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面向数据缺失情况下水淹天然气管道泄漏风险量化分析的需求,提出一种基于贝叶斯网络(BN)和模糊集理论(FST)的概率风险分析方法。首先采用故障树分析(FTA)法分析水淹天然气管道泄漏失效致因,并映射得到相应的BN模型;然后针对基本事件失效概率数据缺失的情况,用专家知识引出概率,替代缺失的统计失效概率;为处理概率引出过程中专家知识的模糊性和主观性导致的不确定性,结合FST与多专家层次分析引出模糊概率,将其作为实际先验概率输入BN模型,进行量化分析。以某复线水淹天然气管道为例,应用所提方法分析其泄漏风险,结果表明:用该方法能够在数据缺失情况下表征并量化泄漏风险,同时BN的正向预测和概率更新能力可用来评估动态风险、识别关键失效因素。
To meet the need of quantitative analysis of the risk of flooding natural gas pipelines in the absence of data, a probabilistic risk analysis method based on Bayesian Network (BN) and Fuzzy Set Theory (FST) is proposed. Firstly, the cause of leakage failure of flooded natural gas pipeline is analyzed by fault tree analysis (FTA) method, and the corresponding BN model is mapped. Then, in the case of missing data of failure probability of basic event, the probability of expert knowledge is introduced to replace the missing probability of statistical failure In order to deal with the ambiguity and subjectivity of expert knowledge in the process of probabilistic deduction, the fuzzy probability is derived from the analysis of FST and multi-expert level analysis, and then is input into the BN model as the actual prior probability for quantitative analysis. Taking a double-flooded natural gas pipeline as an example, the proposed method is applied to analyze the risk of leakage. The results show that this method can be used to characterize and quantify the risk of leakage in the absence of data. At the same time, the positive predictive and probabilistic updating ability of BN can be used to evaluate Dynamic risk, identifying key failure factors.