基于无人机激光雷达技术的开采沉陷监测方法与参数反演

矿区开采沉陷监测与预测对于煤炭安全生产来说至关重要，目前煤矿地表沉陷监测的主流手段均有一定的局限性，存在精度与效率不能兼得的问题。利用无人机激光雷达（UAV LiDAR）技术可以实现矿区地表三维点云的快速获取，建立多期数字高程模型（DEM），两期DEM相减即可得到沉陷盆地，具有高效高精的特点。本文对无人机激光雷达地表沉陷监测的原理流程和概率积分预计参数动态反演方法进行了分析讨论，以内蒙古唐家会煤矿为例，设计了无人机激光雷达飞行方案，采集了两期激光点云数据，并对实测数据进行了组合解算、融合、滤波，建立两期DEM，求取了观测时间段内的地表下沉盆地，并进行了全盆地动态反演，得到测区概率积分预计参数。实验结果DEM精度分别为0.034mm和0.037mm；下沉盆地精度为0.050mm，结果对于煤矿开采沉陷监测与预测来说是相对可靠的，为无人机激光雷达应用于地表监测提供了案例。

Mining subsidence monitoring method and parameter inversion based on UAV Lidar Technology

Mining subsidence monitoring and prediction is very important for coal production safety. At present, the mainstream means of mining subsidence monitoring have certain limitations, and there is a problem that the accuracy and efficiency can not be both. UAV lidar technology can be used to quickly acquire 3D point cloud of mining area surface and establish multi-phase digital elevation model (DEM),The subsidence basin can be obtained by subtraction of two periods of DEM,It has the characteristics of high efficiency and precision. In this paper, firstly, the principle process of UAV lidar surface subsidence monitoring and the inversion method of probability integral prediction parameters are analyzed and discussed. Then, taking Tangjiahui coal mine in Inner Mongolia as an example, the flight scheme of UAV lidar is designed, the two phases of laser point cloud data are collected, and the measured data are combined, solved, fused and filtered to establish two phases of DEM, The subsidence basins in the observation period were obtained, and the dynamic parameters of the whole basin were inversed. The accuracy of DEM is 0.034mm and 0.037mm respectively; The accuracy of subsidence basin is 0.050mm. The results are relatively reliable for coal mining subsidence monitoring and prediction, and provide a case for UAV lidar application in surface monitoring.