基于多层流模型的核动力装置可靠性分析及故障诊断方法研究
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摘要
在确保核安全的基础上实现良好的经济性是核电长期可持续发展的动力,可靠性分析技术是保障核电厂安全性、可靠性和经济性的重要手段。可靠性分析技术不仅可以定量评估设备可靠性对核电厂安全性和可用性的贡献,用于优化定期测试和在役检查周期,制定最佳的维修策略,而且可以揭示设备的故障原因和对系统运行和安全的影响,用于改进设计提高系统的固有可靠性和安全性,或者辅助运行人员进行故障诊断、制定应急规程或防范措施以消除和缓解故障影响。
论文来源于国家自然科学基金和“十二五”核能开发项目,目的是在改进多层流模型(MFM)建模理论的基础上,研究基于MFM的核电厂可靠性分析方法及其在故障诊断中的应用,论文的主要工作如下：
针对传统的MFM只能描述系统静态特性的问题,论文首先通过引入逻辑门、逻辑属性、基本目标、时间点和信号等新概念,对MFM建模方法进行了补充和改进,改进后的MFM可以更清晰地描述系统和设备之间的可靠性逻辑关系,同时也可以描述系统和设备的阶段任务和时序关系。
论文提出了利用MFM层次化流结构进行可靠性分析的基本方法和特征量,提出了两状态系统可靠性分析方法和结合决策表分析的多状态系统可靠性分析方法,提出了MFM生成GO-FLOW模型方法,可以分析有阶段任务的动态系统可靠性问题。
为了进行可靠性定性分析,论文提出了基于MFM的故障模式及影响分析(FMEA)方法,遵循守恒原理沿着MFM的流结构依次分析功能故障的原因和影响,方法简便且不容易遗漏重要的失效模式。在此基础上,论文给出了两状态系统MFM生成故障树方法,通过将MFM功能元件依次生成故障树模型、选择顶事件后连接各元件故障树模型并断开逻辑环路,可以对导致顶事件发生的最小割集、元件的重要度和敏感度等可靠性指标进行定性分析。
论文将MFM可靠性定性分析方法应用于核电厂故障诊断领域,提出了一种综合故障诊断技术,集成了三种故障诊断方法：警报分析法根据守恒原理分析功能故障状态之间的因果关系,通过排除结果性警报,在实现警报压缩功能同时,给出可能的故障集；最小割集法以警报分析法为基础,通过进一步将多状态MFM转化为故障树模型,可以求解系统当前异常状态的最小故障模式；针对警报限值的设定对警报分析法和最小割集法可能造成的影响,论文提出了基于Bayesian原理的不确定性推理方法,通过将具有不确定性因果关系的多状态MFM转化为故障树模型,可以定量给出导致系统故障状态的近似却又合理的解释,在操纵员利用深层次知识进行故障诊断时可以辅助决策。
论文对MFM图形化建模平台、基于MFM的可靠性分析程序和基于MFM的核电厂故障诊断系统进行了设计和开发,可以通过简单的鼠标和键盘操作快速生成和修改系统MFM,通过一次分析可以评价多个系统目标和组态变化,并可处理多状态、时延、时序和阶段任务等问题,可以分析设备故障原因及其对系统可运行性和安全性的影响,综合了基于目标、基于规则、基于风险和基于专家经验的特点,采用统一的建模语言和建模平台,辅助操纵员全面了解系统运行要求,进行推理判断并深入了解系统设计和运行中的薄弱环节,具有良好的工程实践前景。
To realize good economy on the basis of ensuring nuclear safety is a driving force for the long-term and sustainable development of nuclear power in the world. Reliability analysis technology is one of the most important means to guarantee the safety, reliability and economy of nuclear power plant. Reliability analysis technology can be applied for the quantitative assessment of the reliability of equipments and their contributions to the safety and availability of the whole system, which can support various tasks, such as the optimization of periodic test and in-service inspection period, and making best maintenance strategies as well. Reliability analysis technology can also be applied for revealing equipment faults and their effects on the system operation and safety, which will lay a solid basis for improving the inherent system reliability and safety by revising design, assisting operators in their tasks of fault identification, making emergency operating procedures, or making preventive measures to avoid and release the fault consequence.
_This thesis, partially supported by National Natural Science Foundation of China (NSFC) and Chinese Nuclear Development Project in the National12th Five-year Plan, aims at developing a new reliability analysis method and a comprehensive fault diagnosis technology by improving the methodology of Multilevel Flow Models (MFM). The main works of this thesis are summarized as follows.
For solving the problem that the traditional MFM can only describe static characteristics of a system, this thesis improves the MFM methodology by introducing some new concepts including logic gate, logic attribute, basic goal, time point, and signal. The improved MFM can clearly describe not only the reliability logical relations, but also the time consequence relations of the system and equipments with phased missions.
This thesis presents a fundamental method and characteristic quantities for reliability analysis by utilizing the MFM hierarchical flow structure. The algorithms for calculating the reliability of a system with two states and multiple-states are presented, respectively. Especially, a method for solving dynamic reliability problems by mapping MFMs into GO-FLOW models is given and discussed in detailed.
For the qualitative reliability analysis, this thesis presents a Failure Mode and Effect Analysis (FMEA) method based on MFM which can be used for analyzing the causes of the functional faults and their effects along MFM flow structures using conservation principles. The proposed FMEA method is easy to be implemented and can avoid overlooking important failure modes of the system. On the basis of FMEA, a fault tree generation method for two-state system is proposed by mapping MFM elements into mini fault trees, selecting a top event, connecting the relevant mini fault trees and breaking the logic loops. In this way, the reliability indexes including the minimal cut sets, element importance and sensitivity can be qualitatively analyzed.
Finally, this thesis applies above qualitative reliability analysis methods into the fault diagnosis field of nuclear power plant. A comprehensive fault diagnosis technology consisting of three fault diagnosis methods based on MFM is proposed. An alarm analysis method is proposed to analyze the causalities between alarm states of MFM functions. The alarm reduction can be realized by excluding the consequential alarms and a list of possible causes will be given. A minimal cut set method is presented to offer minimal failure modes of the current abnormal system state by mapping the MFMs with multiple states into fault trees. For solving the common limitation of qualitative reasoning methods that the alarm thresholds may greatly affect diagnosis results, this thesis presents an uncertainty diagnosis method based on Bayesian theory which can provide approximate, but reasonable explanations to the current abnormal system state based on the analysis of a fault tree model mapped from the MFM with uncertainty causalities.
A graphical modeling platform, a program for the reliability analysis and a fault diagnosis system for nuclear power plant are designed and developed. The system MFM can be easily built by simple mouse and keyboard operations. Multiple system goals and configurations can be exactly evaluated through one computer calculation. The proposed technologies can be used for analyzing the reliability issues of a system with multiple-state, time delay, time-consequence and phased mission characteristics. In addition, by combining the advantages of goal-based, rule-based, risk-based and expert experience based methodologies into one framework, the proposed technologies can help operators have a comprehensive understanding to the system requirements, perform fault diagnosis and have an insight of the risk in system operation, which shows a good foreground in engineering application.
论文来源于国家自然科学基金和“十二五”核能开发项目,目的是在改进多层流模型(MFM)建模理论的基础上,研究基于MFM的核电厂可靠性分析方法及其在故障诊断中的应用,论文的主要工作如下：
针对传统的MFM只能描述系统静态特性的问题,论文首先通过引入逻辑门、逻辑属性、基本目标、时间点和信号等新概念,对MFM建模方法进行了补充和改进,改进后的MFM可以更清晰地描述系统和设备之间的可靠性逻辑关系,同时也可以描述系统和设备的阶段任务和时序关系。
论文提出了利用MFM层次化流结构进行可靠性分析的基本方法和特征量,提出了两状态系统可靠性分析方法和结合决策表分析的多状态系统可靠性分析方法,提出了MFM生成GO-FLOW模型方法,可以分析有阶段任务的动态系统可靠性问题。
为了进行可靠性定性分析,论文提出了基于MFM的故障模式及影响分析(FMEA)方法,遵循守恒原理沿着MFM的流结构依次分析功能故障的原因和影响,方法简便且不容易遗漏重要的失效模式。在此基础上,论文给出了两状态系统MFM生成故障树方法,通过将MFM功能元件依次生成故障树模型、选择顶事件后连接各元件故障树模型并断开逻辑环路,可以对导致顶事件发生的最小割集、元件的重要度和敏感度等可靠性指标进行定性分析。
论文将MFM可靠性定性分析方法应用于核电厂故障诊断领域,提出了一种综合故障诊断技术,集成了三种故障诊断方法：警报分析法根据守恒原理分析功能故障状态之间的因果关系,通过排除结果性警报,在实现警报压缩功能同时,给出可能的故障集；最小割集法以警报分析法为基础,通过进一步将多状态MFM转化为故障树模型,可以求解系统当前异常状态的最小故障模式；针对警报限值的设定对警报分析法和最小割集法可能造成的影响,论文提出了基于Bayesian原理的不确定性推理方法,通过将具有不确定性因果关系的多状态MFM转化为故障树模型,可以定量给出导致系统故障状态的近似却又合理的解释,在操纵员利用深层次知识进行故障诊断时可以辅助决策。
论文对MFM图形化建模平台、基于MFM的可靠性分析程序和基于MFM的核电厂故障诊断系统进行了设计和开发,可以通过简单的鼠标和键盘操作快速生成和修改系统MFM,通过一次分析可以评价多个系统目标和组态变化,并可处理多状态、时延、时序和阶段任务等问题,可以分析设备故障原因及其对系统可运行性和安全性的影响,综合了基于目标、基于规则、基于风险和基于专家经验的特点,采用统一的建模语言和建模平台,辅助操纵员全面了解系统运行要求,进行推理判断并深入了解系统设计和运行中的薄弱环节,具有良好的工程实践前景。
To realize good economy on the basis of ensuring nuclear safety is a driving force for the long-term and sustainable development of nuclear power in the world. Reliability analysis technology is one of the most important means to guarantee the safety, reliability and economy of nuclear power plant. Reliability analysis technology can be applied for the quantitative assessment of the reliability of equipments and their contributions to the safety and availability of the whole system, which can support various tasks, such as the optimization of periodic test and in-service inspection period, and making best maintenance strategies as well. Reliability analysis technology can also be applied for revealing equipment faults and their effects on the system operation and safety, which will lay a solid basis for improving the inherent system reliability and safety by revising design, assisting operators in their tasks of fault identification, making emergency operating procedures, or making preventive measures to avoid and release the fault consequence.
_This thesis, partially supported by National Natural Science Foundation of China (NSFC) and Chinese Nuclear Development Project in the National12th Five-year Plan, aims at developing a new reliability analysis method and a comprehensive fault diagnosis technology by improving the methodology of Multilevel Flow Models (MFM). The main works of this thesis are summarized as follows.
For solving the problem that the traditional MFM can only describe static characteristics of a system, this thesis improves the MFM methodology by introducing some new concepts including logic gate, logic attribute, basic goal, time point, and signal. The improved MFM can clearly describe not only the reliability logical relations, but also the time consequence relations of the system and equipments with phased missions.
This thesis presents a fundamental method and characteristic quantities for reliability analysis by utilizing the MFM hierarchical flow structure. The algorithms for calculating the reliability of a system with two states and multiple-states are presented, respectively. Especially, a method for solving dynamic reliability problems by mapping MFMs into GO-FLOW models is given and discussed in detailed.
For the qualitative reliability analysis, this thesis presents a Failure Mode and Effect Analysis (FMEA) method based on MFM which can be used for analyzing the causes of the functional faults and their effects along MFM flow structures using conservation principles. The proposed FMEA method is easy to be implemented and can avoid overlooking important failure modes of the system. On the basis of FMEA, a fault tree generation method for two-state system is proposed by mapping MFM elements into mini fault trees, selecting a top event, connecting the relevant mini fault trees and breaking the logic loops. In this way, the reliability indexes including the minimal cut sets, element importance and sensitivity can be qualitatively analyzed.
Finally, this thesis applies above qualitative reliability analysis methods into the fault diagnosis field of nuclear power plant. A comprehensive fault diagnosis technology consisting of three fault diagnosis methods based on MFM is proposed. An alarm analysis method is proposed to analyze the causalities between alarm states of MFM functions. The alarm reduction can be realized by excluding the consequential alarms and a list of possible causes will be given. A minimal cut set method is presented to offer minimal failure modes of the current abnormal system state by mapping the MFMs with multiple states into fault trees. For solving the common limitation of qualitative reasoning methods that the alarm thresholds may greatly affect diagnosis results, this thesis presents an uncertainty diagnosis method based on Bayesian theory which can provide approximate, but reasonable explanations to the current abnormal system state based on the analysis of a fault tree model mapped from the MFM with uncertainty causalities.
A graphical modeling platform, a program for the reliability analysis and a fault diagnosis system for nuclear power plant are designed and developed. The system MFM can be easily built by simple mouse and keyboard operations. Multiple system goals and configurations can be exactly evaluated through one computer calculation. The proposed technologies can be used for analyzing the reliability issues of a system with multiple-state, time delay, time-consequence and phased mission characteristics. In addition, by combining the advantages of goal-based, rule-based, risk-based and expert experience based methodologies into one framework, the proposed technologies can help operators have a comprehensive understanding to the system requirements, perform fault diagnosis and have an insight of the risk in system operation, which shows a good foreground in engineering application.
引文
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