基于钻孔数据煤矿开采地表沉陷预计  

Surface Subsidence Prediction of Mining Based on Borehole Datas

作　　者：徐孟强[1,2] 查剑锋[1,2] 王金涛[1,2] 

机构地区：[1]中国矿业大学环境与测绘学院,江苏徐州221116 [2]国土环境与灾害监测国家测绘地理信息局重点实验室,江苏徐州221116

出　　处：《工业安全与环保》2016年第7期98-102,共5页Industrial Safety and Environmental Protection

摘　　要：开采沉陷引起的环境损害评价是环评工作中的重要内容,现有预计软件基本不适应在大面积环评工作中开展沉陷预计工作。针对现有问题,以矿区钻孔数据为基础,基于Delaunay三角形剖分算法建立了煤层开采地表沉陷预计模型。通过设计对比试验,验证了新建模型预计结果较传统的预计方法更加符合实际地表沉陷情况,预计结果的可靠性较高。将该模型运用到工程实例中,可以节省人力资源,使煤矿生态环评从原来以定性分析、半定量预计为主的状况,提高到以定量预测为主的高度,更好地为矿区生态环境保服务。The environmental impact assessment caused by mining subsidence is an important aspect of EIA,and the existing software is not fit for the work of the large area EIA. Aimed at the present problems,the mining subsidence prediction model based on the Delaunay triangulation is established. Through the contrast test,this new model is more consistent with the actual surface subsidence and the reliability is higher compared to the traditional one. By using this model in the practice,the human resources can be saved,making the coal mine ecological environmental impact assessment improved from the original qualitative analysis and semi quantitative analysis to the high degree of quantitative prediction,and better to protect the ecological environment.

关 键 词：环境评价 DELAUNAY三角形 三角形分割 概率积分法 开采沉陷预计 实验设计 

分 类 号：TD327[矿业工程—矿井建设]