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                周東華  教授(1997) 博¤士生導師(1999--)

                曾任浙江大學博士後♀(1991-1992),清華大學自動化系主任(2008--2015)。

                目前任山東你這五百玄仙科技大學副校長,清華大學教授(雙聘)。

                 

                Email:zdh@tsinghua.edu.cn

                展開
                教育背景

                分別於1985, 1988, 1990年在上海交通大學獲工學學士,碩士,博士學位。

                工作履歷

                曾任北京理工大學副研究員(1993-1994)

                德國杜伊斯堡大∩學洪堡學者(1994-1996)

                耶魯★大學訪問學者(1991-1992)

                 

                研究領域

                動態系統故障診斷與容錯控制,可靠性預測與剩余壽命估計等。

                研究概況

                已出版學術著聲音響起作5部,發表SCI 收錄論文150余篇。

                獎勵與榮譽

                曾獲中國青年科技獎、國家傑出青年科學基金。為教ξ 育部長江學者特聘教授,國家自然科學基金會優秀創新群體學術帶頭人、重大項目》首席負責人,國家“萬人計劃”百千萬▃工程領軍人才。曾獲國家自然科學二等獎、國家科技進步二等→獎、國家級優秀教學成『果二等獎各1次。

                學術成果

                主要論著
                [1]周東華, 陳茂銀, 徐正國. 可靠性預︽測與最優維護技術. 中國科學技術大學出版甚至力量還不能弱于八級仙帝社, 2013

                [2]周東華,李鋼,李元. 數據驅動的工業過程故障診▲斷技術:基於主元分析與偏最小二乘╲的方法. 科學出〒版社, 2011

                [3]文成林,周東華. 多尺卐度估計理論及其應用. 清華↑大學出版社∞,2002

                [4]周東華. 非線性系統的自適應控⌒制導論. 清華大學出○版社,2002

                [5]周東華,葉銀忠. 現代故障診斷與容錯控制. 清◆華大學出版社,2000

                [6]周東華, 孫優賢. 控制系統的故障檢測與診斷技術. 清華大學管家已經被長老他們給殺了出版社,1994

                [7]D. H. Zhou, G. Li , S. J. Qin, Total projection to latent structures for process monitoring, AIChE J, 2010,56(1): 168-178

                [8]Y. Y. Hu, Z. S. Duan, D. H. Zhou, Estimation fusion with general asynchronous multi-rate sensors, IEEE Trans. on AES, 2010, 46(4): 2090-2102

                [9]G. Li, S. J. Qin D. H. Zhou, Geometric properties of partial least squares for process monitoring, Automatica, 2010, 46(1): 204-210

                [10]H. D. Fan, C. H. Hu, M. Y. Chen, and D. H. Zhou ,Cooperative predictive maintenance of repairable systems with dependent failure modes and resource constraint, IEEE Trans. on Reliability, 2011, 60(1):144-157

                [11]G. Li, C. F. Alcala, S. J. Qin, and D. H. Zhou, Generalized reconstruction based contributions for output-relevant fault diagnosis with application to the Tennessee Eastman process. IEEE Trans. on CST, 2011, 19(5): 1114-1127

                [12]X. S. Si, W.B. Wang, C. H. Hu and D. H. Zhou, Remaining useful life estimation-a review on the statistical data driven approaches, EJOR, 2011, 213(1), 1-14.

                [13]D. H. Zhou, X. He, Z. D. Wang, G. P. Liu, and Y. D. Ji, Leakage fault diagnosis for an Internet-based three-tank system: an experimental study, IEEE Trans. on  CST, 2012, 20(4): 857-870

                [14]X. S. Si, W. B. Wang, C. H. Hu, D. H. Zhou, G. P. Michael , Remaining useful life estimation based on a nonlinear diffusion degradation process, IEEE Trans. on  Reliability, 2012, 61(1): 50-67

                [15]X. F. Lu, M. Y. Chen, M. Liu and D. H. Zhou. Optimal imperfect periodic preventive maintenance for systems in the time-varying environment, IEEE Trans. on  Reliability, 2012, 61(2): 426-439

                [16]M. H. We, M. Y. Chen, and D. H. Zhou, Multi-sensor information based remaining useful life prediction with anticipated performance, IEEE Trans. on Reliability ,2013, 62(1):183-198

                [17]X. S. Si, W. B. Wang, M. Y. Chen, C. H. Hu, D. H. Zhou, A degradation path-dependent approach for remaining useful life estimation with an exact yet closed-form solution, EJOR, 2013, 226:53-66

                [18]X.S. Si, M.Y. Chen, W. B. Wang, C. H. Hu, D.H. Zhou, Specifying measurement errors for required lifetime estimation performance, EJOR , 2013,231: 631-644

                [19]X. S. Si, W. B. Wang, C. H. Hu, D. H. Zhou, Estimating remaining useful life with three-source variability in degradation modeling, IEEE Trans. on Reliability,2014, 63(1): 167-190

                [20]Y. Liu,  X. He,  Z. D. Wang, D. H. Zhou, Optimal filtering for networked systems with stochastic sensor gain degradation, Automatica, 2014, 50:1521-1525.

                [21]X. S. Si, D. H. Zhou, A generalized result for degradation model based reliability estimation, IEEE Transactions on Automation Science and Engineering, 2014, 11(2): 632-637

                [22] Y. Liu, Z.D. Wang, X. He and D. H. Zhou, Filtering and fault detection for nonlinear systems with polynomial approximation, Automatica, 2015, 54:348-359.

                [23] Q.Y. Liu,  Wang Z.D., He X., Zhou D.H., Event-based recursive distributed filtering over wireless sensor networks, IEEE Transactions on Automatic Control, 2015, 60(9): 2470-2475.

                [24] Q.Y. Liu,Z.D. Wang, D. H. Zhou, Event-based distributed filtering with stochastic measurement fading, IEEE Trans. on Industrial Informatics, 2015, 11(6): 1643-1652.

                [25] Y. Liu,  Z.D. Wang, X. He and  D. H. Zhou, Minimum-variance recursive filtering over sensor networks with stochastic sensor gain degradation: algorithms and performance analysis, IEEE Trans. on  Control of  Network  Systems,2016, 3(3): 265-274.

                [26] Z.H. Pang, G.P. Liu, D.H. Zhou, et al. Data-based predictive control for networked nonlinear systems with network-Induced delay and packet dropout . IEEE Trans. on Industrial Electronics, 2016,  63, (2):   1249-1259.

                [27] J. Shang,  M.Y. Chen,  H.Q. Ji,  D. H. Zhou, Recursive transformed component statistical analysis for incipient fault detection, Automatica, 80 (2017) 313–327.

                 

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