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作 者:郑梦琰 李坤祥 隋阳 ZHENG Mengyan;LI Kunxiang;SUI Yang(School of Nuclear Science and Technology,University of South China,Hengyang 421001,Hunan,China;Fujian Fuqing Nuclear Power Co.,Ltd,Fuqing 350300,Fujian,China)
机构地区:[1]南华大学核科学技术学院,湖南衡阳421001 [2]福建福清核电有限公司,福建福清350300
出 处:《原子核物理评论》2024年第4期1106-1112,共7页Nuclear Physics Review
基 金:国家自然科学基金资助项目(52174189)。
摘 要:传统静态可靠性评估方法难以表征核电厂数字化控制系统的动态交互性和时间依赖性。为了解决这一问题,以数字化主给水控制系统(DMFCS)为研究对象,提出了一种基于动态故障树(DFT)和动态贝叶斯网络(DBN)的动态可靠性评估方法,对DMFCS进行动态可靠性评估。首先,应用DFT方法,建立了表征DMFCS动态交互性的DFT模型;然后,应用DFT至DBN的转换策略,建立了表征DMFCS动态交互性和时间依赖性的DBN模型;最后,通过DBN正向推理计算得到了DMFCS随时间变化的可靠度曲线,逆向推理计算得到了根节点的后验概率,重要度分析识别了系统薄弱环节。结果表明:所提方法能够很好地描述DMFCS的动态交互性和时间依赖性,分析结果为系统智能维护、日常检修提供了科学依据,进一步提高了DMFCS可靠性和安全性。Traditional static reliability assessment methods face challenges in characterizing the dynamic interaction and time dependency of digital control systems in nuclear power plants.To address this issue,this study proposes a dynamic reliability assessment method integrating dynamic fault tree(DFT)and dynamic Bayesian network(DBN)for digital main feedwater control system(DMFCS).First,DFT method was applied to establish a DFT model which characterized the dynamic interaction of DMFCS.Subsequently,the conversion strategy from DFT to DBN was implemented to construct a DBN model which characterized the time dependency of DMFCS.Finally,the DBN forward inference was conducted to obtain the reliability curve of DMFCS,while the DBN backward inference was conducted to calculate the posterior probabilities of root nodes,and the importance analysis was implemented to identify the vulnerable parts in the system.The results demonstrated that the proposed method can effectively characterize both dynamic interaction and time dependency of DMFCS,and the analytical outcomes provided scientific guidance for intelligent maintenance and routine inspections,thereby further enhancing the reliability and safety for DMFCS.
关 键 词:核电厂 数字化主给水控制系统 动态可靠性评估 动态故障树 动态贝叶斯网络
分 类 号:TL364[核科学技术—核技术及应用]
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