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.
作者
江克贵
王磊
魏涛
蒋创
朱尚军
张广学
房振
Jiang Kegui;Wang Lei;Wei Tao;Jiang Chuang;Zhu Shangjun;Zhang Guangxue;Fang Zhen(School of Geomatics,Anhui University of Science and Technology,Huainan 232001,China;Yingpanhao of Ordos City Coal Co.,Ltd.,Ordos 017300,China)
出处
《金属矿山》
CAS
北大核心
2019年第7期161-166,共6页
Metal Mine
基金
国家自然科学基金项目(编号:41602357)
安徽高校自然科学研究项目(编号:KJ2016A190)