基于FA-Logistic的煤矿瓦斯突出事故安全预警研究  

Study on Safety Early Warning of Coal Mine Gas Outburst Accident Based on Factor Analysis and Logistic Regression

作　　者：兰国辉[1] 余保华[1] 陈亚树[1] 李恕洲 LAN Guohui Yu Baohua CHEN Yashu LI Shuzhou(School of Economics and Management, Anhui University of Science ＆ Technology Huainan,Anhui 232001)

机构地区：[1]安徽理工大学经济与管理学院,安徽淮南232001

出　　处：《工业安全与环保》2017年第10期51-54,共4页Industrial Safety and Environmental Protection

基　　金：安徽省人文社科重点基地研究基金(SK2016A0279;SK2015A081)

摘　　要：我国煤矿瓦斯突出事故时有发生,造成的损失巨大。基于此,对新常态下的瓦斯突出事故进行预警具有重要意义。通过研究近年来瓦斯突出事故发生状况,选取煤层瓦斯含量、埋藏深度、厚度等十个关键影响因素作为评价指标体系,以获取的18组数据作为研究样本,借助SPSS软件,运用因子分析——Logistic回归方法进行综合预警,另外18组数据作为检验样本,结果都表明该方法有很好的预警效果,总体预警准确率达到80%以上。因此,该综合预警方法可以较早预测煤矿瓦斯突出事故的发生。China＇s coal mine gas outburst accidents happen time and again, resulting in huge losses and based on this, the gas outburst accident early warning under new normal is of great significance. Through the study of gas outburst accident condition in recent years, it is selected ten key factors, such as coal seam gas content, buried depth, thickness and so on, as evaluation index system, to get 18 sets of data acquisition as the research sample, with the help of SPSS software, the comprehensive warning is conducted by using the factor analysis and Logistic regression methods and the other 18 sets of data is applied as the test sample. The result indicates that the method has a good warning effect and the overall warning accuracy rate reaches above 80%. Therefore, this comprehensive early warning method can early predict the occurrence of coal mine gas outburst accident.

关 键 词：煤矿 瓦斯突出 因子分析 LOGISTIC回归 预警 

分 类 号：TD713[矿业工程—矿井通风与安全]