王振恒，男，1983年10月出生，博士，講師。主要從事化工和礦業的過程控制、過程監測和故障診斷、過程質量預測與建模等領域的研究工作。近年來，主持湖南省教育廳一般項目，參與國家863計劃項目、973計劃項目，加拿大NSERC項目、國家自然科學基金面上項目、湖南省自然科學基金面上項目等多項。在國内外學術期刊和國際學術會議上發表學術論文10餘篇，其中SCI收錄7篇。
n 學習經曆
2009.09－2014.04，勞倫森大學（加拿大），自然資源工程，博士研究生
2006.09－2009.06，北京化工大學，控制理論與控制工程，碩士研究生
2002.09－2006.06，北京化工大學，自動化，本科/學士
n 科研項目
[1] 湖南省教育廳一般項目“基于數據驅動的粒子濾波故障預測與健康管理的系統設計”，項目編号：19C0759，研究年度：2020.06-2022.12，項目負責人
n 學術論文
[1] 王振恒，基于Multiblock-PLS的工業銅礦雜質去除過程故障診斷，2017年中國過程系統工程年會（PSE2017），昆明，2017.7.25-2017.7.27
[2] Z. Wang, S. Wiebe and H. Shang, “Fault detection and diagnosis of an industrial copper electrowinning process,” Canadian Journal of Chemical Engineering，vol 94，pp 415-423，2016.
[3] Z. Wang, H. Shang, “Kalman filter based fault detection for two-dimensional systems,” Journal of Process Control, vol. 28, pp. 83-94, 2015.
[4] Z. Wang, H. Shang,, “Observer based fault detection for two dimensional systems described by Roesser models,” Multidimensional Systems and Signal Processing, vol. 26, no. 3, pp753-775, 2014.
[5] Z. Wang, J. Zhao and H. Shang, “A hybrid fault diagnosis strategy for chemical process startups,” Journal of Process Control, vol. 28, pp. 83-94, 2012
[6] 王振恒，趙勁松，精餾塔開車過程混合故障診斷研究，華東理工大學學報(自然科學版)，2009，35（4）：639-643
[7] 王振恒，趙勁松，李昌磊，一種新的間歇過程故障診斷策略，化工學報，2008，59（11）：2837-2842.
[8] Z. Wang, H. Shang, “Model-based fault detection for two dimensional systems using polynomial matrix transformation,” 61st Canadian Chemical Engineering Conference in London，Canada，2011.10.23-2011.10.26.
[9] 王振恒，趙勁松，精餾塔開車過程混合故障診斷研究，2008年中國過程系統工程年會(PSE2008)，上海，2008.9.19-2008.9.21
[10] Z. Liu, X. Meng, L. Wei, L. Chen,B. Lu, Z. Wang, and L. Chen, “A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling Bearing,” IJAC-2020-07-178.R1, 2021.
[11] J. Liu, J. Wang, W. Yu, Z. Wang, and G. Zhong, “Open-circuit fault diagnosis of traction inverter based on improved convolutional neural network,” Journal of Physics: Conference Series, Vol 1633,012099, 2020.
[12] J. Sun, J. Wang, W. Yu, Z. Wang, and Y. Wang, " Power Load Disaggregation of Households with Solar Panels Based on an Improved Long Short-term Memory Network," Journal of Electrical Engineering & Technology, vol 15, pp. 2401-2413，2020.
[13] J. Wang, Y. Dou, Z. Wang, and D. Jiang, “Multi-fault diagnosis method for wind power generation system based on recurrent neural network,” The Journal of Power and Energy, Part A of the Proceedings of the Institution of Mechanical Engineers, vol. 233, no. 5, pp. 604-615, 2019.
[14] H. Shang，B. Zhang,Z. Wang and J.A. Scott，“Feedforward control for an industrial nickel smelter roaster off-gas system”，19th International Congress of Chemical and Process Engineering in Prague，Czech Republic，2010.8.28-2010.9.1
