核电厂设备冷却水系统动态可靠性评估方法

An Approach for Dynamic Reliability Assessment of Equipment Cooling Water System for Nuclear Power Plant

核电厂设备冷却水系统作为一类双重冗余的系统,存在复杂的动态时序失效行为。传统故障树分析法缺乏对时间因素的描述,对设备冷却水系统中的动态时序问题分析假设过于保守。针对上述故障树分析法的局限性,结合动态故障树(dynamic fault tree, DFT)和动态贝叶斯网络(dynamic Bayesian network, DBN),提出了一种核电厂设备冷却水系统动态可靠性评估方法。首先在设备冷却水系统结构功能的基础上构建系统DFT模型;然后根据转化规则将DFT模型转化为DBN模型;最后通过DBN正向推理得到设备冷却水系统可靠度曲线,反向推理得到根节点的后验概率排序,敏感性分析识别系统薄弱环节。评估结果表明:所提出的方法能够为提高系统智能维修维护水平和可靠性提供依据。

As a kind of repairable system with double redundancy, equipment cooling water system has complex dynamic time series failure behaviors. Due to the lack of description of time factors in traditional fault tree analysis, the analysis assumption is too conservative for such dynamic time series problems of equipment cooling water system. In view of the above limitations of fault tree analysis, dynamic fault tree(DFT) and dynamic Bayesian network(DBN) were combined to propose an approach for dynamic reliability assessment of equipment cooling water system for nuclear power plant. Firstly, the DFT model was constructed based on the systemic architecture. Secondly, the DFT model was converted into the DBN model according to the conversion rules. Finally, the reliability curve of equipment cooling water system was obtained based on the forward inference of DBN, the posterior probabilities of root nodes were obtained and sorted out based on the backward inference of DBN, the vulnerabilities of system were recognized though sensitivity analysis. The assessment results show that the proposed method can provide basis for improving the intelligent maintenance and reliability level of system.