基于人工神经网络的巷道围岩分类与支护参数优化研究
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摘要
随着煤矿开采深度的增加,采掘工作将在高地应力、围岩条件很差的环境中进行,导致巷道被整体压垮、底板膨胀鼓起、拱顶下沉、两帮收敛、鞍形大变形破坏等,这对巷道支护技术提出了更高的要求。课题以皖北煤电集团钱营孜煤矿岩石巷道为背景,开展矿井岩石巷道围岩分类与支护方案优化技术研究,具有重要的现实意义。
影响煤矿巷道围岩稳定性分类的因素很多,主要有自然因素与开采技术因素。作者结合两淮地区煤系地层特点,选取BQ分类方法作为围岩分类样本空间依据。论文基于BP神经网络原理,利用MATLAB神经网络工具箱函数,在收集了大量淮南、皖北矿区的工程地质条件、巷道围岩情况以及相应的支护参数的基础上,编制深井巷道围岩分类与支护优化设计系统软件。
深井巷道围岩分类与支护优化设计系统软件主要包括两方面功能,其一,实现煤矿巷道围岩稳定性分类;其二,实现煤矿巷道支护参数优化设计。在钱营孜煤矿西翼回风与3212巷道应用此软件的设计结果,经过现场锚杆受力、深部位移及松动圈监测,表明此软件的设计结果合理。该软件的成功应用,可明显缩短支护设计时间,降低巷道失稳率与返修率,且软件界面人性化,易于操作,所需输入的资料,大部分为下拉式选择方式,易于有针对性的收集,具有一定的应用价值。
The job will work at highland stress and very poor rock conditions environment with the increase of mining depth, which may lead to the whole tunnel crush, floor heave, dome subsidence, two sidewalls convergence, large deformation damage like saddle-shaped and so on, all of these require new technique in tunnel supporting. This thesis takes the roadway supporting of QianYingzi coal mine in WanBei coal group as the engineering background, the study of rock classification of deep well and optimized design of supporting were carried out, it have important Practical significance.
Many factors influence the stability of surrounding rock classification, mainly include natural and exploitation technical these two factors. Considered the characteristics of coal measure strata. The author select BQ classification as a basis for the samples of classification of surrounding rock. The software system of rock classification of deep well and optimized design of supporting was developped, which based on BP neural network and used MATLAB neural network toolbox function, The basis of collecting much engineering geological information HuaiNan, HuaiBei mining area, as well as the corresponding support parameters.
The software system mainly consists of two functions. First, it can achieve classification of stability of surrounding rock; Second, it can implmentation realize optimization and decision-making of supporting parameter in mine roadway. At the XiYi return aircourse and the 3212 tunnel of QianYingzi coal mine, the outcome of the decision-making of application of the software design, after the scene by the bolt force, and deep displacement and broken zone monitoring, it shows that this software is reasonable to decision-making. The software in the successful application of the QianYingzi coal mine, can obviously shorten the design supporting time, reduce the percentage of products sent back for repair and destabilization, The software is humanized, easy to operate, and the required information, most of the information were inputed by the drop-down selection; we can see that the software have some application value.
影响煤矿巷道围岩稳定性分类的因素很多,主要有自然因素与开采技术因素。作者结合两淮地区煤系地层特点,选取BQ分类方法作为围岩分类样本空间依据。论文基于BP神经网络原理,利用MATLAB神经网络工具箱函数,在收集了大量淮南、皖北矿区的工程地质条件、巷道围岩情况以及相应的支护参数的基础上,编制深井巷道围岩分类与支护优化设计系统软件。
深井巷道围岩分类与支护优化设计系统软件主要包括两方面功能,其一,实现煤矿巷道围岩稳定性分类;其二,实现煤矿巷道支护参数优化设计。在钱营孜煤矿西翼回风与3212巷道应用此软件的设计结果,经过现场锚杆受力、深部位移及松动圈监测,表明此软件的设计结果合理。该软件的成功应用,可明显缩短支护设计时间,降低巷道失稳率与返修率,且软件界面人性化,易于操作,所需输入的资料,大部分为下拉式选择方式,易于有针对性的收集,具有一定的应用价值。
The job will work at highland stress and very poor rock conditions environment with the increase of mining depth, which may lead to the whole tunnel crush, floor heave, dome subsidence, two sidewalls convergence, large deformation damage like saddle-shaped and so on, all of these require new technique in tunnel supporting. This thesis takes the roadway supporting of QianYingzi coal mine in WanBei coal group as the engineering background, the study of rock classification of deep well and optimized design of supporting were carried out, it have important Practical significance.
Many factors influence the stability of surrounding rock classification, mainly include natural and exploitation technical these two factors. Considered the characteristics of coal measure strata. The author select BQ classification as a basis for the samples of classification of surrounding rock. The software system of rock classification of deep well and optimized design of supporting was developped, which based on BP neural network and used MATLAB neural network toolbox function, The basis of collecting much engineering geological information HuaiNan, HuaiBei mining area, as well as the corresponding support parameters.
The software system mainly consists of two functions. First, it can achieve classification of stability of surrounding rock; Second, it can implmentation realize optimization and decision-making of supporting parameter in mine roadway. At the XiYi return aircourse and the 3212 tunnel of QianYingzi coal mine, the outcome of the decision-making of application of the software design, after the scene by the bolt force, and deep displacement and broken zone monitoring, it shows that this software is reasonable to decision-making. The software in the successful application of the QianYingzi coal mine, can obviously shorten the design supporting time, reduce the percentage of products sent back for repair and destabilization, The software is humanized, easy to operate, and the required information, most of the information were inputed by the drop-down selection; we can see that the software have some application value.
引文
[1]曾凡宇.组建大型煤炭企业集团.促进煤炭工业可持续健康发展.煤炭工程,2007.1
[2]张立明.人工神经网络的模型及应用[M] .上海:复旦大学出版社,1993
[3]张吉礼.模糊:神经网络控制原理与工程应用.哈尔滨工业大学出版社,2004.6
[4]陈继光.MATLAB与自适应神经网络模糊推理系统.山东省地图出版社,2002.3
[5]王果.回采巷道围岩稳定性分类及锚杆支护设计决策系统研制与应用.太原理工大学,2006.5
[6]王广德,复杂条件下围岩分类研究.成都理工大学,2006.4
[7]林韵梅等著.岩石分级的理论与实践.北京:冶金工业出版社,1996
[8]吴德伦,黄质红,赵明阶.岩石力学.重庆大学出版社,2001
[9]蔡美峰,何满潮,刘东燕.岩石力学与工程.科学出版社,2002.8
[10]杨双锁,钱鸣高,康立勋.巷道围岩控制的波动性平衡理论[J] .太原理工大学学报,2001:32(4):339-343.)
[11]冯夏庭,贾民泰.岩石力学问题的神经网络建模.岩石力学与工程学报,2000,19(增):10301033
[12]许明,张永兴,阴可.锚杆极限承载力的人工神经网络预测.岩石力学与工程学报2002,5(21)
[13]刘明贵,岳向红.基于小波神经网络的锚杆锚固质量分析.岩石力学与工程学报2006(1)25
[14]于学馥等,地下工程围岩稳定分析.北京:煤炭工业出版社,1983
[15]岳翰,贾悦谦,严志才.井巷锚杆及锚喷支护技术.山西人民出版社,1984.4
[16]马世志,张茂林等.巷道围岩稳定性分类方法评述.建井技术,2004.10第五期
[17]段振西.锚杆支护技术的新发展[A].岩土锚固新技术[C].人民交通出版社,1998
[18]陈继光,MATLAB与自适应神经网络模糊推理系统,山东省地图出版社,2002.3
[19]陈荣.一种新型的岩石加固锚杆——砂固结内锚头预应力锚杆的试验及理论研究[D].中国科学院武汉岩土力学研究所,1998
[20]常魏,谢光军,黄朝辉编著.北京:MATLAB R2007基础与提高电子工业出版社.2007
[21] MATLAB6.5辅助神经网络分析与设计.飞思科技研发中心编著,北京:电子工业出版社,2003.1
[22]姚树江,孟凡海,张福.钢纤维混凝土在矿山井巷支护中的应用.有色金属(矿山部分),2000,(1)
[23]《采矿设计手册——井巷工程卷》,北京:中国建筑工业出版社,1989
[24]丛爽.面向MATLAB工具箱的神经网络理论与应用.合肥:中国科技大学出版社,1998
[25]工程岩体分级标准GB50218-94.北京:中国计划出版社
[26] Y.Yang, Q.Zhang, The Application of Neural Network to Rock Engineering Systems(RMRS), Int. J. Rock Mech. Min. Sci. 1998, 35(6)
[27]刘小兵,韩玉华.喷锚支护参数的优化确定.岩石力学与工程学报,1994,13(1)
[28]蔡美峰,孔广亚,贾立宏.岩体工程系统失稳的能量突变判断准则及其应用.北京科技大学学报,1997,19(4):325~328
[29]胡守仁,余少波,戴葵.神经网络导论.长沙:国防科技大学出版社,1993
[30]李世辉等著.隧道支护设计新论——典型类比分析法应用和理论.北京:科学出版社,1999.2
[31] Werbos PJ. 1974. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences, Harvard University
[32]李彦斌,苏学贵.影响锚喷支护质量的因素分析.山西煤炭,2000
[33]朱琢华,黄宏伟.锚喷支护设计的工程类比模糊经验法.煤炭学报,1998,No.23(6)
[34]金掌臻.锚喷支护及其应用.矿业研究与开发, 1999,No.19(增刊)
[35]莫恭佑.神经网络及其在英国的应用.国际科技交流,1992(3)
[36]袁曾忍.人工神经元网络及其应用.北京:清华大学出版社,1999
[37]曹庆林.用神经网络方法预测围岩类别.冶金矿山设计与建设,1994.22
[38]冯夏庭.巷道支护优化设计的智能系统研究.博士学位论文.东北工学院,1991.07
[39]元邵英.国外锚杆的新发展.化工矿山技术,1995. Vol.24.258-89
[40]杨朝晖,刘浩吾.地下工程围岩稳定性分类的人工神经网络模型.四川联合大学学报,1999,Vol 3. No.4. 66-72
[41]邹喜正.煤矿巷道围岩稳定性分类.徐州:中国矿业大学出版社,1995.04
[42]谭学术,鲜学福.复合岩体力学与应用.北京:煤炭工业出版社,1994.6
[43]龚维明,童小东等.地下结构与工程.南京:东南大学出版社.2004.2.
[44]袁和生等.煤矿巷道锚杆支护技术.煤炭工业出版社,1997
[45]刘永阔.新型锚杆及岩土锚固新技术.西部探矿技术2006年第6期
[46] Evert Hoke, Reliablity of Hoke-Brown Estimates of Rock Mass Properties and Their Impact on Design, Int. J. Rock Mech. And Min.Sci. 1998,35(1)
[47] T F Herbst, removable ground anchors-answer for urban excava-tions[A] In: proc. Ground Anchorage and Anchorages and Anchored Structures[C]. London: Thomas Telford. 1997
[48]周彦清.可拆芯式锚索的拆除[A].岩土锚固新技术[C].人民交通出版社,1998
[49]程良奎.深基坑支护的新进展[A].见中国岩土锚杆工程协会编.岩土锚固新技术[C].人民交通出版社,1998
[2]张立明.人工神经网络的模型及应用[M] .上海:复旦大学出版社,1993
[3]张吉礼.模糊:神经网络控制原理与工程应用.哈尔滨工业大学出版社,2004.6
[4]陈继光.MATLAB与自适应神经网络模糊推理系统.山东省地图出版社,2002.3
[5]王果.回采巷道围岩稳定性分类及锚杆支护设计决策系统研制与应用.太原理工大学,2006.5
[6]王广德,复杂条件下围岩分类研究.成都理工大学,2006.4
[7]林韵梅等著.岩石分级的理论与实践.北京:冶金工业出版社,1996
[8]吴德伦,黄质红,赵明阶.岩石力学.重庆大学出版社,2001
[9]蔡美峰,何满潮,刘东燕.岩石力学与工程.科学出版社,2002.8
[10]杨双锁,钱鸣高,康立勋.巷道围岩控制的波动性平衡理论[J] .太原理工大学学报,2001:32(4):339-343.)
[11]冯夏庭,贾民泰.岩石力学问题的神经网络建模.岩石力学与工程学报,2000,19(增):10301033
[12]许明,张永兴,阴可.锚杆极限承载力的人工神经网络预测.岩石力学与工程学报2002,5(21)
[13]刘明贵,岳向红.基于小波神经网络的锚杆锚固质量分析.岩石力学与工程学报2006(1)25
[14]于学馥等,地下工程围岩稳定分析.北京:煤炭工业出版社,1983
[15]岳翰,贾悦谦,严志才.井巷锚杆及锚喷支护技术.山西人民出版社,1984.4
[16]马世志,张茂林等.巷道围岩稳定性分类方法评述.建井技术,2004.10第五期
[17]段振西.锚杆支护技术的新发展[A].岩土锚固新技术[C].人民交通出版社,1998
[18]陈继光,MATLAB与自适应神经网络模糊推理系统,山东省地图出版社,2002.3
[19]陈荣.一种新型的岩石加固锚杆——砂固结内锚头预应力锚杆的试验及理论研究[D].中国科学院武汉岩土力学研究所,1998
[20]常魏,谢光军,黄朝辉编著.北京:MATLAB R2007基础与提高电子工业出版社.2007
[21] MATLAB6.5辅助神经网络分析与设计.飞思科技研发中心编著,北京:电子工业出版社,2003.1
[22]姚树江,孟凡海,张福.钢纤维混凝土在矿山井巷支护中的应用.有色金属(矿山部分),2000,(1)
[23]《采矿设计手册——井巷工程卷》,北京:中国建筑工业出版社,1989
[24]丛爽.面向MATLAB工具箱的神经网络理论与应用.合肥:中国科技大学出版社,1998
[25]工程岩体分级标准GB50218-94.北京:中国计划出版社
[26] Y.Yang, Q.Zhang, The Application of Neural Network to Rock Engineering Systems(RMRS), Int. J. Rock Mech. Min. Sci. 1998, 35(6)
[27]刘小兵,韩玉华.喷锚支护参数的优化确定.岩石力学与工程学报,1994,13(1)
[28]蔡美峰,孔广亚,贾立宏.岩体工程系统失稳的能量突变判断准则及其应用.北京科技大学学报,1997,19(4):325~328
[29]胡守仁,余少波,戴葵.神经网络导论.长沙:国防科技大学出版社,1993
[30]李世辉等著.隧道支护设计新论——典型类比分析法应用和理论.北京:科学出版社,1999.2
[31] Werbos PJ. 1974. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences, Harvard University
[32]李彦斌,苏学贵.影响锚喷支护质量的因素分析.山西煤炭,2000
[33]朱琢华,黄宏伟.锚喷支护设计的工程类比模糊经验法.煤炭学报,1998,No.23(6)
[34]金掌臻.锚喷支护及其应用.矿业研究与开发, 1999,No.19(增刊)
[35]莫恭佑.神经网络及其在英国的应用.国际科技交流,1992(3)
[36]袁曾忍.人工神经元网络及其应用.北京:清华大学出版社,1999
[37]曹庆林.用神经网络方法预测围岩类别.冶金矿山设计与建设,1994.22
[38]冯夏庭.巷道支护优化设计的智能系统研究.博士学位论文.东北工学院,1991.07
[39]元邵英.国外锚杆的新发展.化工矿山技术,1995. Vol.24.258-89
[40]杨朝晖,刘浩吾.地下工程围岩稳定性分类的人工神经网络模型.四川联合大学学报,1999,Vol 3. No.4. 66-72
[41]邹喜正.煤矿巷道围岩稳定性分类.徐州:中国矿业大学出版社,1995.04
[42]谭学术,鲜学福.复合岩体力学与应用.北京:煤炭工业出版社,1994.6
[43]龚维明,童小东等.地下结构与工程.南京:东南大学出版社.2004.2.
[44]袁和生等.煤矿巷道锚杆支护技术.煤炭工业出版社,1997
[45]刘永阔.新型锚杆及岩土锚固新技术.西部探矿技术2006年第6期
[46] Evert Hoke, Reliablity of Hoke-Brown Estimates of Rock Mass Properties and Their Impact on Design, Int. J. Rock Mech. And Min.Sci. 1998,35(1)
[47] T F Herbst, removable ground anchors-answer for urban excava-tions[A] In: proc. Ground Anchorage and Anchorages and Anchored Structures[C]. London: Thomas Telford. 1997
[48]周彦清.可拆芯式锚索的拆除[A].岩土锚固新技术[C].人民交通出版社,1998
[49]程良奎.深基坑支护的新进展[A].见中国岩土锚杆工程协会编.岩土锚固新技术[C].人民交通出版社,1998