马战国

作者:发布者:董亮发布时间:2025-04-14浏览次数:1549

哈尔滨理工大学自动化学院

研究生指导教师简介

姓    名

马战国

性    别

出生年月

1982.03

导师类别

硕士生导师

(学硕和专硕)

技术职称

讲师

任职部门

自动化系

E_mail

mazhanguo@hrbust.edu.cn

电    话

18904613895

教育经历

2002.09-2006.07,哈尔滨工程大学,    自动化,         学士

2006.09-2008.07,哈尔滨工业大学,    控制科学与工程, 硕士

2013.09-2018.01,哈尔滨工程大学,    核科学与技术,   博士

工作经历

2008.07-2012.10,北京广利核系统工程有限公司,    工程师

2018.01-2021.10,哈尔滨工程大学核科学与技术学院,工程师

2019.10-2020.10,布里斯托大学工学院土木工程系,  访问学者

2021.10-至今,   哈尔滨理工大学自动化学院,      讲师

研究领域及方向

  1. 研究领域(学科)

  •  控制科学与工程

  •  核科学与技术

2. 主要研究方向

  •  人工智能、机器学习与深度学习

  •  状态监测、预测与故障诊断

  •  系统可靠性分析

3. 个人简介

马战国,工学博士,讲师,硕士生导师,主要从事系统和设备状态监测、预测与故障诊断研究工作,解决机器学习与深度学习、大模型等人工智能技术在核能领域、轨道交通领域的应用与开发。累计主持或参与相关科研项目10余项。荣获哈尔滨理工大学第九届亚洲冬季运动会优秀志愿者和中国商业联合会服务业科技进步二等奖。授权国家发明专利1项,软著3项,出版专著2部,发表学术论文30余篇,其中SCI检索10余篇。参与完成核能开发、装备预研等课题。


2022年任硕导以来,指导硕士研究生7人,已毕业3人,其中2人获国家奖学金。

科研项目

1. 主持或参与纵向课题

  1.  核动力装置智能运维技术,装备发展部,202410月至202512月,参与,技术负责人,已结题。

  2.  英国商务能源与产业战略部(BEIS),英国国家核电研发计划,核电仪控系统测试性(R3.9.10“Improving C&I Design for Testability”)201905月至202109月,参与。

  3.  英国商务能源与产业战略部(BEIS),英国国家核电研发计划,核电仪控系统可靠性(R3.9.11“Reliability Limits of Programmable Protection Systems”)201905月至202109月,参与。

  4.  核动力装置在线监测与运行支持技术研究,国防科工局核能开发项目,201601月至201912月,参与。

2. 主持横向课题

  1. ADANES燃烧器仪控系统设计与仿真系统开发,横向课题,20267月至20277月,主持,在研。

  2.  核动力系统智能运行辅助决策算法模型开发,横向课题,20265月至20275月,主持,在研。

  3.  核事故仿真模型不确定性测试,横向课题,20265月至20268月,主持,在研。

  4.  工业时序数据处理通用算子封装及测试,横向课题,20266月至202612月,主持,在研

  5. 智能故障诊断及辅助决策系统软件研发项目,横向课题,20224月至20234月,参与,技术负责人,已结题。

代表性科研论文

  1. Zhanguo MA*, Shurui Ren, and etc. A nuclear power plant open set fault recognition method based on dual mode negative sample generation and distance guided learning, Annals of nuclear energy. 2026, 238. (SCI).

  2. Zhanguo MA*, Dihao Zheng, and etc. Multi-step forecasting of key parameters based on text data and time series data for nuclear power plant, Annals of nuclear energy. 2026, 235. (SCI: WOS:001747207200001).

  3. Zhanguo MA*, Long Tian, and etc. Research on fault differentiation methods for similar faults based on multiple Gated memory graph convolutional networks (M−GM−GCN), Annals of nuclear energy. 2026, 226. (SCI: WOS: 001562458000001).


  1. Zhanguo MA*, Jing Cui, and etc. Fault diagnosis study for nuclear power plants under imbalanced fault sample datasets based on deep learning, Annals of nuclear energy. 2025, 223. (SCI: WOS: 001511701200004).

  2. Zhanguo MA*, Wenhao Jia, and etc. An interpretable deep transfer learning method for fault diagnosis of nuclear power plants under multiple power level conditions, Annals of nuclear energy. 2025, 222. (SCI: WOS: 001513360600001).

  3. Wenhao Jia, Zhanguo Ma*, and etc. A temporal transfer learning model with adaptive batch normalization for fault diagnosis of nuclear power plants under multiple power levels, ICONE32, 2025. (EI).


  1. Zhanguo MA*, Shiguang Deng, and etc. Expert knowledge modelling software design based on Signed Directed Graph with the application for PWR fault diagnosis, Annals of nuclear energy. 2024, 196. (SCI: WOS: 001115077600001; EI: 20234615055696).

  2. Jing Cui, Lei Song, Zhanguo MA*, and etc. Deep learning based key parameters prediction in nuclear power plants, 14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024, (EI: 20250617807351).


  1. Zhuoran Zhou, Zhanguo Ma*, Yingying Jiang and Minjun Peng. Fault Diagnosis Using Bond Graphs in an Expert System, Energies2022, 15(15), 5703 (SCI)

  2. Zhanguo MA,Xinkai LIU, Minjun PENG, etc., Failure Mode Effects and Criticality Analysis for Nuclear Fuel Reliability Improvement of a Commercial PWR, ISSNP 2021.

  3. Zhanguo MA, Minjun PENG, Hidekazu YOSHIKAWA, etc., A Safety-Critical Software Reliability Analysis Method Based On Statistical Model Checking And Bayesian TheoryICONE27, 2019 (EI20193507377554).

  4. Zhanguo MA, Hidekazu YOSHIKAWA, Ming YANG, A human-machine interaction design and evaluation method by combination of scenario simulation and knowledge base,Journal of Nuclear Science and Technology, 2018, 55:5, 516-529 (SCI: WOS: 000428678300006; EI: 20175204585076).

  5. Zhanguo Ma, Hidekazu Yoshikawa, Takashi Nakagawa and Ming Yang, Knowledge-based software design for Defense-in-Depth Risk monitor system and application for AP1000, Journal of Nuclear Science and Technology, 2017, 54:5, 552-568 (SCI:WOS: 000399483900005; EI: 20170903386006).

  6. Zhanguo MA, Hidekazu YOSHIKAWA, Ming YANG, Reliability model of the digital reactor protection system considering the repair time and common cause failure, Journal of Nuclear Science and Technology, 2017, 54:5, 539-551 (SCI: WOS: 000399483900004; EI: 20171003424646).

  7. Zhanguo MA, Hidekazu YOSHIKAWA, Ming YANG, Module level reliability performance evaluation of digital reactor protection system considering the repair and common cause failure, Annals of nuclear energy. 2017, 110, 805-817. (SCI: WOS: 000412251000071; EI:20173204028509).

  8. Zhanguo Ma, Hidekazu Yoshikawa, Ming Yang, The reliability model for the FPGA-based instrument and control system using Colored Petri Net, ICONE25, 2017 (EI:20174404360639).

  9. MA Zhanguo, YANG Ming, Knowledge-based software design for Defense-in-Depth risk monitor system with the preliminary study for AP1000 application, International Journal of Nuclear Safety and Simulation, Vol. 7, Number 1, 2017.

  10. MA Zhanguo, YOSHIKAWA Hidekazu, NAWAZ Amjad, YANG Ming, Developmental Study of Advanced Human Interface System Design Method for Digital I&C+HMIT -A Preliminary Study for Passive Safety PWR AP1000, International Journal of Nuclear Safety and Simulation, Vol. 7, Number 2, 2017.

  11. Ma Zhanguo, Yoshikawa Hidekazu, Yang Ming, Function-centered modeling of the Digital Instrument and Control system using the colored Petri net, ICONE23, 2015 (EI: 20160902019370).

  12. MA Zhanguo, YOSHIKAWA Hidekazu, YANG Ming, Global generic model for reliability analysis of the digital instrumentation and control systems, International Journal of Nuclear Safety and Simulation, Vol. 6, Number 1, 2015.

  13. Zhanguo Ma, Hidekazu Yoshikawa, Takashi Nakagawa, Development of Knowledge-based Software Tools for Defense-in-Depth Risk Monitor System, Transactions of the American Nuclear Society -2015 ANS Winter Meeting and Nuclear Technology Expo.

代表性专利、专著

  1. 译著:《可靠性工程中的建模与仿真分析》,哈尔滨工程大学出版社,202501月,39.5万字。

  2. 译著:先进重水反应堆空间控制策略,哈尔滨工程大学出版社,202105月,24.9万字。


  1. 授权专利:一种基于可解释深度迁移学习的核电厂故障诊断方法,ZL202411799329.9,马战国等,授权发明专利

社会、学会及学术兼职

 担任Journal of nuclear science and technologyProgress in nuclear energyNuclear Engineering and DesignAnnals of nuclear energyReliability Engineering & System SafetyInternational Journal of Critical Infrastructure Protection等多个国际期刊审稿人。