基于PSO-SVM算法联合数值模拟的红岭铅锌矿地表移动带圈定
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摘要
为了更加准确圈定红岭铅锌矿地表移动带,依据PSO-SVM算法与数值模拟联合确定红岭铅锌矿各矿体移动角。统计国内外30个崩落法矿山的地质特征数据,选取矿体上下盘围岩性质、上下盘围岩稳固程度、矿体倾角、矿体厚度以及开采深度共5种因素作为模型的输入参数,矿体上下盘移动角作为输出参数,基于PSO优化算法建立崩落法矿山移动角预测模型。采用前处理软件HyperMesh对矿区进行高精度建模,并导入有限差分法软件FLAC~(3D)之中,利用数值模拟分析了地表移动变形。结果表明,利用PSO-SVM算法与数值模拟得出的移动角基本吻合,相互验证。最终确定红岭铅锌矿1~#、1-1~#、2~#矿体的上下盘移动角,由此得出红岭铅锌矿地表移动带范围。为圈定金属矿山地表移动带提供了一种可靠的方法。
In order to obtain more accurate delineation of surface displacement belt for Hongling lead-zinc mine,the motion angles were calculated by the PSO-SVM algorithm combined with the results of numerical simulation.The geological characteristic data of 30caving mines in china and abroad were counted,and a total of five factors were selected as the input parameters of the model including the surrounding rock properties of the ore body,the stability of the surrounding rock,the dip angle of the ore body,the thickness of the ore body and the mining depth.The motion angel of the upper and lower terranes were selected as the output parameter,and the mining displacement angle prediction model of the caving mine is established based on the PSO optimization algorithm.The pre-processing software HyperMesh was used to model the mining area with high precision and imported to a commercial code(FLAC~(3D)).The surface displacement deformation was analyzed by numerical simulation.The results show that the PSO-SVM algorithm is basically consistent with the displacement angle obtained by numerical simulation and mutual verification.Finally,the displacement angle of the upper and lower terranes of the ore bodies(1~#,1-1~#,2~#)of Hongling Lead-Zinc mine were determined,and the range of surface displacement was obtained.It provides a reliable method for delineating metal mine surface displacement belt in underground metal mines.
In order to obtain more accurate delineation of surface displacement belt for Hongling lead-zinc mine,the motion angles were calculated by the PSO-SVM algorithm combined with the results of numerical simulation.The geological characteristic data of 30caving mines in china and abroad were counted,and a total of five factors were selected as the input parameters of the model including the surrounding rock properties of the ore body,the stability of the surrounding rock,the dip angle of the ore body,the thickness of the ore body and the mining depth.The motion angel of the upper and lower terranes were selected as the output parameter,and the mining displacement angle prediction model of the caving mine is established based on the PSO optimization algorithm.The pre-processing software HyperMesh was used to model the mining area with high precision and imported to a commercial code(FLAC~(3D)).The surface displacement deformation was analyzed by numerical simulation.The results show that the PSO-SVM algorithm is basically consistent with the displacement angle obtained by numerical simulation and mutual verification.Finally,the displacement angle of the upper and lower terranes of the ore bodies(1~#,1-1~#,2~#)of Hongling Lead-Zinc mine were determined,and the range of surface displacement was obtained.It provides a reliable method for delineating metal mine surface displacement belt in underground metal mines.
引文
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[15]高栗,李夕兵,张楚璇.地下金属矿山岩层移动角选取的进化支持向量机模型及工程应用[J].采矿与安全工程学报,2014,31(5):795-802.GAO Li,LI Xibing,ZHANG Chuxuan.Nonlinear SVM with GA in determination of the motion angle of terrane in underground metal mine and its application in engineering[J].Journal of Mining and Safety Engineering,2014,31(5):795-802.
[16]张学工.关于统计学习理论与支持向量机[J].自动化学报,2000,26(1):32-42.ZHANG Xuegong.Statistical learning theory and support vector machines[J].Acta Automatica Sinica,2000,26(1):32-41.
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[18]杨维,李歧强.粒子群优化算法综述[J].中国工程科学,2004,6(5):87-94.YANG Wei,LI Qiqiang.An overview:particle swarm optimization[J].Engineering Science,2004,6(5):87-94.
[19]Gu D S,Deng J,Li X B,et al.Three dimensional numerical simulation of excavation and backfilling in mining engineering[J].Transactions of Nonferrous Metals Society of China,1999,9(2):213-217.
[20]郭文兵,邓喀中,邹友峰.岩层移动角选取的神经网络方法研究[J].中国安全科学学报,2003,13(9):69.GUO Wenbing,DENG Kazhong,ZOU Youfeng.Study on artificial neural network method for calculation of displacement angle of strata[J].China Safety Science Journal,2003,13(9):69.
[21]李铀,白世伟,杨春和,等.矿山覆岩移动特征与安全开采深度[J].岩土力学,2005(1)27-32.LI You,BAI Shiwei,YANG Chunhe,et al.Characters of overburden strata movement of mines and safe mining depth[J].Rock and Soil Mechanics,2005(1):27-32.
[22]王艳辉,宋卫东,蔡嗣经.地下金属矿山崩落采矿法岩层移动规律分析[J].金属矿山,2002(3):13-16.WANG Yanhui,SONG Weidong,CAI Sijing.Analysis of the rock stratum displacement law in caving mining of underground metal mines[J].Metal Mine,2002(3):13-16.
[23]北京有色冶金设计研究总院.采矿设计手册矿床开采卷[M].北京:冶金工业出版社,1987.General research institute for nonferrous metals.Mining design manual, volume of mining[M].Bejing:Metallurgical Industry Press,1987.
[24]Chang C C,Lin C J.LIBSVM:A library for support vector machines[J].Acm Transactions on Intelligent Systems&Technology,2011,2(3):1-27.
[2]Carnec C,Delacourt C.Three years of mining subsidence monitored by SAR interferometry, near Gardanne,France[J].Journal of Applied Geophysics,2000,43(1):43-54.
[3]Alejano L R,RamíRez-Oyanguren P,Taboada J.FDM predictive methodology for subsidence due to flat and inclined coal seam mining[J].International Journal of Rock Mechanics&Mining Sciences,1999,36(4):475-491.
[4]何国清,杨伦,凌赓娣,等.矿山开采沉陷学[M].徐州:中国矿业大学出版社,1991.HE Guoqing,YANG Lun,LING Gengdi,et al.Ming subsidence science[M].Xuzhou:China University of Mining and Technology Press,1991.
[5]王崇革,宋振骐,石永奎,等.近水平煤层开采上覆岩层运动与沉陷规律相关研究[J].岩土力学,2004,25(8):1343-1346.WANG Chongge,SONG Zhenqi,SHI Yongkui,et al.Study on the relation between stratum movement and subsidence of flat seam mining[J].Rock and Soil Mechanics,2004,25(8):1343-1346.
[6]黄平路,陈从新,肖国峰,等.复杂地质条件下矿山地下开采地表变形规律的研究[J].岩土力学,2009,30(10):3020-3024.HUANG Pinglu, CHEN Congxin, XIAO Guofeng.Study of rock movement caused by underground mining in mines with complicated geological conditions[J].Rock and Soil Mechanics,2009,30(10):3020-3024.
[7]汤伏全.基于地表变形预计的矿区保护煤柱留设方法[J].西安科技大学学报,2009,29(3):313-316.TANG Fuquan.Method of designing protection coal pillar in mine area based on prediction of surface deformation[J].Journal of Xi'an University of Science and Technology,2009,29(3):313-316.
[8]黄敏,李夕兵,曾凌方,等.基于三维建模技术的矿山移动范围圈定[J].矿冶工程,2009,29(4):5-9.HUANG Min, LI Xibing, ZENG Lingfang,et al.Determination of mine movement scope based on 3DM modeling technology[J]. Mining and Metallurgical Engineering,2009,29(4):5-9.
[9]汤伏全,姚顽强,夏玉成.薄基岩下浅埋煤层开采地表沉陷预测方法[J].煤炭科学技术,2007,35(6):71,108-110.TANG Fuquan, YAO Wanqiang, XIA Yucheng.Prediction method of ground subsidence for coal mining in seam under thin base rock[J].Coal Science and Technology,2007,35(6):71,108-110.
[10]陈赞成,余斌,解联库,等.大型地下铁矿覆岩移动破坏规律数值模拟[J].有色金属工程,2015,5(5):101-106.CHEN Zancheng, YU Bin, XIE Lianku, et al.Numerical simulation on overlying strata movement damage rule of large underground iron mines[J].Nonferrous Metals Engineering,2015,5(5):101-106.
[11]于保华,朱卫兵,许家林.深部开采地表沉陷特征的数值模拟[J].采矿与安全工程学报,2007,24(4):422-426.YU Baohua,ZHU Weibing,XU Jialin.Numerical simulation of surface subsidence induced by deep mining[J].Journal of Mining and Safety Engineering,2007,24(4):422-426.
[12]郭延辉,侯克鹏,孙华芬.金属矿山岩层移动角选取的BP神经网络模型及工程应用[J].矿冶,2011,20(4):9.GUO Yanhui,HOU Kepeng,SUN Huafen.Bp neural network model to predict motion angle of metal mine and its application in engineering[J].Mining and Metallurgy,2011,20(4):9.
[13]赵国彦.金属矿隐覆采空区探测及其稳定性预测理论研究[D].长沙:中南大学,2010.ZHAO Guoyan.Research on hidden cavity detection and theories of stability prediction in metal mine[D].Changsha:Central South University,2010.
[14]刘钦,刘志祥,李地元,等.金属矿开采岩层移动角预测知识库模型及其工程应用[J].中南大学学报(自然科学版),2011,42(8):2446-2452.LIU Qin,LIU Zhixiang,LI Diyuan,et al.Knowledge bank model to predict motion angle of terrane in metal deposit and its application in engineering[J].Journal of Central South University:Science and Technology Edition,2011,42(8):2446-2452.
[15]高栗,李夕兵,张楚璇.地下金属矿山岩层移动角选取的进化支持向量机模型及工程应用[J].采矿与安全工程学报,2014,31(5):795-802.GAO Li,LI Xibing,ZHANG Chuxuan.Nonlinear SVM with GA in determination of the motion angle of terrane in underground metal mine and its application in engineering[J].Journal of Mining and Safety Engineering,2014,31(5):795-802.
[16]张学工.关于统计学习理论与支持向量机[J].自动化学报,2000,26(1):32-42.ZHANG Xuegong.Statistical learning theory and support vector machines[J].Acta Automatica Sinica,2000,26(1):32-41.
[17]丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报,2011,40(1):2-10.DING Shifei, QI Bingjuan, TAN Hongyan. An overview on theory and algorithm of support vector machines[J].Journal of University of Electronic Science and Technology of China,2011,40(1):2-10.
[18]杨维,李歧强.粒子群优化算法综述[J].中国工程科学,2004,6(5):87-94.YANG Wei,LI Qiqiang.An overview:particle swarm optimization[J].Engineering Science,2004,6(5):87-94.
[19]Gu D S,Deng J,Li X B,et al.Three dimensional numerical simulation of excavation and backfilling in mining engineering[J].Transactions of Nonferrous Metals Society of China,1999,9(2):213-217.
[20]郭文兵,邓喀中,邹友峰.岩层移动角选取的神经网络方法研究[J].中国安全科学学报,2003,13(9):69.GUO Wenbing,DENG Kazhong,ZOU Youfeng.Study on artificial neural network method for calculation of displacement angle of strata[J].China Safety Science Journal,2003,13(9):69.
[21]李铀,白世伟,杨春和,等.矿山覆岩移动特征与安全开采深度[J].岩土力学,2005(1)27-32.LI You,BAI Shiwei,YANG Chunhe,et al.Characters of overburden strata movement of mines and safe mining depth[J].Rock and Soil Mechanics,2005(1):27-32.
[22]王艳辉,宋卫东,蔡嗣经.地下金属矿山崩落采矿法岩层移动规律分析[J].金属矿山,2002(3):13-16.WANG Yanhui,SONG Weidong,CAI Sijing.Analysis of the rock stratum displacement law in caving mining of underground metal mines[J].Metal Mine,2002(3):13-16.
[23]北京有色冶金设计研究总院.采矿设计手册矿床开采卷[M].北京:冶金工业出版社,1987.General research institute for nonferrous metals.Mining design manual, volume of mining[M].Bejing:Metallurgical Industry Press,1987.
[24]Chang C C,Lin C J.LIBSVM:A library for support vector machines[J].Acm Transactions on Intelligent Systems&Technology,2011,2(3):1-27.