張凱，男，北京科技大學自動化學院控制科學與工程系副教授，所屬工業過程先進控制與故障診斷。
教學科研,主講課程,研究方向,主要成就,代表論著,代表項目,學術任職,
教學科研
主講課程
可程式控制器及套用，過程控制系統設計，智慧型控制理論基礎
研究方向
乘性故障診斷，複雜工業過程監控，層次化數據建模
主要成就
代表論著
專著：
Performance Assessment for Process Monitoring and Fault Detection Methods，Springer，ISBN: 978-3-658-15970-2，2016.
代表性論文：
[1] Kai Zhang, Haiyang Hao, Zhiwen Chen, Steven X. Ding, and Kaixiang Peng, A comparison and evaluation of key performance indicator-based multivariate statistics process monitoring approaches, Journal of Process Control, vol. 33, pp. 112-126, 2015. （SCI）
[2] Kai Zhang, Yuri A. W. Shardt, Zhiwen Chen, and Kaixiang Peng, Using the expected detection delay to assess the performance of different multivariate statistical process monitoring methods for multiplicative and drift faults, ISA Transactions, vol. 67, no. 6, pp. 56-66, 2017. （SCI）
[3] Kai Zhang, Haiyang Hao, Zhiwen Chen, Steven X. Ding, Kaixiang Peng, and Eve L. Ding, Comparison study of multivariate statistics based key performance indicator monitoring approaches, 19th IFAC world congress, Cape Town, South Africa, 2014, pp.10628-10633. （EI）
[4] Kai Zhang, Yuri A. W. Shardt, Zhiwen Chen, Steven X. Ding, and Kaixiang Peng, Unit-level modelling for KPI of batch hot strip mill process using dynamic partial least squares, 17th IFAC SYSID, Beijing, China, 2015, pp. 1005-1010. （EI）
[5] Kai Zhang, Jie Dong, and Kaixiang Peng, A novel dynamic non-Gaussian approach for quality-related fault diagnosis with application to the hot strip mill process, Journal of the Franklin Institute, vol. 354, no. 2, pp. 702-721, 2017. （SCI）
[6] Kai Zhang, Steven X. Ding, Yuri A. W. Shardt, Zhiwen Chen, and Kaixiang Peng, Assessment of T2- and Q-statistics for detecting additive and multiplicative faults, Journal of the Franklin Institute, vol. 354, no. 2, pp. 668-688, 2017. （SCI）
[7] Kai Zhang, Yuri A. W. Shardt, Steven X. Ding, Zhiwen Chen and Kaixiang Peng, A brief survey of test statistics for detecting multiplicative faults, IEEE CDC 2016, Las vegas, USA, pp. 2152-2157. （EI）
[8] Kai Zhang, Yuri A. W. Shardt, Zhiwen Chen, Steven X. Ding, and Kaixiang Peng, A KPI-based process monitoring framework for large-scale processes, ISA Transactions, vol. 68, 276-286, 2017. （SCI）
[9] Zhiwen Chen, Kai Zhang, Yuri A.W. Shardt, and Steven X. Ding, Comparison of two basic statistics for fault detection and process monitoring, IFAC world congress 2017, Toulouse, France. （EI）
[10] Kaixiang Peng, Kai Zhang*, Gang Li, and Donghua Zhou, Contribution rate plot for nonlinear quality-related fault diagnosis with application to the hot strip mill process, Control Engineering Practice, vol. 24, no. 4, pp. 360-369, 2013. （SCI）
[11] Kaixiang Peng, Kai Zhang*, and Gang Li, Quality-related process monitoring based on total kernel PLS model and its industrial application, Mathematical Problems in Engineering, vol. 2013, pp. 1-14, 2013. （SCI）
[12] Kaixiang Peng, Kai Zhang*, Xiao He, Gang Li, and Xu Yang, New kernel independent and principal components analysis-based process monitoring approach with application to hot strip mill process, IET Control Theory & Applications, vol. 8. no. 16, pp. 1723-1731, 2014. （SCI）
[13] Kaixiang Peng, Kai Zhang*, Jie Dong, and Xu Yang, A new data-driven process monitoring scheme for key performance indictors with application to hot strip mill process, Journal of the Franklin Institute, vol. 351, no. 9, pp. 4555-4569, 2014. （SCI）
[14] Kaixiang Peng, Kai Zhang*, and Gang Li, Online Contribution rate based fault diagnosis for nonlinear industrial processes, Acta Automatica Sinica, vol. 40, no. 3, pp. 423-430, 2014. （SCI）
[15] Kaixiang Peng, Kai Zhang*, Jie Dong, and Bo You, Quality-relevant fault detection and diagnosis for hot strip mill process with multi-specification and multi-batch measurements, Journal of the Franklin Institute, vol. 352, no. 3, pp. 987-1006, 2014. （SCI）
[16] Jie Dong, Kai Zhang*, Ya Huang, Gang Li, and Kaixiang Peng, Adaptive total PLS based quality-relevant process monitoring with application to the Tennessee Eastman process, Neurocomputing, vol. 154, pp. 77-85, 2015. （SCI）
[17] Kaixiang Peng, Kai Zhang*, Bo You, and Jie Dong, Quality-relevant fault detection based on efficient projection to latent structures with application to hot strip mill process, IET Control Theory & Applications, vol. 9, no. 7, pp. 1135-1145, 2015. （SCI）
[18] Kaixiang Peng, Kai Zhang*, Bo You, and Jie Dong, Quality-related prediction and monitoring of multi-mode processes using multiple PLS with application to an industrial hot strip mill, Neurocomputing, vol. 168, pp. 1094-1103, 2015. （SCI）
[19] Kaixiang Peng, Kai Zhang*, Bo You, Jie Dong, and Zidong Wang, A Quality-based nonlinear fault diagnosis framework focusing on industrial multimode batch processes, IEEE Transactions on Industrial Electronics, vol. 63, no.4, pp. 2615-2624, 2016. （SCI）
[20] Zhiwen Chen, Steven X. Ding, Kai Zhang, and Zhikun Hu, Canonical correlation analysis-based fault detection methods with application to alumina evaporation process, Control Engineering Practice, vol. 46, pp. 51-58, 2016. （SCI）
[21]Liang Ma, Jie Dong, Kaixiang Peng, and Kai Zhang, A novel data-based quality-related fault diagnosis scheme for fault detection and root cause diagnosis with application to hot strip mill process, Control Engineering Practice, vol. 47, pp. 43-51, 2017. （SCI）
[22] YAW Shardt , S Mehrkanoon , Kai Zhang , X Yang, J Suykens, Modelling the Strip Thickness in Hot Steel Rolling Mills Using Least‐Squares Support Vector Machines, Canadian Journal of Chemical Engineering , accepted. （SCI）
[23] Haiyang Hao, Kai Zhang, Steven X. Ding, Zhiwen Chen, and Yaguo Lei, A data-driven multiplicative fault diagnosis approach for automation processes, ISA Transactions, vol. 53, no. 5, pp. 1436-1445, 2014. （SCI）
[24] Zhiwen Chen, Kai Zhang, Steven X. Ding, Yuri, and A. W. Shardt, Improved canonical correlation analysis-based fault detection methods for industrial processes, Journal of Process Control, vol. 41, 26-34, 2016. （SCI）
[25]Zhiwen Chen, Steven X. Ding, Hao Luo, Kai Zhang , An alternative data-driven fault detection scheme for dynamic processes with deterministic disturbances, accepted by Journal of the Franklin Institute, vol. 354, no.1 , 556–570, 2017.（SCI）
[26] Kaixiang Peng, Qianqian Li, Kai Zhang, Jie Dong, Quality-related process monitoring for dynamic non-Gaussian batch process with multi-phase using a new data-driven method, Neurocomputing, ,vol. 214, 317-328, 2016. (SCI)
[27]彭開香，馬亮，張凱，複雜工業過程質量相關的故障檢測與診斷技術綜述，自動化學報，vol.43, no.3, pp.433-353, 2017. (EI)
[28]彭開香，李鋼，張凱，基於動態全潛結構投影的熱連軋厚度監控，控制理論與套用，vol.29, no.11, pp.1446-1451, 2012. (EI)
代表項目
[1]國家自然科學基金青年基金（61703036）：基於多變數統計的乘性故障診斷方法研究，2018.01-2020.12，負責人
[2]國家自然科學基金（61473033）質量相關的多工況動態間歇過程建模及故障診斷方法研究，2015.01-2018.12，參與人
[3]國家重點研發計畫（2017YFB0306403），基於工業大數據的鋁/銅板帶材智慧型化工藝控制技術，2017-2020，參與人
學術任職
IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, Journal of Process Control, Control Engineering Practice, 《自動化學報》等期刊審稿人
