基于云计算的分布式煤矿井下作业安全监控方法  

Safety Monitoring Method for Distributed Coal Mine Underground Operation Based on Cloud Computing

作　　者：幸荔芸[1] 王涛[2] XING Liyun;WANG Tao(Chongqing Three Gorges Vocational College,Chongqing 404155,China;Chengdu University of Technology,Chengdu 610059,China)

机构地区：[1]重庆三峡职业学院,重庆404155 [2]成都理工大学,成都610059

出　　处：《煤炭技术》2023年第6期137-140,共4页Coal Technology

基　　金：重庆市重点教改项目(201071S)。

摘　　要：煤矿井下作业监控中存在环境危险点定位误差大、监控准确度较低等问题,为此,提出基于云计算的分布式煤矿井下作业安全监控方法。分析煤矿井下作业环境安全影响因素,将其划分为物理因素、化学因素和本质因素;通过确定井下作业环境安全影响因素的热量值,完成井下作业环境安全数据的提取;以此为基础,引入云计算设计基于Hadoop的安全监控系统,通过该系统中的分布式计算功能确定井下作业环境的异常情况变化,实现井下作业的安全监控。实验结果表明:所提方法的执行时间短,且监控的异常情况数值变化较为精准,具有一定可行性。There are many problems in the monitoring of underground coal mine operation,such as large positioning error of environmental dangerous points and low monitoring accuracy.Therefore,proposes a distributed monitoring method of underground coal mine operation safety based on cloud computing.The factors affecting the safety of the underground working environment are analyzed and divided into physical factors,heat sources,chemical factors and essential factors;by determining the heat value of the factors affecting the safety of the underground working environment,the extraction of the safety data of the underground working environment is completed;on this basis,cloud computing is introduced to design a security monitoring system based on Hadoop.Through the distributed computing function in the system,the abnormal changes of the underground operation environment are determined,and the security monitoring of underground operations is realized.The experimental results show that the proposed method has a short execution time,and the monitored abnormal situation numerical changes are more accurate,which is feasible.

关 键 词：云计算 分布式煤矿 井下作业 安全监控 HADOOP 物理因素 

分 类 号：TD76[矿业工程—矿井通风与安全]