煤矿事故智能应急预案生成方法研究
Research on generation method of intelligent emergency preplan for coal mine accident
张晓蕾 1高进东 2赵开功 3李严肃 4李长明 5谢子彬4
作者信息
- 1. 中国矿业大学(北京) 应急管理与安全工程学院,北京 100083;中国安全生产科学研究院,北京 100012
- 2. 中国安全生产科学研究院,北京 100012
- 3. 北京科技大学 土木与资源工程学院,北京 100083
- 4. 中国矿业大学(北京) 应急管理与安全工程学院,北京 100083
- 5. 中国矿业大学(北京) 应急管理与安全工程学院,北京 100083;国能网信科技(北京)有限公司,北京 100011
- 折叠
摘要
为了实现应急预案数字智能化管理,快速生成精准有效的救援方案,采用网络爬虫技术从事故案例及事发后状况中获取基础数据,并对数据进行结构化处理;构建一种分层结构化应急预案生成模型,结合模糊综合评价法与层次分析法对应急预案进行有效性评估,形成了煤矿事故数字智能化应急预案系统.选取煤矿瓦斯爆炸事故,验证"8·29"肖家湾煤矿瓦斯爆炸事故和"10·31"金山沟煤业瓦斯爆炸事故子事件集合,证明了智能应急预案生成结果和实际情况基本相符.研究结果表明:实时添加事发信息,快速生成可视化预案,自动分析结构化存储,可提高应急预案生成效率与精准性,降低事故灾害风险和损失,提升矿井应急救援保障能力.
Abstract
In order to realize the digital intelligent management of emergency preplans and quickly generate accurate and effective rescue plans,the web crawler technology was used to obtain basic data from accident cases and post-incident situations,and the data was structured and processed.Constructing a hierarchical and structured emergency preplan generation model,combining fuzzy comprehensive evaluation method and analytic hierarchy process to evaluate the effectiveness of emergency preplans,forming a digital intelligent emergency preplan system for coal mine accidents.Selecting coal mine gas explosion accidents,verifying the sub event sets of"August 29"Xiaojiawan Coal Mine gas explosion accident and"October 31"Jinshangou Coal Industry gas explosion accident,proving that the results of intelligent emergency plan generation were basically consistent with the actual situation.The research results indicate that real-time addition of incident information,rapid generation of visual contingency plans,automatic analysis of structured storage can improve the generation efficiency and accuracy,reduce the accident disaster risks and losses,and improve the ability of mine emergency rescue support.
关键词
煤矿事故/应急预案/智能化/结构化/案例库/规则推理模型Key words
coal mine accident/emergency preplan/intelligent/structuring/case base/rule inference model引用本文复制引用
基金项目
国家重点研发计划项目(2016YFC0801805)
中国安全生产科学研究院基本科研项目(2023JBKY20)
出版年
2024
NETL
NSTL
万方数据