基于应急预案的煤矿应急救援辅助决策系统设计

Design of coal mine emergency rescue auxiliary decision system based on emergency plan

针对煤矿应急救援辅助决策系统中应急预案应用不足、应用效率低及系统生成的救援方案可执行性欠佳等问题,提出了一种基于应急预案的煤矿应急救援辅助决策系统设计方法。该方法采用基于大语言模型的信息抽取技术,从应急预案中提炼出关键任务要素,如任务名称、触发条件、执行部门和任务内容等,形成元任务,并构建根据事故类型和级别对元任务进行分类存储的元任务库;发生煤矿安全事故时,运用基于SBERT模型的语义匹配技术,根据现场收集的信息进行事故分类分级,并从元任务库中筛选出与当前应急需求相符合的元任务集;为提高任务的可执行性,将元任务与实时采集的现场数据结合,通过指令模板构建具体的行动指令,并利用任务规划技术对指令的优先级进行优化和调整,生成切实可行的现场救援方案。基于应急预案的煤矿应急救援辅助决策系统充分利用了应急预案的规范化内容,形成了与现场信息紧密结合、资源优化的救援方案,进一步提高了救援决策的准确性、科学性和智能化水平。

In the coal mine emergency rescue auxiliary decision system,there are problems such as insufficient application of emergency plans,low application efficiency,and poor execution of rescue plans generated by the system.In order to solve the above problems,a design method for a coal mine emergency rescue auxiliary decision system based on emergency plans is proposed.This method uses information extraction technology based on large language models to extract key task elements from emergency plans,such as task names,triggering conditions,executing departments,and task content.This method forms meta tasks,and constructs a meta task library that classifies and stores meta tasks based on accident types and levels.When a coal mine safety accident occurs,this method uses semantic matching technology based on the SBERT model to classify and grade the accident based on the information collected on site.The method selects the meta task set that matches the current emergency needs from the meta task library.To improve the feasibility of tasks,this method combines meta tasks with real-time collected on-site data,constructs specific action instructions through instruction templates.The method uses task planning techniques to optimize and adjust the priority of instructions,and generate practical and feasible on-site rescue plans.The coal mine emergency rescue auxiliary decision system based on emergency plans fully utilizes the standardized content of emergency plans,forming a rescue plan closely integrated with on-site information and resource optimization.The system further improves the accuracy,scientificity,and intelligence level of rescue decision-making.