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| 基于贝叶斯推断的公路隧道施工风险概率评估方法 |
| A Bayesian Inference–based Risk Probability Assessment Method for Highway Tunnel Construction |
| 投稿时间：2025-11-22 |
| DOI：10.16018/j.cnki.cn32-1650/n.202601007 |
| 中文关键词: 隧道施工 施工风险评估 多源监测数据 动态贝叶斯推断 风险概率 不确定性量化 |
| 英文关键词: tunnel construction construction risk assessment multi-source monitoring data dynamic Bayesian inference risk probability uncertainty quantification |
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| 中文摘要: |
| 针对隧道施工过程中围岩条件复杂、施工扰动频繁,传统基于静态阈值或单一监测指标的风险评价方法难以准确反映施工风险的动态变化问题,本文提出一种基于多源监测数据与动态贝叶斯推断的隧道施工风险概率评估方法,通过对围岩内部位移、围岩压力、锚杆轴力和钢拱架应力等监测信息的数据同步、异常处理与特征重构,建立统一的时序监测特征体系;构建动态贝叶斯网络模型,实现风险概率随施工推进的递推更新;最后结合工程实例对模型进行验证。结果表明,风险后验概率随施工过程呈现出明显的阶段性演化特征,即在初期支护稳定阶段风险水平较低,在掌子面推进及强扰动阶段风险概率显著升高,在支护体系形成后逐步回落;该演化特征与围岩变形发展及支护受力调整过程具有良好一致性。 |
| 英文摘要: |
| Given the complex geological conditions and frequent construction disturbances during tunnel excavation, traditional risk evaluation methods based on static thresholds or single monitoring indicators are often unable to accurately reflect the dynamic evolution of construction risks. To address this issue, this study proposes a tunnel construction risk probability assessment method based on multi-source monitoring data and dynamic Bayesian inference. By synchronizing heterogeneous monitoring data, performing anomaly processing and feature reconstruction on surrounding rock internal displacement, surrounding rock pressure, rock-bolt axial force, and steel arch stress, a unified time-series monitoring feature system is established. A dynamic Bayesian network model is then constructed to realize the recursive updating of risk probability with construction progress. Finally, the proposed method is verified through an engineering case study.The results indicate that the posterior risk probability exhibits distinct stage-dependent evolutionary characteristics during construction: the risk level remains low during the initial support stabilization stage, increases significantly during the excavation advance and strong disturbance stage, and gradually decreases after the formation of the support system. This evolutionary trend shows good consistency with the development of surrounding rock deformation and the adjustment of support structural forces. |
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