基于主成分分析法的东荣一矿煤层自然发火指标气体实验研究
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摘要
为有效预防东荣一矿由煤自燃引起的灾害,通过煤自燃氧化实验,研究东荣一矿煤层自然发火特性,测定出实验煤样标志气体出现的临界温度并分析其体积分数随煤氧化温度的变化规律;运用主成分分析法对温度、一氧化碳体积分数φ(CO)、烯烷比φ(C_2H_4)/φ(C_2H_6)等9个指标进行综合评判分析,优选出对预测煤自燃起主导作用的指标。研究结果表明,指标气体出现的临界温度及其规律性可以反映出煤的自然发火过程。根据指标气体优选原则和主成分分析法的优选结果,建立以φ(CO)、φ(C_2H_6)、φ(C_2H_4)、φ(C_2H_2)作为主要指标,以烯烷比φ(C_2H_4)/φ(C_2H_6)作为辅助指标的东荣一矿煤层自然发火预测预报体系,提高了煤层自燃早期预测预报的准确性,实现了对矿井火灾的预防。
In order to effectively prevent the disaster caused by coal spontaneous combustion in Dongrong No. 1 Coal Mine,the spontaneous combustion characteristics of coal seams in this coal mine were studied through the experiment of coal spontaneous combustion oxidation,the critical temperature of the marked gas in the experimental coal sample was determined and the variation of its volume fraction with temperature was analyzed; the principal component analysis method was used to comprehensively evaluate the nine indexes such as temperature,φ( CO),φ( C_2 H_4)/φ( C_2 H_6),etc.,and the dominant index in predicting coal spontaneous combustion was selected. The results showed that the critical temperature of index gas and its regularity can reflect the spontaneous combustion process of coal. According to the principle of index gas optimization and the optimization results of principal component analysis,a prediction and forecast system for coal spontaneous combustion of Dongrong No.1 Coal Mine was established. φ( CO),φ( C_2 H_6),φ( C_2 H_4) and φ( C_2 H_2) were selected as the main indicators and the ratio of φ( C_2 H_4)/φ( C_2 H_6) was selected as the auxiliary indicator. The accuracy of early prediction of coal spontaneous combustion was improved, and the prevention of mine fire was realized.
In order to effectively prevent the disaster caused by coal spontaneous combustion in Dongrong No. 1 Coal Mine,the spontaneous combustion characteristics of coal seams in this coal mine were studied through the experiment of coal spontaneous combustion oxidation,the critical temperature of the marked gas in the experimental coal sample was determined and the variation of its volume fraction with temperature was analyzed; the principal component analysis method was used to comprehensively evaluate the nine indexes such as temperature,φ( CO),φ( C_2 H_4)/φ( C_2 H_6),etc.,and the dominant index in predicting coal spontaneous combustion was selected. The results showed that the critical temperature of index gas and its regularity can reflect the spontaneous combustion process of coal. According to the principle of index gas optimization and the optimization results of principal component analysis,a prediction and forecast system for coal spontaneous combustion of Dongrong No.1 Coal Mine was established. φ( CO),φ( C_2 H_6),φ( C_2 H_4) and φ( C_2 H_2) were selected as the main indicators and the ratio of φ( C_2 H_4)/φ( C_2 H_6) was selected as the auxiliary indicator. The accuracy of early prediction of coal spontaneous combustion was improved, and the prevention of mine fire was realized.
引文
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[3]周西华,陈猛,白刚,等.基于灰色关联法的褐煤燃烧阶段指标气体分析与优选[J].世界科技研究与发展,2016,38(6):1262-1265.
[4]周西华,白刚,聂荣山,等.褐煤燃烧阶段烃生成规律研究[J].中国安全科学学报,2016,26(1):58-63.
[5]周西华,宋东平,聂荣山,等.褐煤燃烧阶段碳氧化物生成规律研究[J].中国安全科学学报,2016,26(3):59-63.
[6]梁运涛.煤炭自然发火预测预报的气体指标法[J].煤炭科学技术,2008,36(6):5-8.
[7]贾廷贵,王树刚,郝宇,等.煤自燃过程烷烃析出规律及氧化特性实验[J].辽宁工程技术大学学报(自然科学版),2012,31(6):830-833.
[8]贾宝山,王汉元,金珂,等.主成分分析法在煤自燃标志性气体优选中应用[J].应用泛函分析学报,2017,19(4):452-456.
[9]邓军,周少柳,马砺,等.基于PCA-PSOSVM的煤自燃程度预测研究[J].矿业安全与环保,2016,43(5):27-31.
[10]郑忠,宋万利.基于主成分分析的中煤发热量的检测研究[J].煤炭技术,2014,33(6):218-220.
[11]陈胜可.SPSS统计分析从入门到精通[M].北京:清华大学出版社,2010.
[12]高惠璇.应用多元统计分析[M].北京:北京大学出版社,2005.
[13]中华人民共和国煤炭工业部.煤层煤样采取方法:GB 482—1995[S].北京:中国标准出版社,1995:1-5.
[14]中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.煤样的制备方法:GB 474—2008[S].北京:中国标准出版社,2008:10-14.
[15]黎锦贤,胡千庭.主成分分析法在煤矿安全评价中的应用[J].矿业安全与环保,2007(5):71-73.
[16]李峰,刘小阳,于雪涛,等.基于AHP-PCA模型的煤炭城市生态环境质量评价[J].矿业安全与环保,2017,44(5):103-106.