基于BP神经网络的煤与瓦斯突出危险性预测的研究
|
摘要
煤矿安全是当前煤矿安全生产工作的首要任务,然而煤与瓦斯突出是威胁煤矿安全生产最为严重的自然灾害之一。它是一种极其复杂的动力现象,是地应力、瓦斯和煤的物理力学性质等因素综合作用的结果。鉴于目前突出灾害日益严重的现实状况,煤与瓦斯突出的预测研究对保障煤矿的安全生产显得更加重要。本文结合目前大家普遍接受的综合假说为理论基础,通过对贵州地区煤与瓦斯突出事故的统计分析,研究了煤与瓦斯突出的一般规律,并应用BP神经网络的知识对煤与瓦斯突出的危险性预测进行了研究。
1)论文首先阐述了煤与瓦斯突出危险性预测的必要性和深远意义,分析了当前的研究现状和存在问题,并以综合假说的突出机理为基础,确定了基于BP神经网络的煤与瓦斯突出危险性预测的研究方案和技术路线。
2)通过对该地区突出事故的统计分析,研究了煤与瓦斯突出的一般规律,并以综合假说为理论基础,分析了煤与瓦斯突出危险性的影响因素,建立了煤与瓦斯突出危险性的评价指标体系。
3)分析以地应力、瓦斯参数和煤体物理力学性质等控制和影响突出的各种因素,应用三角模糊数的理论和知识,确定了煤与瓦斯突出危险性预测的主控因素。
4)建立了基于BP神经网络的煤与瓦斯突出危险性预测的数学模型,并通过数学软件MATLAB将其实现,以响水矿井为例进行了区域突出危险程度的评价。该方法简单易行,具有很强的实用性和操作性。
5)最后,提出了煤与瓦斯突出的区域性防治技术,即开采保护层、预抽煤层瓦斯和煤层注水等方法。并针对我国数字化矿山的建设需要,提出了基于GIS的煤与瓦斯突出危险性预测管理系统的设计方案,为煤与瓦斯突出的防治提供了种新的防治技术,开辟煤与瓦斯突出防治的新途径,对保障煤矿企业的安全生产具有重要的意义。
本文通过对该地区突出的一般规律以及突出危险控制因素的研究,建立了基于BP神经网络煤与瓦斯突出危险性预测的数学模型,提出了煤与瓦斯突出区域性的防治技术,为煤与瓦斯突出的预测和防治探索新的途径。
The safety of coal mine is the most important task in the current coal mine safety production, however, Coal and gas outburst is one of the most serious natural disasters in coal mine safety production. It is a kind of complicated dynamical phenomena in mines, and is the synthesized result of stress, gas, coal physics mechanics etc. because of the disasters increasingly heavier, the study of coal and gas outburst prediction is even more important for safety production in coal mine. Combined with the generally accepted synthesizing hypothesis as theory basis in the paper, the paper through the statistical analysis of the coal and gas outburst accident of Gui Zhou region, to study the general rules coal and gas outburst in the region's, and the prediction of coal and gas outburst is studied by applying the knowledge of BP neural network.
1)The need and significance of coal and gas outburst risk prediction have been discussed in the paper, the actualities and limitations of current studying have been summarized, the study project and technology routes of coal and gas outburst risk prediction also have been confirmed based on BP neural network, and the outburst mechanism of synthesizing hypothesis.
2)The paper through the statistical analysis of the coal and gas outburst accident, to study the general rules coal and gas outburst in the region's, analyzing the influencing factors of coal and gas outburst based on the theory basis of synthesizing hypothesis, a hazard assessment index system of coal and gas outburst was build.
3)The paper analyzes a variety of factors controlling and effecting coal and gas outburst about the synthesized result of stress, gas, coal physics mechanics etc, the controlling factors of coal and gas outburst hazard prediction was confirmed by applying the theory and knowledge triangular fuzzy numbers.
4)The mathematical model of coal and gas outburst hazard prediction was established based on BP neural network, it was achieved by mathematical software of MATLAB, for example of Xiang Shui mine, the risk degree of the region outburst was evaluated. The method is simple、very practical and operational.
5)Finally, the regional control technology of coal and gas outburst was proposed, namely mining protective coal seam、gas pre-drainage and coal seam injecting etc. because of the need of digital mine, a design project of coal and gas outburst risk prediction management system based on GIS, a new control technology of coal and gas outburst was provided,a new access of coal and gas outburst control technology was opened, it have very important significance for safety production in mining enterprises.
The paper through the research of the general rules outburst in the region's and control factors of outburst hazard, the mathematical model of coal and gas outburst hazard prediction was established based on BP neural network, the regional control technology of coal and gas outburst was proposed, to explore new a avenue for prediction and control of coal and gas outburst.
1)论文首先阐述了煤与瓦斯突出危险性预测的必要性和深远意义,分析了当前的研究现状和存在问题,并以综合假说的突出机理为基础,确定了基于BP神经网络的煤与瓦斯突出危险性预测的研究方案和技术路线。
2)通过对该地区突出事故的统计分析,研究了煤与瓦斯突出的一般规律,并以综合假说为理论基础,分析了煤与瓦斯突出危险性的影响因素,建立了煤与瓦斯突出危险性的评价指标体系。
3)分析以地应力、瓦斯参数和煤体物理力学性质等控制和影响突出的各种因素,应用三角模糊数的理论和知识,确定了煤与瓦斯突出危险性预测的主控因素。
4)建立了基于BP神经网络的煤与瓦斯突出危险性预测的数学模型,并通过数学软件MATLAB将其实现,以响水矿井为例进行了区域突出危险程度的评价。该方法简单易行,具有很强的实用性和操作性。
5)最后,提出了煤与瓦斯突出的区域性防治技术,即开采保护层、预抽煤层瓦斯和煤层注水等方法。并针对我国数字化矿山的建设需要,提出了基于GIS的煤与瓦斯突出危险性预测管理系统的设计方案,为煤与瓦斯突出的防治提供了种新的防治技术,开辟煤与瓦斯突出防治的新途径,对保障煤矿企业的安全生产具有重要的意义。
本文通过对该地区突出的一般规律以及突出危险控制因素的研究,建立了基于BP神经网络煤与瓦斯突出危险性预测的数学模型,提出了煤与瓦斯突出区域性的防治技术,为煤与瓦斯突出的预测和防治探索新的途径。
The safety of coal mine is the most important task in the current coal mine safety production, however, Coal and gas outburst is one of the most serious natural disasters in coal mine safety production. It is a kind of complicated dynamical phenomena in mines, and is the synthesized result of stress, gas, coal physics mechanics etc. because of the disasters increasingly heavier, the study of coal and gas outburst prediction is even more important for safety production in coal mine. Combined with the generally accepted synthesizing hypothesis as theory basis in the paper, the paper through the statistical analysis of the coal and gas outburst accident of Gui Zhou region, to study the general rules coal and gas outburst in the region's, and the prediction of coal and gas outburst is studied by applying the knowledge of BP neural network.
1)The need and significance of coal and gas outburst risk prediction have been discussed in the paper, the actualities and limitations of current studying have been summarized, the study project and technology routes of coal and gas outburst risk prediction also have been confirmed based on BP neural network, and the outburst mechanism of synthesizing hypothesis.
2)The paper through the statistical analysis of the coal and gas outburst accident, to study the general rules coal and gas outburst in the region's, analyzing the influencing factors of coal and gas outburst based on the theory basis of synthesizing hypothesis, a hazard assessment index system of coal and gas outburst was build.
3)The paper analyzes a variety of factors controlling and effecting coal and gas outburst about the synthesized result of stress, gas, coal physics mechanics etc, the controlling factors of coal and gas outburst hazard prediction was confirmed by applying the theory and knowledge triangular fuzzy numbers.
4)The mathematical model of coal and gas outburst hazard prediction was established based on BP neural network, it was achieved by mathematical software of MATLAB, for example of Xiang Shui mine, the risk degree of the region outburst was evaluated. The method is simple、very practical and operational.
5)Finally, the regional control technology of coal and gas outburst was proposed, namely mining protective coal seam、gas pre-drainage and coal seam injecting etc. because of the need of digital mine, a design project of coal and gas outburst risk prediction management system based on GIS, a new control technology of coal and gas outburst was provided,a new access of coal and gas outburst control technology was opened, it have very important significance for safety production in mining enterprises.
The paper through the research of the general rules outburst in the region's and control factors of outburst hazard, the mathematical model of coal and gas outburst hazard prediction was established based on BP neural network, the regional control technology of coal and gas outburst was proposed, to explore new a avenue for prediction and control of coal and gas outburst.
引文
[1]于不凡.煤矿瓦斯灾害防治及利用技术手册(修订版)[M].北京：煤炭工业出版社,2005
[2]马丕梁.煤矿瓦斯灾害防治技术手册[M].北京：化学工业出版社,2005
[3]俞启香.矿井瓦斯防治[M].江苏：中国矿业大学出版社,1992
[4]李建铭.煤与瓦斯突出防治技术手册[M].徐州：中国矿业大学出版社,2006
[5]樊栓保.国内外煤与瓦斯突出预测新方法[J].矿业安全与环保,2000,27(5)：17-18
[6]卫修君,林柏权,张建国,翟成.煤岩瓦斯动力灾害发生机理及综合治理措施[M].北京：科学出版社,2009
[7]廖志恒.贵州某煤矿煤与瓦斯突出规律分析[J].贵州工业大学学报(自然科学版),2008,(3)：45-47
[8]煤炭工业部.防治煤与瓦斯突出细则(S).北京：煤炭工业出版社,1995
[9]李善旺.汪家寨矿井煤与瓦斯突出的地质因素及规律分析[J].矿业安全与环保,2002,(3)：35-36
[10]陈飞,江波,李仁东等.贵州青龙矿瓦斯赋存与突出影响因素分析[J].煤矿开采,2008,(4)：18-20
[11]姚宝魁,孙广忠,尹代勋.煤与瓦斯突出的区域性预测[M].北京：中国科学技术出版社,1993
[12]张子敏,张玉贵.瓦斯地质规律与瓦斯预测[M].北京：煤炭工业出版社,2005
[13]王文星.岩体力学[M].长沙：中南大学出版社,2004
[14]王志亮,李其中.浅析煤与瓦斯突出的危险性评价指标体系.西部探矿工程[J].2008,(3)：91-93
[15]肖辞源.工程模糊系统[M].北京：科学出版社,2004
[16]曾祥纪,蒋惠园.基于三角模糊数的综合评价法在互通立交方案选取中的应用[J].武汉理工大学学报(交通科学与工程版),2008,32(3)：544-545
[17]徐杨,周延,孙鑫,于明.基于模糊层次分析法的矿井安全综合评价[J].中国安全科学学报,2009,19(5)：147-149
[18]李成华,李慧民,云小红.基于模糊层次分析法的建筑安全管理绩效评价研究[J].西安建筑科技大学学报(自然科学版)2009,41(2)：208-210
[19]李春辉,陈日辉,苏恒瑜.基于三角模糊数的矿由作业人员安全生产综合素质的分析[J].工矿自动化,2010,10(8)：37-40
[20]韩力群.人工神经网络理论、设计及应用[M].北京：化学工业出版社,2007
[21]李念友.煤与瓦斯突出预测灰色理论-神经网络方法研究[D].北京：中国矿业大学,2003
[22]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[23]朱凯,王正林.精通MATLAB神经网络[M].北京：电子工业出版社,2010
[24]飞思科技产品研发中心MATLAB6.5辅助神经网络分析与设计[M].北京：电子工业出版社,2003
[25]许东,吴铮.基于MATLAB6. X的系统分析与设计—神经网络[M].西安：西安电子科技大学出版社,2002
[26]邬伦,刘瑜,张晶,马修军,韦中亚,田原.地理信息系统—原理、方法和应用[M].北京：科学出版社,2001
[27]刘海新.基于组件GIS的邯郸市公交查询系统设计[J].河北工程大学学报(自然科学版)2008,25(2)：76-77
[28]江成玉,苏恒瑜,岳宗洪.基于GIS的锚杆支护设计管理系统研究与开发[J].煤炭工程,2009,(3)：107-108
[29]李春辉,陈日辉,苏恒瑜.基于GIS的煤与瓦斯突出危险性预测管理系统的研究[J].工业安全与环保,2010,(11)：15-16
[30]赵涛.基于多因素概率预测的瓦斯突出预警方法研究[D].成都：成都理工大学,2007
[31]张瑞林.现代信息技术在煤与瓦斯突出区域预测中的应用[D].重庆：重庆大学,2004
[32]刘志云.基于神经网络的煤与瓦斯突出矿井等级划分方法研究[D].西安：西安科技大学,2003
[33]宋卫华.煤与瓦斯突出区域预测研究[D].辽宁：辽宁工程技术大学,2004
[34]杨孟达.煤矿地质学[M].北京：煤炭工业出版社,2005
[35]程伟.煤与瓦斯突出危险性预测及防治技术[M].徐州：中国矿业大学出版社,2003
[36]李春辉,陈日辉,苏恒瑜.BP神经网络在煤与瓦斯突出预测中的应用[J].矿冶,2010,19(3)：21-23
[37]熊亚选,蔡成功.基于人工神经网络的煤与瓦斯突出预测[J].煤矿安全,2004,35(9)35-37
[38]支晓伟,林柏泉,齐黎明.人工神经网络在煤与瓦斯突出预测中的应用[J].工业安全与环保,2005,31(4)：43-43
[39]江成玉,李春辉,苏恒瑜.基于GIS的煤矿火灾救援管理系统设计[J].中国矿业,2010,(4)：99-101.
[40]许树柏.实用决策方法—层次分析法原理[M].天津：天津大学出版社,1988
[41]赵换臣,许树柏.层次分析法[M].北京：科技出版社，1986
[42]Li Sheng,Zhang Hongwei coal and gas outburst model recognition and regional predicidion.Proceedings of Mining Science and Safety Technology[C],2002,331-3
[43]Xie Shengxian On interval-valued fuzzy numbers. Fuzzy set and systems,1997,73(3):83-86
[44]都锋,苏恒瑜,李春辉.基于SuperMap的煤与瓦斯突出预测管理系统的设计[J].中国矿业,2010,(4)：4-6.
[45]梁冰,章梦涛.从煤和瓦斯的耦合作用及煤的失稳破坏看突出的机理[J].中国安全科学学报,1997,(1)：45-46
[46]Wang Q,Wu J T.Research on applied model and its management in GIS[J],Acta Geodaeticaet Cartographica Sinica,1997,26(3):280-283
[47]李希建.煤巷炮掘工作面煤与瓦斯突出预警系统的研究[D].贵阳：贵州大学,2007
[48]王凯.钻孔法预测煤与瓦斯突出的研究[D].徐州：中国矿业大学,1997
[49]扬纶标,高英仪.模糊数学原理及应用[M].广州：华南理工大学出版社,2005
[50]马尚权等.煤与瓦斯突出预测预报方法[J].矿山机械,2000(5)
[51]B.Ripley. Pattern Recognition and Neural Networks. Cambridge University Press,1996
[52]Hu Zhengyu,Yu Haifeng,Gu Ping.Fuzzy Mathematics for Raw Silk Size Control[J], Journal of Donghua University,2008(4),449-452
[53]G.Shafer.A mathe matical theory of evidence[M].Princeton U.P.princeton,1976
[54]魏风清.俄罗斯煤与瓦斯突出区域预测方法的新进展[J].矿业安全与环保.2005,(5)：32-33
[55]陈学龙,段克信等.地质动力区划与矿井动力现象区域预测[J].煤矿开采..2003,(6)：55-57
[2]马丕梁.煤矿瓦斯灾害防治技术手册[M].北京：化学工业出版社,2005
[3]俞启香.矿井瓦斯防治[M].江苏：中国矿业大学出版社,1992
[4]李建铭.煤与瓦斯突出防治技术手册[M].徐州：中国矿业大学出版社,2006
[5]樊栓保.国内外煤与瓦斯突出预测新方法[J].矿业安全与环保,2000,27(5)：17-18
[6]卫修君,林柏权,张建国,翟成.煤岩瓦斯动力灾害发生机理及综合治理措施[M].北京：科学出版社,2009
[7]廖志恒.贵州某煤矿煤与瓦斯突出规律分析[J].贵州工业大学学报(自然科学版),2008,(3)：45-47
[8]煤炭工业部.防治煤与瓦斯突出细则(S).北京：煤炭工业出版社,1995
[9]李善旺.汪家寨矿井煤与瓦斯突出的地质因素及规律分析[J].矿业安全与环保,2002,(3)：35-36
[10]陈飞,江波,李仁东等.贵州青龙矿瓦斯赋存与突出影响因素分析[J].煤矿开采,2008,(4)：18-20
[11]姚宝魁,孙广忠,尹代勋.煤与瓦斯突出的区域性预测[M].北京：中国科学技术出版社,1993
[12]张子敏,张玉贵.瓦斯地质规律与瓦斯预测[M].北京：煤炭工业出版社,2005
[13]王文星.岩体力学[M].长沙：中南大学出版社,2004
[14]王志亮,李其中.浅析煤与瓦斯突出的危险性评价指标体系.西部探矿工程[J].2008,(3)：91-93
[15]肖辞源.工程模糊系统[M].北京：科学出版社,2004
[16]曾祥纪,蒋惠园.基于三角模糊数的综合评价法在互通立交方案选取中的应用[J].武汉理工大学学报(交通科学与工程版),2008,32(3)：544-545
[17]徐杨,周延,孙鑫,于明.基于模糊层次分析法的矿井安全综合评价[J].中国安全科学学报,2009,19(5)：147-149
[18]李成华,李慧民,云小红.基于模糊层次分析法的建筑安全管理绩效评价研究[J].西安建筑科技大学学报(自然科学版)2009,41(2)：208-210
[19]李春辉,陈日辉,苏恒瑜.基于三角模糊数的矿由作业人员安全生产综合素质的分析[J].工矿自动化,2010,10(8)：37-40
[20]韩力群.人工神经网络理论、设计及应用[M].北京：化学工业出版社,2007
[21]李念友.煤与瓦斯突出预测灰色理论-神经网络方法研究[D].北京：中国矿业大学,2003
[22]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[23]朱凯,王正林.精通MATLAB神经网络[M].北京：电子工业出版社,2010
[24]飞思科技产品研发中心MATLAB6.5辅助神经网络分析与设计[M].北京：电子工业出版社,2003
[25]许东,吴铮.基于MATLAB6. X的系统分析与设计—神经网络[M].西安：西安电子科技大学出版社,2002
[26]邬伦,刘瑜,张晶,马修军,韦中亚,田原.地理信息系统—原理、方法和应用[M].北京：科学出版社,2001
[27]刘海新.基于组件GIS的邯郸市公交查询系统设计[J].河北工程大学学报(自然科学版)2008,25(2)：76-77
[28]江成玉,苏恒瑜,岳宗洪.基于GIS的锚杆支护设计管理系统研究与开发[J].煤炭工程,2009,(3)：107-108
[29]李春辉,陈日辉,苏恒瑜.基于GIS的煤与瓦斯突出危险性预测管理系统的研究[J].工业安全与环保,2010,(11)：15-16
[30]赵涛.基于多因素概率预测的瓦斯突出预警方法研究[D].成都：成都理工大学,2007
[31]张瑞林.现代信息技术在煤与瓦斯突出区域预测中的应用[D].重庆：重庆大学,2004
[32]刘志云.基于神经网络的煤与瓦斯突出矿井等级划分方法研究[D].西安：西安科技大学,2003
[33]宋卫华.煤与瓦斯突出区域预测研究[D].辽宁：辽宁工程技术大学,2004
[34]杨孟达.煤矿地质学[M].北京：煤炭工业出版社,2005
[35]程伟.煤与瓦斯突出危险性预测及防治技术[M].徐州：中国矿业大学出版社,2003
[36]李春辉,陈日辉,苏恒瑜.BP神经网络在煤与瓦斯突出预测中的应用[J].矿冶,2010,19(3)：21-23
[37]熊亚选,蔡成功.基于人工神经网络的煤与瓦斯突出预测[J].煤矿安全,2004,35(9)35-37
[38]支晓伟,林柏泉,齐黎明.人工神经网络在煤与瓦斯突出预测中的应用[J].工业安全与环保,2005,31(4)：43-43
[39]江成玉,李春辉,苏恒瑜.基于GIS的煤矿火灾救援管理系统设计[J].中国矿业,2010,(4)：99-101.
[40]许树柏.实用决策方法—层次分析法原理[M].天津：天津大学出版社,1988
[41]赵换臣,许树柏.层次分析法[M].北京：科技出版社，1986
[42]Li Sheng,Zhang Hongwei coal and gas outburst model recognition and regional predicidion.Proceedings of Mining Science and Safety Technology[C],2002,331-3
[43]Xie Shengxian On interval-valued fuzzy numbers. Fuzzy set and systems,1997,73(3):83-86
[44]都锋,苏恒瑜,李春辉.基于SuperMap的煤与瓦斯突出预测管理系统的设计[J].中国矿业,2010,(4)：4-6.
[45]梁冰,章梦涛.从煤和瓦斯的耦合作用及煤的失稳破坏看突出的机理[J].中国安全科学学报,1997,(1)：45-46
[46]Wang Q,Wu J T.Research on applied model and its management in GIS[J],Acta Geodaeticaet Cartographica Sinica,1997,26(3):280-283
[47]李希建.煤巷炮掘工作面煤与瓦斯突出预警系统的研究[D].贵阳：贵州大学,2007
[48]王凯.钻孔法预测煤与瓦斯突出的研究[D].徐州：中国矿业大学,1997
[49]扬纶标,高英仪.模糊数学原理及应用[M].广州：华南理工大学出版社,2005
[50]马尚权等.煤与瓦斯突出预测预报方法[J].矿山机械,2000(5)
[51]B.Ripley. Pattern Recognition and Neural Networks. Cambridge University Press,1996
[52]Hu Zhengyu,Yu Haifeng,Gu Ping.Fuzzy Mathematics for Raw Silk Size Control[J], Journal of Donghua University,2008(4),449-452
[53]G.Shafer.A mathe matical theory of evidence[M].Princeton U.P.princeton,1976
[54]魏风清.俄罗斯煤与瓦斯突出区域预测方法的新进展[J].矿业安全与环保.2005,(5)：32-33
[55]陈学龙,段克信等.地质动力区划与矿井动力现象区域预测[J].煤矿开采..2003,(6)：55-57