基于贝叶斯分类算法的隧道开挖安全风险概率评价

Probabilistic Evaluation of Tunnel Excavation Safety Risk Based on Bayesian Classification Algorithm

隧道开挖安全风险因子的早期识别及风险评估,对隧道后期施工及安全管理具有重要的指导意义。在收集研究区8条隧道相关资料的基础上确定影响因子,同时结合同类型隧道开挖遇到的主流问题进行分析,采用专家打分法确定了各安全风险因子的权重比例,确定了6个一级安全风险因子和20个二级安全风险因子,并对各一级因子权重进行归一化处理,进而得到各安全风险因子条件概率表和先验概率表,最后利用GeNie2.3软件进行风险评价。研究表明,线路涉及的隧道工程总体安全风险水平为Ⅲ级,各安全风险因子中敏感性较高的为地震(B3)、塌方(B6)及开挖方式的合理性(B15),并在此基础上提出了应对措施。

The early identification and risk assessment of safety risk factors for tunnel excavation are of great guiding significance for the construction and safety management of tunnels in the later stage.The impact factor were determined based on the collection of information on the eight tunnels in the study area.Meanwhile the mainstream problems encountered in the same type of tunnel excavation were discussed.The weight proportion of each safety risk factor was determined using the expert scoring method,and the six primary safety risk factors and twenty secondary safety risk factors were determined.The weights of each primary factor were normalised to determine the conditional probability and prior probability table of each safety risk factor.Finally,GeNie2.3 software was used to evaluate the risk.The research results show that the overall safety risk level of the tunnel involved in the line is levelⅢ,and the most sensitive safety risk factors are earthquake(B3),landslide(B6)and rationality of excavation mode(B15).On this basis,the corresponding countermeasures are proposed.