基于模糊聚类方法的复杂煤层煤与瓦斯突出危险性分析
Coal and Gas Outburst Hazard Analysis of Complex Coal Seam Based on Fuzzy Clustering Method
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摘要: 为研究复杂条件下煤层煤与瓦斯突出危险性的预测方法,以通顺煤矿2#煤层为例,对其区域性突出危险性预测敏感指标进行筛选,通过井下直接测定法和实验室对比分析得出瓦斯含量值作为主要判定指标(敏感指标),临界值为8 m3/t,瓦斯压力作为辅助判定指标,参考临界值定为0.60 MPa。并通过模糊聚类方法分析得出通顺煤矿2#煤层同一工作面△h2的相对敏感度最大,K1次之,S最小,所以选取△h2作为通顺2#煤层煤与瓦斯突出危险性预测的敏感指标,K1和S作为辅助性的参考指标。运用统计学理论和概率分布确定出通顺2#煤层煤与瓦斯突出危险性预测敏感指标为△h2,临界值定为180 Pa(湿煤临界值为160 Pa);K1值作为局部预测的辅助指标,参考临界值为0.41 mL/(g·min1/2)(干煤);S反映煤层应力大小,亦作为辅助指标,参考临界值为5.10 kg/m(干煤)。Abstract: In order to study the forecast method of coal and gas outburst under complex conditions, taking 2# coal seam of Tongshun Coal Mine as an example, regional sensitive indexes of dangerous forecast for coal and gas outburst are selected, this analysis, through direct downhole measurement and comparison tests at laboratory, concludes that gas content is the main index for forecast and critical value is 8 m3/t; gas pressure is a secondary index and the critical value is 0.60 MPa. It is found that △h2 has the largest relative sensitivity, K1 comes second, the least relative sensitivity is S in the same working face of Tongshun 2# coal seam by fuzzy classification analysis method. So, △h2 is selected as the sensitivity index in coal and gas outburst of Tongshun 2# coal seam, K1 and S as the auxiliary sensitivity indexes. It is determined that △h2 is the sensitive index for predicting coal and gas outburst hazard by statistical learning theory and probabilistic distribution, and the critical value is 180 Pa (160 Pa for wet coal); K1 as the auxiliary sensitivity index for local prediction, critical value is 0.41 mL/(g·min1/2) (dry coal), S can reflects the stress of coal seam as the auxiliary sensitivity indexe for local prediction, critical values is 5.10 kg/m (dry coal).
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Keywords:
- coal and gas outburst /
- complex coal seam /
- fuzzy clustering /
- forecast /
- critical value
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[1] 任培良,李国旗.义安矿突出预测指标统计及影响因素分析[J].矿业安全与环保,2011,38(5):80-86. [2] 胡千庭,邹银辉,文光才,等.瓦斯含量法预测突出危险新技术[J].煤炭学报,2007,32(3):276-280. [3] 赵旭生,董银生,岳超平.煤与瓦斯突出预测敏感指标及其临界值的确定方法[J].矿业安全与环保,2007,34(3):28-30. [4] 张庆华,文光才,邹云龙,等.瓦斯涌出预警指标及其临界值优选方法[J].矿业安全与环保,2014,41(1):23-27. [5] 邱贤德,姜永东,舒生云,等.芙蓉煤矿煤与瓦斯突出指标临界值分析[J].煤炭科学技术,2004,32(1):59. [6] 舒龙勇,孙赫.邯郸通顺矿业有限公司2号煤层突出预测敏感指标考察及临界值确定研究报告[R].北京:煤炭科学研究总院安全分院,2014. [7] 王路军.突出预测指标钻屑量的实验研究[J].煤矿安全,2008,39(9):1-3. [8] 仇海生.工作面防突措施效果检验指标的敏感性分析[J].煤矿安全,2012,43(1):83-85. [9] 胡千庭,文光才,徐三民.工作面突出预测敏感指标及临界值确定方法的研究[J].矿业安全与环保,1998(S1):8-10. [10] 翟清伟,程远平,王亮,等.祁南煤矿72#煤层钻屑瓦斯解吸指标敏感性分析[J].中国煤炭,2012,38(1):88-91. [11] 高旭,张浪,汪东,等.屯兰矿钻屑解吸指标敏感性研究[J].煤炭科学技术,2014,42(10):41-44. [12] 申宏敏,毛桃良,张雷林,等.基于钻屑理论的抽采钻孔合理封孔深度研究[J].煤矿安全,2014,45(8):39-45. [13] 董杰,李希建,刘钊.突出预测指标钻屑量影响因素研究[J].洁净煤技术,2012,18(1):95-97.
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