H. Wang*, M.J. Peng, Z. Miao, et al. Remaining useful life prediction techniques for electric valves based on convolution auto encoder and long short term memory[J]. ISA Transactions, 2021(108): 333-342.  H. Wang*, M.J. Peng, A. Ayodeji, et al. Advanced fault diagnosis method for nuclear power plant based on convolutional gated recurrent network and enhanced particle swarm optimization[J]. Annals of Nuclear Energy, 2021, 151: 107934.  H. Wang*, M.J. Peng, R.Y. Xu, et al. Remaining Useful Life Prediction Based on Improved Temporal Convolutional Network for Nuclear Gate Valves, Frontiers in Nuclear Energy, 2020, 11: 584463.  H. Wang*, M.J. Peng, Y.K. Liu, et al. Remaining Useful Life Prediction Techniques of Electric Valves for Nuclear Power Plants with Convolution Kernel and LSTM, Science and Technology of Nuclear Installations, 2020: 8349349.  Hang WANG (*), Min-jun Peng, Yue Yu, et al. Fault identification and diagnosis based on KPCA and similarity clustering for nuclear power plants. Annals of Nuclear Energy, 2020, 85: 259-270.  Y. Yu, M.J. Peng, H. Wang*, et al. Improved PCA model for multiple fault detection, isolation and reconstruction of sensors in nuclear power plant[J]. Annals of Nuclear Energy, 2020, 148: 107662.  Hanan A. Saeed, Hang WANG (*), Min-jun Peng, et al. Online fault monitoring based on deep neural network and sliding window technique. Progress in Nuclear Energy, 2020 (121): 103236  Hanan A. Saeed, Min-jun Peng, Hang WANG (*), Bo-wen Zhang. Novel fault diagnosis scheme utilizing deep learning networks. Progress in Nuclear Energy, 2020 (118): 103066  Hang WANG (*),Min-jun PENG, et al. A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants. ISA Transactions, 2019, 95: 358-371.  Min-jun PENG(*), Hang WANG, Shan-shan CHEN, et al. An Intelligent Hybrid Methodology of On-line System-level Fault Diagnosis for Nuclear Power Plant. Nuclear Engineering and Technology, 2018, 50(3): 396-410.  Min-jun PENG(*), Hang WANG, Xu YANG, et al. Real-time Simulations to Enhance Distributed On-line Monitoring and Fault Detection in Pressurized Water Reactors. Annals of Nuclear Energy, 2017, 85: 259-270.  Hang WANG, Min-jun PENG (*), et al. On-line Monitoring for Turbine Bypass System Based on real-time simulation. 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 Volume 1, 2017, Pages 47-56, San Francisco, United States.  Hang WANG (*),Min-jun PENG, et al. An integrated data-driven methodology for early fault detection and diagnosis in nuclear power plant. International Journal of Nuclear Safety and Simulation (IJNS), 2017, Vol.8 No.3: 225-238.  Hang WANG(*), Min-jun PENG, Peng WU, Shou-yu CHENG. Improved methods of online monitoring and prediction in condensate and feed water system of nuclear power plant. Annals of Nuclear Energy, 2016, 90: 44-53.  Hang WANG (*),Min-jun PENG and Shou-yu CHENG. Online Fault diagnosis and Prediction of Condenser in Nuclear Power Plant. ANS 2015 Winter Meeting & Expo, Washington D.C, America, November 7-13, 2015.  王航*，彭敏俊、徐仁义、刘永阔. 基于卷积核和GRU网络的核电厂阀门故障预测方法[J]. 核电(重大设备可靠性提升及数据智能应用专辑), 2020, 5: 49-54.  Liu, Jie; Peng, Minjun; Wang, Hang; Gong, Meijie, Development of distributed performance monitoring and analysis system for nuclear power Plant., 27th International Conference on Nuclear Engineering: Nuclear Power Saves the World!, ICONE 2019 , 2019-05-19 To 2019-05-24.  郭良壮, 彭敏俊, 王航, 等. 核电厂蒸汽旁排系统故障诊断与状态预测方法研究[C]. 中国核学会2017年学术年会. 威海市. 2017:321-326.  ZHU Hai-shan,WANG Hang, et al. Development and analysis of a detailed parametric simulation model of condensers for nuclear power plants[J]. International Journal of Nuclear Safety and Simulation (IJNS). 2014,5(4):347-357. Li Wei, Peng Min-jun, Wang Hang, et al. Design of comprehensive diagnosis system in nuclear power plant[J]. Annals of Nuclear Energy. 2017,109:92-102.