基于贝叶斯网络情景分析的含水土质埋压救援现场监测体系研究*

为提高含水土质埋压救援现场救援效率，基于贝叶斯网络进行情景推演分析，明确典型不利情景演化路径和关键节点，构建多方位多因素耦合的含水土质埋压监测体系。研究结果表明:基于贝叶斯网络情景分析的含水土质埋压救援现场监测体系将灾害环境监测、救援人员状态监测、埋压人员状态监测、救援设备状态监测、整体救援进展跟踪监测划分为18个监测单元，明确土质压力等11个关键监测参数及其技术手段。研究结果可有效提高救援行动安全性，为含水土质埋压救援现场安全监测系统研发提供理论支撑。

Research on on-site monitoring system of burial rescue in water-bearing soil based on Bayesian network scenario analysis

In order to improve the rescue efficiency of the water-bearing soil buried pressure rescue site,the scenario deduction analysis was carried out based on Bayesian network to clarify the evolution path and key nodes of typical adverse scenarios,and a multi-directional and multi-factor coupling monitoring system of the burial in the water-bearing soil was constructed.The results showed that the on-site monitoring system of burial rescue in the water-bearing soil based on Bayesian network scenario analysis divided objects into 18 monitoring units,including the disaster environment monitoring,rescuer condition monitoring,buried personnel condition monitoring,rescue equipment condition monitoring and overall rescue progress tracking,and defined 11 key monitoring parameters and corresponding technical means such as the soil pressure.The research results can provide theoretical support for the research and development of on-site safety monitoring system for the burial rescue in water-bearing soil,and improve the safety of rescue operation.