无人机LiDAR在采空区沉陷监测中的应用

Application of UAV LiDAR in monitoring subsidence of goaf

煤炭资源高强度开采对地表造成了极大破坏,严重威胁建(构)筑物安全,现有的开采沉陷监测方法缺乏面域形变监测,限制了采空区地表形变规律研究。针对传统观测方法的不足,以西部煤矿某工作面为研究对象,采用无人机LiDAR(Light Detection and Ranging)测量方法,进行采空区面域沉陷监测研究。针对采空区地形特征,改进渐进三角网点云滤波过程中种子点的选取方法,提高点云滤波精度;对研究区沉陷模型精度进行验证,结果表明:沉陷模型整体误差小于100 mm,平均误差小于50 mm;最后,基于沉陷模型进行数据挖掘分析,获取下沉等值线图、下沉面积统计图、下沉分区统计图等,实现采空区全方位沉陷监测。为煤矿煤炭资源开采、地表下沉监测、土地复垦和生态环境保护等提供参考。

High-intensity mining of coal resources has caused great damage to the surface and seriously threatened the safety of buildings(structures).The existing mining subsidence monitoring methods lacked overall surface deformation monitoring,which limited the study of surface deformation laws in goaf.In response to the shortcomings of traditional observation methods,a working face in the western coal mine was taken as the research object,and the unmanned aerial vehicle LiDAR(Light Detection and Ranging)survey method was used to monitor the subsidence of the goaf area.In light of the terrain characteristics of the goaf,the selection method of seed points in the process of progressive triangulation cloud filtering was improved so as to promote the precision of point cloud filtering;the accuracy of the subsidence model in the study area was verified.The results showed that the overall error of the settlement model was less than 100 mm,and the average error was less than 50 mm;through the data mining analysis of the subsidence model,the subsidence contour map,subsidence area statistical map,and subsidence zoning statistical map were obtained to achieve the all-round subsidence monitoring of the goaf.The research provides a reference for coal mining,surface subsidence monitoring,land reclamation and ecological environment protection.