基于突变理论的瓦斯隧道揭煤突出危险性预测
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摘要
文章引入了突变级数瓦斯隧道揭煤突出危险性综合评价方法,基于完备性、综合性与独立性等原则选取了11个瓦斯隧道揭煤突出危险性评价指标,建立了由目标层、准则层和指标层组成的瓦斯隧道揭煤突出危险性评价多层次突变模型。在对评价指标进行标准化处理后,采用皮尔逊积矩相关系数法对评价指标的相关性进行检验。结果表明,所选指标均属于低度相关或基本无相关性。将瓦斯隧道揭煤突出危险分为无危险、轻度危险、中度危险、重度危险和极度危险5个等级,在计算了西南地区3座瓦斯隧道12层煤的突变级数基础上,评价了隧道揭露各煤层突出危险等级,并通过工程实例对评价结果进行了验证,证实了该方法评价瓦斯隧道揭煤突出危险性是合理、可行的,为瓦斯隧道揭煤突出危险性的综合评价提供了新思路。
As for the gas tunnel uncovering coal seams,a comprehensive risk evaluation method of mutation series of coal and gas outburst was introduced. 11 outburst risk assessment indicators were selected based on principles such as completeness, comprehensiveness and independence. A multi-level mutation model for coal and gas outburst risk assessment consisting of target layer,criterion layer,and indicator layer was established. The assessment indicators were standardized first,and then the Pearson's product-moment correlation coefficient method was used to test the correlation of the evaluation indicators. The results show that the selected indicators are all low-level correlation. It divides the outburst riks of gas tunnels uncovering coal seams into non-hazardous, mildly dangerous, moderately dangerous, severely dangerous and extremely dangerous grades. Based on the calculation results of the catastrophe series of 12-layer coal seams in the three gas tunnels in the southwestern region,the hazard level of coal and gas outburst of each coal seam were evaluated when the gas tunnel uncovering coal seams. It is confirmed that this method is reasonable and feasible for evaluating the outburst risk of coal and gas in gas tunnels uncovering coal seams by engineering examples.
As for the gas tunnel uncovering coal seams,a comprehensive risk evaluation method of mutation series of coal and gas outburst was introduced. 11 outburst risk assessment indicators were selected based on principles such as completeness, comprehensiveness and independence. A multi-level mutation model for coal and gas outburst risk assessment consisting of target layer,criterion layer,and indicator layer was established. The assessment indicators were standardized first,and then the Pearson's product-moment correlation coefficient method was used to test the correlation of the evaluation indicators. The results show that the selected indicators are all low-level correlation. It divides the outburst riks of gas tunnels uncovering coal seams into non-hazardous, mildly dangerous, moderately dangerous, severely dangerous and extremely dangerous grades. Based on the calculation results of the catastrophe series of 12-layer coal seams in the three gas tunnels in the southwestern region,the hazard level of coal and gas outburst of each coal seam were evaluated when the gas tunnel uncovering coal seams. It is confirmed that this method is reasonable and feasible for evaluating the outburst risk of coal and gas in gas tunnels uncovering coal seams by engineering examples.
引文
[1]国务院“十三五”现代综合交通运输体系发展规划[EB/OL]. http://www. gov. cn/zhengce/content/2017-02/28/content_5171345. htm,2017,(2):28.The State Council. Development Plan of Modem Comprehensive Transportation System in 13 th Five-Year Plan[EB/OL]. http://www. gov. cn/zhengce/content/2017-02/28/content_5171345. htm, 2017,(2):28.
[2]凌复华.突变理论及其应用[M].上海:上海交通大学出版社,1988.LING Fuhua. Mutation Theory and Its Application[M]. Shanghai:Shanghai Jiaotong University Press,1988.
[3]李春辉.基于BP神经网络的煤与瓦斯突出危险性预测的研究[D].昆明:昆明理工大学,2010.LI Chunhui. Predetermination of Coal and Gas Outburst Based on BP Neural Network[D]. Kunming:Kunming University of Science and Technology,2010.
[4]肖红飞,何学秋,刘黎明.改进BP算法在煤与瓦斯突出预测中的应用[J].中国安全科学学报,2003,13(9):59-61.XIAO Hongfei,HE Xueqiu,LIU Liming. Application of Modified BP Neural Network in Predicting Coal and Gas Outburst[J].China Safety Production Journal,2003,13(9):59-61.
[5]张子戌,袁崇孚.瓦斯地质数学模型法预测矿井瓦斯涌出量研究[J].煤炭学报,1999,(4):368-372.ZHANG Zixu,YUAN Chongfu. Gas Geological Mathematical Modeling Method for Predicting Mine Gas Emissions[J]. Journal ofChina Coal Society, 1999,(4):368-372.
[6]冯涛,尹光志.模糊数学在煤与瓦斯突出预测中的应用[J].湖南科技大学学报:自然科学版,1993,(4):13-18.FENG Tao,YIN Guangzhi. Application of Fuzzy Mathematics in Coal and Gas Outburst Prediction[J]. Journal of Hunan University of Science and Technology:Natural Science Edition, 1993,(4):13-18.
[7]赵志刚,谭云亮.基于混沌理论的煤与瓦斯突出前兆时序预测研究[J].岩土力学,2009,30(7):2186-2190.ZHAO Zhigang,TAN Yunliang. Study of Premonitory Time Series Prediction of Coal and Gas Outbursts Based on Chaos Theory[J]. Rock and Soil Mechanics,2009,30(7):2186-2190.
[8]高科,李夕兵,宫凤强.基于突变级数法的边坡地震稳定性综合评价[J].地下空间与工程学报,2009,5(2):406-412.GAO Ke, LI Xibing, GONG Fengqing. Integrative Evaluation on Seismic Stability of Slopes Based on Catastrophe Progression Method[J]. Journal of Undergournd Space and Engineering,2009,5(2):406-412.
[9]赵志峰,徐卫亚.基于突变理论的边坡安全稳定性综合评价[J].岩石力学与工程学报,2007,26(S1):2707-2712.ZHAO Zhifeng, XU Weiya. Comprehensive Evaluation of Slope Stability Based on Catastrophe Theory[J]. Journal of Rock Mechanics and Engineering,2007,26(S1):2707-2712.
[10]梁桂兰,徐卫亚,何育智,等.突变级数法在边坡稳定综合评判中的应用[J].岩土力学,2008,29(7):1895-1899.LIANG Guilan,XU Weiya,HE Yuzhi,et al. Application of Catastrophe Progression Method to Comprehensive Evaluation of Slope Stability[J]. Rock and Soil Mechanics,2008,29(7):1895-1899.
[11]周先叶,王伯荪,李鸣光,等.黑石顶自然保护区森林次生演替过程中群落主要种的种间协变分析[J].应用生态学报,2004,15(3):367-371.ZHOU Xianye,WANG Bosun, LI Mingguang, et al. Interspecies Covariation Analysis of Dominant Tree Species in Secondary Succession of Forest Communities in Heishiding Natural Reserve[J]. Journal of Applied Ecology,2004,15(3):367-371.
[2]凌复华.突变理论及其应用[M].上海:上海交通大学出版社,1988.LING Fuhua. Mutation Theory and Its Application[M]. Shanghai:Shanghai Jiaotong University Press,1988.
[3]李春辉.基于BP神经网络的煤与瓦斯突出危险性预测的研究[D].昆明:昆明理工大学,2010.LI Chunhui. Predetermination of Coal and Gas Outburst Based on BP Neural Network[D]. Kunming:Kunming University of Science and Technology,2010.
[4]肖红飞,何学秋,刘黎明.改进BP算法在煤与瓦斯突出预测中的应用[J].中国安全科学学报,2003,13(9):59-61.XIAO Hongfei,HE Xueqiu,LIU Liming. Application of Modified BP Neural Network in Predicting Coal and Gas Outburst[J].China Safety Production Journal,2003,13(9):59-61.
[5]张子戌,袁崇孚.瓦斯地质数学模型法预测矿井瓦斯涌出量研究[J].煤炭学报,1999,(4):368-372.ZHANG Zixu,YUAN Chongfu. Gas Geological Mathematical Modeling Method for Predicting Mine Gas Emissions[J]. Journal ofChina Coal Society, 1999,(4):368-372.
[6]冯涛,尹光志.模糊数学在煤与瓦斯突出预测中的应用[J].湖南科技大学学报:自然科学版,1993,(4):13-18.FENG Tao,YIN Guangzhi. Application of Fuzzy Mathematics in Coal and Gas Outburst Prediction[J]. Journal of Hunan University of Science and Technology:Natural Science Edition, 1993,(4):13-18.
[7]赵志刚,谭云亮.基于混沌理论的煤与瓦斯突出前兆时序预测研究[J].岩土力学,2009,30(7):2186-2190.ZHAO Zhigang,TAN Yunliang. Study of Premonitory Time Series Prediction of Coal and Gas Outbursts Based on Chaos Theory[J]. Rock and Soil Mechanics,2009,30(7):2186-2190.
[8]高科,李夕兵,宫凤强.基于突变级数法的边坡地震稳定性综合评价[J].地下空间与工程学报,2009,5(2):406-412.GAO Ke, LI Xibing, GONG Fengqing. Integrative Evaluation on Seismic Stability of Slopes Based on Catastrophe Progression Method[J]. Journal of Undergournd Space and Engineering,2009,5(2):406-412.
[9]赵志峰,徐卫亚.基于突变理论的边坡安全稳定性综合评价[J].岩石力学与工程学报,2007,26(S1):2707-2712.ZHAO Zhifeng, XU Weiya. Comprehensive Evaluation of Slope Stability Based on Catastrophe Theory[J]. Journal of Rock Mechanics and Engineering,2007,26(S1):2707-2712.
[10]梁桂兰,徐卫亚,何育智,等.突变级数法在边坡稳定综合评判中的应用[J].岩土力学,2008,29(7):1895-1899.LIANG Guilan,XU Weiya,HE Yuzhi,et al. Application of Catastrophe Progression Method to Comprehensive Evaluation of Slope Stability[J]. Rock and Soil Mechanics,2008,29(7):1895-1899.
[11]周先叶,王伯荪,李鸣光,等.黑石顶自然保护区森林次生演替过程中群落主要种的种间协变分析[J].应用生态学报,2004,15(3):367-371.ZHOU Xianye,WANG Bosun, LI Mingguang, et al. Interspecies Covariation Analysis of Dominant Tree Species in Secondary Succession of Forest Communities in Heishiding Natural Reserve[J]. Journal of Applied Ecology,2004,15(3):367-371.