河南理工大学学报：自然科学版2012，Vol.31Issue(1)：16-18,3.
基于灰关联方法的突出预测敏感指标研究
Study on outburst prediction sensitive index based on grey relevancy analysis method
摘要
Abstract
Baiyangling Coal Mine is the coal gas outburst mine,which main minable No.15 coal seam has coal and gas outburst risk.In order to improve accuracy and validity of outburst prediction during the course of coal drift excavation,sensitivity of gas desorption index of drill-cutting（Δh2 and K1） and drilling cuttings weight（S） were studied using grey relevancy analysis method according to measured data of outburst prediction index and coalbed gas content.Research results indicate that gas desorption index of drill-cutting（K1） can reflect outburst risk level of coal body in front of working face more well and truly,so K1 is outburst prediction sensitive index in Baiyangling Coal Mine,and its critical value is 0.30 mL/（g·min0.5）.关键词
灰关联分析/突出预测/敏感指标/临界值Key words
grey relevancy analysis/outburst prediction/sensitive index/critical value分类
矿山工程引用本文复制引用
韩颖,余伟凡,杨志龙,曹文涛,张平生..基于灰关联方法的突出预测敏感指标研究[J].河南理工大学学报：自然科学版,2012,31(1):16-18,3.基金项目
河南省教育厅自然科学研究计划项目 （）
河南省教育厅自然科学研究资助项目 （）
河南省教育厅自然科学研究计划项目 （）
河南理工大学博士基金资助项目 （）
