基于改进三角剖分的复杂形状工作面开采沉陷预计方法
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摘要
为弥补复杂形状工作面变形预计的不足,提高开采沉陷变形预计的准确性,构建了一种基于改进三角剖分的复杂形状工作面开采沉陷预计方法。该方法引入了改进的三角剖分算法,优化了坐标系统转换、拐点偏移改正等方法,基于概率积分法原理建立了复杂形状工作面的开采沉陷预计模型。该模型首先利用改进的三角剖分算法将工作面剖分为多个三角形;然后用变步长Simpson二重积分方法在三角形单元内进行下沉预计,将各单元的预计结果求和,即可得到整个工作面开采对地表下沉的影响情况;最后根据概率积分法原理可分别得到其他移动变形预计值。采用MATLAB软件开发了所构建模型的沉陷预计程序。模拟试验结果表明:该模型预计值插入点全部分布于常规概率积分法预计下沉曲线上,表明该模型能够对形状较为复杂的不规则工作面进行开采沉陷变形预计。淮南顾桥矿1414(1)工作面实例分析表明:该模型预计的下沉曲线与实测下沉曲线的拟合度较好,预计下沉值的绝对误差为0.2～359.2 mm,相对误差为25.02%,中误差为101.9 mm,能较好地满足工程应用需求。
In order to make up for the insufficiency of the complex shape working face deformation prediction,and to improve the adaptability and accuracy of the mining subsidence deformation prediction,subsidence prediction method of complex shape working face based on improved triangulation algorithm is built.In this method,an improved triangulation algorithm is introduced,and key methods such as coordinate system conversion and correction of inflexion migration are optimized,the subsidence prediction model of complex shape working face is established based on probability integral method.In this model,the working face is split into multiple triangles by using the improved triangulation algorithm;then,the variable step-size Simpson double integral method is adopted to conduct subsidence prediction in triangular units,and the impact of the entire working face mining on the surface mining subsidence can be obtained through summation method;finally,other movement and deformation prediction values can be received in turn according to probability integral method.Based on MATLAB software,the subsidence prediction program of the model established in this paper is developed.The simulation results show that the predicted insertion points of the model are all distributed on the expected subsidence curve of the conventional probability integral model,which indicated that the model could predict the mining subsidence deformation of irregular working face with complex shape.The test results of the 1414(1)working face of Guqiao Mine in Huainan City show that the fitting effects of the prediction subsidence curve and the measured subsidence curve is good,the absolute error of prediction subsidence curve is from 0.2 mm to 359.2 mm,the relative error is 25.02%,and the medium error is 101.9 mm,which can meet the requirement for engineering application.
In order to make up for the insufficiency of the complex shape working face deformation prediction,and to improve the adaptability and accuracy of the mining subsidence deformation prediction,subsidence prediction method of complex shape working face based on improved triangulation algorithm is built.In this method,an improved triangulation algorithm is introduced,and key methods such as coordinate system conversion and correction of inflexion migration are optimized,the subsidence prediction model of complex shape working face is established based on probability integral method.In this model,the working face is split into multiple triangles by using the improved triangulation algorithm;then,the variable step-size Simpson double integral method is adopted to conduct subsidence prediction in triangular units,and the impact of the entire working face mining on the surface mining subsidence can be obtained through summation method;finally,other movement and deformation prediction values can be received in turn according to probability integral method.Based on MATLAB software,the subsidence prediction program of the model established in this paper is developed.The simulation results show that the predicted insertion points of the model are all distributed on the expected subsidence curve of the conventional probability integral model,which indicated that the model could predict the mining subsidence deformation of irregular working face with complex shape.The test results of the 1414(1)working face of Guqiao Mine in Huainan City show that the fitting effects of the prediction subsidence curve and the measured subsidence curve is good,the absolute error of prediction subsidence curve is from 0.2 mm to 359.2 mm,the relative error is 25.02%,and the medium error is 101.9 mm,which can meet the requirement for engineering application.
引文
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[5]沈殊璇,薄亚明.一种矩形网格自动剖分及加密算法[J].计算机工程与应用,2003,39(16):91-93.Shen Shuxuan,Bo Yaming.A new algorithm for automatic rectangular mesh and mesh refinemen[tJ].Computer Engineering and Applications,2003,39(16):91-93.
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[7]康建荣,王金庄,温泽民.任意形多工作面多线段开采沉陷预计系统(MSPS)[J].矿山测量,2000(1):24-27.Kang Jianrong,Wang Jinzhuang,Wen Zemin.Arbitrarily shaped multi-face multi-line of mining subsidence prediction system(MSPS)[J].Mine Surveying,2000(1):24-27.
[8]张兵,崔希民,赵玉玲,等.不规则工作面沉陷预计三角剖分算法研究[J].煤矿安全,2018,49(9):280-283.Zhang Bing,Cun Ximin,Zhao Yuling,et al.Research on triangulation algorithm for irregular mining working face[J].Safety in Coal Mines,2018,49(9):280-283.
[9]李明,李琰庆,王红梅.任意形状工作面开采沉陷预计系统开发[J].矿业安全与环保,2008,35(5):18-21.Li Ming,Li Yanqing,Wang Hongmei.Development of predicting system for mining subsidence of arbitrarily shaped face[J].Mining Safety&Environmental Protection,2008,35(5):18-21.
[10]徐孟强,查剑锋.基于三角形剖分算法的开采沉陷预计系统设计[J].金属矿山,2016(2):128-131.Xu Mengqiang,Zha Jianfeng.Software design of mining subsidence prediction based on triangle subdivision algorithm[J].Metal Mine,2016(2):128-131.
[11]刘伟韬,刘欢.不规则工作面开采地表沉陷预计研究[J].矿山测量,2014(5):68-71.Liu Weitao,Liu Huan.Prediction of surface subsidence caused by irregular face mining[J].Mine Surveying,2014(5):68-71.
[12]赵晓东,陈阳,蒋建.任意形状工作面沉陷预测的概率积分法及其应用[J].岩土力学,2016(12):3387-3392.Zhao Xiaodong,Chen Yang,Jiang Jian.Probability integral method of arbitrary shape face to predict mining subsidence and its application[J].Rock and Soil Mechanics,2016(12):3387-3392.
[13]许冬,王临清,吴侃.任意形状工作面沉陷预计计算方法[J].金属矿山,2014(5):55-59.Xu Dong,Wang Linqing,Wu Kan.Mining subsidence prediction calculation methods of random shape working face[J].Metal Mine,2014(5):55-59.
[14]武若,张新东.简单多边形三角剖分算法[J].微计算机信息,2010,26(30):226-227.Wu Ruo,Zhang Xindong.A simple polygon triangulation algorithm[J].Microcomputer Information,2010,26(30):226-227.
[15]曹清龙,李君.基于最小距离的简单多边形三角剖分[J].长江大学学报:自然科学版,2006(4):54-56.Cao Qinglong,Li Jun.Simply polygon triangulation algorithm based on minimum distance[J].Journal of Yangtze University:Natural Science Edition,2006(4):54-56.
[16]刘少华,汤军,吴东胜,等.简单多边形三角剖分的一种快速算法及应用[J].计算机应用与软件,2008,25(3):79-80.Liu Shaohua,Tang Jun,Wu Dongsheng,et al.A fast algorithm for simple polygon triangulation and its applications[J].Computer Applications and Software,2008,25(3):79-80.
[17]周棒,康建荣,胡晋山,等.基于VC++的任意形状工作面计算坐标系的自动确定[J].矿业研究与开发,2018,38(9):58-62.Zhou Bang,Kang Jianrong,Hu Jinshan,et al.Automatic determination of calculating coordinate system for arbitrary shape working face[J].Mining Research and Development,2018,38(9):58-62.
[18]陈岩,奚砚涛.基于Surfer的金属矿山开采沉陷预测和三维可视化[J].金属矿山,2012(5):149-151.Chen Yan,Xi Yantao.Metal mine mining subsidence prediction and 3D visualization based on surfer[J].Metal Mine,2012(5):149-151.
[19]张合兵,王世东,李春意.煤矿区土地复垦中土地损毁预测方法研究[J].金属矿山,2013(9):142-147.Zhang Hebing,Wang Shidong,Li Chunyi.Research on land destruction prediction methods of land relamation in coal mining area[J].Metal Mine,2013(9):142-147.
[20]高超,徐乃忠,刘贵.特厚煤层综放开采地表沉陷预计模型算法改进[J].煤炭学报,2018,43(4):939-944.Gao Chao,Xu Naizhong,Liu Gui.Improvement on prediction model algorithm for surface subsidence of extra thick seam using fullymechanized top coal caving method[J].Journal of China Coal Society,2018,43(4):939-944.
[21]陈元非,王磊,查剑锋.矿山开采沉陷预计与分析[J].煤矿安全,2017,48(1):99-102.Chen Yuanfei,Wang Lei,Zha Jianfeng.Prediction and analysis of mine mining subsidence[J].Safety in Coal Mines,2017,48(1):99-102.
[22]蒋创,王磊,魏涛,等.基于模矢法的顾桥矿采空区参数识别[J].金属矿山,2018(8):123-126.Jiang Chuang,Wang Lei,Wei Tao,et al.Identification method of the goaf’s parameters in Guqiao Mine based on pattern search method[J].Metal Mine,2018(8):123-126.
[2]蒋建,赵晓东,陈阳.基于GIS的任意形状工作面预测概率积分算法研究[J].计算机应用研究,2015,32(12):3673-3676.Jiang Jian,Zhao Xiaodong,Chen Yang.Study on GIS-based probability integral algorithm to predict mining subsidence for arbitrary shape face[J].Application Research of Computers,2015,32(12):3673-3676.
[3]赵科,张开智,王树立,等.榆家梁煤矿不规则采场顶板控制[J].煤矿安全,2014,45(8):231-233.Zhao Ke,Zhang Kaizhi,Wang Shuli,et al.Roof control for irregular working face in Yujialiang Coal Mine[J].Safety in Coal Mines,2014,45(8):231-233.
[4]吴侃,周鸣.开采沉陷预测预报系统[M].徐州:中国矿业大学出版社,1999.Wu Kan,Zhou Ming.Mining Subsidence Prediction System[M].Xuzhou:China University of Mining and Technology Press,1999.
[5]沈殊璇,薄亚明.一种矩形网格自动剖分及加密算法[J].计算机工程与应用,2003,39(16):91-93.Shen Shuxuan,Bo Yaming.A new algorithm for automatic rectangular mesh and mesh refinemen[tJ].Computer Engineering and Applications,2003,39(16):91-93.
[6]朱刘娟,陈俊杰,邹友峰.任意形状工作面开采地表移动变形预计的算法实现[J].辽宁工程技术大学学报,2005,24(3):337-340.Zhu Liujuan,Chen Junjie,Zou Youfeng.Algorithm of ground movement and deformation prediction in mining of random shape face[J].Journal of Liaoning Technical University,2005,24(3):337-340.
[7]康建荣,王金庄,温泽民.任意形多工作面多线段开采沉陷预计系统(MSPS)[J].矿山测量,2000(1):24-27.Kang Jianrong,Wang Jinzhuang,Wen Zemin.Arbitrarily shaped multi-face multi-line of mining subsidence prediction system(MSPS)[J].Mine Surveying,2000(1):24-27.
[8]张兵,崔希民,赵玉玲,等.不规则工作面沉陷预计三角剖分算法研究[J].煤矿安全,2018,49(9):280-283.Zhang Bing,Cun Ximin,Zhao Yuling,et al.Research on triangulation algorithm for irregular mining working face[J].Safety in Coal Mines,2018,49(9):280-283.
[9]李明,李琰庆,王红梅.任意形状工作面开采沉陷预计系统开发[J].矿业安全与环保,2008,35(5):18-21.Li Ming,Li Yanqing,Wang Hongmei.Development of predicting system for mining subsidence of arbitrarily shaped face[J].Mining Safety&Environmental Protection,2008,35(5):18-21.
[10]徐孟强,查剑锋.基于三角形剖分算法的开采沉陷预计系统设计[J].金属矿山,2016(2):128-131.Xu Mengqiang,Zha Jianfeng.Software design of mining subsidence prediction based on triangle subdivision algorithm[J].Metal Mine,2016(2):128-131.
[11]刘伟韬,刘欢.不规则工作面开采地表沉陷预计研究[J].矿山测量,2014(5):68-71.Liu Weitao,Liu Huan.Prediction of surface subsidence caused by irregular face mining[J].Mine Surveying,2014(5):68-71.
[12]赵晓东,陈阳,蒋建.任意形状工作面沉陷预测的概率积分法及其应用[J].岩土力学,2016(12):3387-3392.Zhao Xiaodong,Chen Yang,Jiang Jian.Probability integral method of arbitrary shape face to predict mining subsidence and its application[J].Rock and Soil Mechanics,2016(12):3387-3392.
[13]许冬,王临清,吴侃.任意形状工作面沉陷预计计算方法[J].金属矿山,2014(5):55-59.Xu Dong,Wang Linqing,Wu Kan.Mining subsidence prediction calculation methods of random shape working face[J].Metal Mine,2014(5):55-59.
[14]武若,张新东.简单多边形三角剖分算法[J].微计算机信息,2010,26(30):226-227.Wu Ruo,Zhang Xindong.A simple polygon triangulation algorithm[J].Microcomputer Information,2010,26(30):226-227.
[15]曹清龙,李君.基于最小距离的简单多边形三角剖分[J].长江大学学报:自然科学版,2006(4):54-56.Cao Qinglong,Li Jun.Simply polygon triangulation algorithm based on minimum distance[J].Journal of Yangtze University:Natural Science Edition,2006(4):54-56.
[16]刘少华,汤军,吴东胜,等.简单多边形三角剖分的一种快速算法及应用[J].计算机应用与软件,2008,25(3):79-80.Liu Shaohua,Tang Jun,Wu Dongsheng,et al.A fast algorithm for simple polygon triangulation and its applications[J].Computer Applications and Software,2008,25(3):79-80.
[17]周棒,康建荣,胡晋山,等.基于VC++的任意形状工作面计算坐标系的自动确定[J].矿业研究与开发,2018,38(9):58-62.Zhou Bang,Kang Jianrong,Hu Jinshan,et al.Automatic determination of calculating coordinate system for arbitrary shape working face[J].Mining Research and Development,2018,38(9):58-62.
[18]陈岩,奚砚涛.基于Surfer的金属矿山开采沉陷预测和三维可视化[J].金属矿山,2012(5):149-151.Chen Yan,Xi Yantao.Metal mine mining subsidence prediction and 3D visualization based on surfer[J].Metal Mine,2012(5):149-151.
[19]张合兵,王世东,李春意.煤矿区土地复垦中土地损毁预测方法研究[J].金属矿山,2013(9):142-147.Zhang Hebing,Wang Shidong,Li Chunyi.Research on land destruction prediction methods of land relamation in coal mining area[J].Metal Mine,2013(9):142-147.
[20]高超,徐乃忠,刘贵.特厚煤层综放开采地表沉陷预计模型算法改进[J].煤炭学报,2018,43(4):939-944.Gao Chao,Xu Naizhong,Liu Gui.Improvement on prediction model algorithm for surface subsidence of extra thick seam using fullymechanized top coal caving method[J].Journal of China Coal Society,2018,43(4):939-944.
[21]陈元非,王磊,查剑锋.矿山开采沉陷预计与分析[J].煤矿安全,2017,48(1):99-102.Chen Yuanfei,Wang Lei,Zha Jianfeng.Prediction and analysis of mine mining subsidence[J].Safety in Coal Mines,2017,48(1):99-102.
[22]蒋创,王磊,魏涛,等.基于模矢法的顾桥矿采空区参数识别[J].金属矿山,2018(8):123-126.Jiang Chuang,Wang Lei,Wei Tao,et al.Identification method of the goaf’s parameters in Guqiao Mine based on pattern search method[J].Metal Mine,2018(8):123-126.