无人机在煤矿采空塌陷多源数据融合探测的应用研究
Application Research of UAV in Multi-Source Data Fusion Detection of Coal Mine Cave-In

矿山资源开采以后，采空区上覆岩层的原始应力平衡状态受到破坏，依次发生冒落、断裂、弯曲等移动变形，最终涉及地表，形成一个比采空区面积大得多的近似椭圆形的下沉塌陷区盆地。针对矿山采空区周边地质情况进行监测传统的方法包括星载SAR、无人机LiDAR、光学遥感、三维激光扫描仪、地基InSAR、远程激光测振、微芯传感等设备以及实地踏勘等。为满足高效常态化的巡检探测要求，采用适配自动机库的航测无人机综合无人机机载激光雷达和光学遥感技术相融合的方法来高效探测采空区的地质灾害情况。利用光学遥感融合AI识别实时监测采空区塌陷情况，再兼容激光雷达的三维点云数据对塌陷区域进行三维建模，在LiDAR成果中圈定出塌陷形态边界、面积、体积等信息。对比星载SAR，航测无人机具有实时性、精度高、成本低的优势；对比实地踏勘，航测无人机的自动化、智能化及高空视角具有高效性、常态化的优势。
After mining resources, the original stress balance of the overlying strata in the goaf is destroyed, and the movement deformation such as caving, fracture and bending, occurs in turn, and finally involves the surface, forming an elliptical subsidence basin which is much larger than the goaf area. The traditional methods for monitoring the geological conditions around the mined-out area include spaceborne SAR, UAV LiDAR, optical remote sensing, 3D laser scanner, ground-based InSAR, remote laser vibration measurement, micro-core sensing and other equipment as well as field survey. In order to meet the requirements of efficient and normal inspection and detection, the method of integrating aerial survey UAV with automatic hangar, airborne Lidar and optical remote sensing technology is adopted to efficiently detect geological hazards in goaf. The optical remote sensing fusion AI was used to identify and monitor the gob collapse situation in real time, and then the three-dimensional point cloud data of LiDAR was compatible to conduct three-dimensional modeling of the collapse area, and the information of collapse form boundary, area and volume was defined in the LIDAR results. Compared with spaceborne SAR, aerial survey UAV has the advantages of real-time, high precision and low cost. Compared with field survey, the automation, intelligence and high-altitude perspective of aerial survey UAV have the advantages of high efficiency and normalization.