Top 1% ESI高被引論文)
[20] 韓特, 李彥夫*, 雷亞國, 李乃鵬, 李響. 融合圖示簽傳播和判別特徵增強的工業機器人關鍵部件半監督故障診斷方法. 機械工程學報, 2022, 58(17): 116-124.
科研項目
[1] 國家自然科學基金青年科學基金項目:小樣本下風力發電機系統運行健康狀態表征與域泛化智慧型診斷研究,2023年-2025年,30萬,在研,負責人
[2] 安徽省科技重大專項“揭榜掛帥”項目:面向工業網際網路的多模態智慧型感知與認知決策技術攻關,2023年-2025年,3020萬,在研,子課題負責人
[3] 中國博士後科學基金特別資助(站中):數據驅動的高速列車傳動系統智慧型故障診斷與根原因分析方法研究,2021年-2022年,18萬,已結題,負責人
[4] 中國博士後科學基金面上資助:高速列車傳動系統的智慧型遷移故障診斷與根原因分析方法研究,2021年-2022年,8萬,已結題,負責人
[5] 企業橫向委託-中國船舶集團系統工程研究院:機電設備亞健康狀態識別技術輔助研究及功能演示,2023年-2024年,48.7萬,在研,負責人
[6] 國家自然科學基金重點項目:大數據驅動的高速鐵路高可用性研究,2018年-2022年,245萬,已結題,課題骨幹
[7] 國家重點研發計畫:工業機器人智慧型故障診斷及健康評估系統,2019年-2022年,1341萬,已結題,課題骨幹
[8] 國家重點研發計畫:燃氣輪機空氣品質保障關鍵技術標準及檢測體系的建立,2019年-2021年,1400萬,已結題,參研
[9] 航空發動機及燃氣輪機重大專項基礎研究項目:燃氣輪機轉子系統的結構動力學與振動控制研究,2018年-2022年,1700萬,已結題,參研
[10] 企業橫向委託-廣西電網有限公司:基於故障診斷與健康管理技術的計量裝置線上評估技術研究,2021年-2023年,170萬,已結題,課題骨幹
[11] Mitsubishi Heavy Industries, Ltd.-Tsinghua University Joint Research Project, Development of renewable generating power forecasting methods using statistical model, 2015年-2016年,50萬,已結題,課題骨幹
學術兼職與服務
《Applied Soft Computing》 (SCI, JCR Q1, 中科院一區Top期刊) 編委
《IEEE Sensors Journal》 (SCI, JCR Q1, 中科院二區期刊) 副主編
《Reliability Engineering & System Safety》 (SCI, JCR Q1, 中科院一區Top期刊, FMS B類) 客座編輯, Special Issue: Scientific Machine Learning for Enhancing Reliability and Safety of AI-powered Systems
《Journal of Risk and Reliability》 (SCI, JCR Q2, FMS B類) 客座編輯, Special Issue: Domain-Knowledge Guided Machine Learning in Safety-Critical Applications
《IEEE Transactions on Industrial Cyber-Physical Systems》 客座編輯, Special Issue: Machine Learning for Prognostics and Health Management of Industrial Cyber-physical Systems
《Measurement Science and Technology》 (SCI, JCR Q1) 客座編輯, Special Issue: AI-Enabled Industrial Equipment Monitoring, Diagnosis and Health Management
《Chinese Journal of Mechanical Engineering》(SCI, JCR Q1) 青年編委
《Journal of Dynamics, Monitoring and Diagnostics》青年編委
全國自動化系統與集成標準化技術委員會鋰電池智慧型製造裝備標準化工作組組員(SAC/TC159/WG18)
中國系統工程學會系統可靠性工程專委會委員
中國“雙法”研究會能源經濟與管理研究分會理事
The 2023 IEEE Global Reliability & Prognostics and Health Management Conference (IEEE GlobalRel & PHM 2023) Session Chair
The 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT 2023) Session Chair
The Fourth International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD 2023) Session Organizer
The International Conference on Aerospace Structural Dynamics (ICASD 2023) Organizing Committee
The Third International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD 2022) Session Organizer
主要榮譽獎勵
中國科協“青年人才托舉工程”(2023)
斯坦福全球前2%頂尖科學家(2023)
《Journal of Dynamics, Monitoring and Diagnostics》Outstanding Member of the Youth Editorial Board(2023)
斯坦福全球前2%頂尖科學家(2022)
中國運籌學會運籌套用獎(排名第四)(2022)
斯坦福全球前2%頂尖科學家(2021)
清華大學“水木學者”(2020)
清華大學優秀博士學位論文,入選“清華大學優秀博士學位論文叢書”出版項目(2020)
斯坦福全球前2%頂尖科學家(2020)
教育部博士研究生“國家獎學金”(2019)
中科院Top期刊《ISA Transactions》Outstanding Reviewer(2019)
全國設備監測診斷與維護會議優秀論文獎(2018)
清華大學綜合優秀一等獎學金(2018)
清華校友-倪維斗院士獎學勵志基金(2017)
清華大學三菱重工獎學金(2016)