首页> 外文会议>International Conference on Nuclear Engineering >RESEARCH ON PROBABILISTIC SAFETY ASSESSMENT (PSA) METHOD OF SAFETY CLASS DISTRIBUTED CONTROL SYSTEM (DCS) IN NUCLEAR POWER PLANT BASED ON FUZZY MARKOV PROCESS
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RESEARCH ON PROBABILISTIC SAFETY ASSESSMENT (PSA) METHOD OF SAFETY CLASS DISTRIBUTED CONTROL SYSTEM (DCS) IN NUCLEAR POWER PLANT BASED ON FUZZY MARKOV PROCESS

机译:基于模糊马尔可夫工艺的核电站安全类分布式控制系统(DCS)概率安全评估(PSA)方法研究

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Safety class DCS(Distributed Control System) in nuclear power plant is characterized by multi-state interaction, complex function and unknown fault mechanism, which limits the use of tradition PSA(Probabilistic Safety Assessment) method such as event tree and fault tree. An improved dynamic probabilistic security simulation method is proposed based on fuzzy Markov process to quantitative evaluation the risk of Safety class DCS in nuclear power plant, which resolved the failure uncertainty problem without in-depth understanding of failure mechanism. Firstly, the fuzzy fault tree reliability evaluation model is established based on fuzzy theory and FTA(Fault Tree Analysis), which describes the probability and degree of failure with fuzzy number. Then, the fuzzy fault tree is transformed into fuzzy Markov chain, this model is described mathematically, and the reliability indexes are simulated and analyzed with Monte Carlo simulation method, the change of system safety performance in long-term operation is obtained. Finally, the scientificity and effectiveness is verified by the example of redundant analog output module of safety class DCS in nuclear plant.
机译:核电厂中的安全等级DCS(分布式控制系统)的特点是多状态相互作用,复杂功能和未知故障机制,其限制了传统PSA(概率安全评估)方法,如事件树和故障树。基于模糊马尔可夫过程,提出了一种改进的动态概率安全仿真方法,以定量评估核电站安全级别DCS风险,解决失败的不确定性问题,不深入了解失效机制。首先,基于模糊理论和FTA(故障树分析)建立了模糊故障树可靠性评估模型,其描述了模糊数的故障概率和程度。然后,模糊故障树被转换为模糊马尔可夫链,在数学上描述了该模型,并用蒙特卡罗仿真方法模拟和分析可靠性指标,获得了长期操作中系统安全性能的变化。最后,通过核电站安全等级DCS的冗余模拟输出模块的示例来验证科学性和有效性。

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