地铁健康监测PCBN模型的参数相关性分析

对城市盾构地铁结构的健康服役和安全可靠性进行评价时,多局限于静态推理,通过构建PCBN(Pair-Copula Bayes Network)网络结构得到评判指标的多元联合概率分布,实现参数相依性的准确识别和高精度重构。基于3种失效模式对盾构地铁结构节点相关性分析及安全状态评价,充分挖掘监测数据的隐藏信息,表征盾构地铁结构的风险状态。以武汉地铁三号线某空推段为工程背景进行PCBN模型建模。结果表明:PCBN模型得出的地铁安全状态与地铁工程中的实际风险信息非常吻合,体现了构建PCBN网络模型的准确性和实用性。

Correlation analysis of parameters in PCBN model for metro health monitoring

At present, the most common method to evaluate the health service and safety reliability of urban shield metro structures is limited to static analysis. In this paper, by applying the concept of Pair-Copula to Bayesian networks, the multi-joint probability distribution of evaluation index was obtained by constructing PCBN (Pair-Copula Bayes Network) structure, which is capable of identifying parameters'' dependencies accurately and high-precision reconstruction. Based on the three kinds of failure modes, the correlation analysis and safety evaluation of shield metro structure nodes were conducted. The implicit information in monitoring data was exploited to characterize the risk status of the shield metro structure. As an example, an empty pushing section of Wuhan Metro Line 3 is used to build a PCBN model. Results show that the metro safety status obtained by the PCBN model is in good agreement with the actual risk information in the subway project, demon strating the accuracy and practicability of the PCBN network model proposed in this paper.