Identification of Surface Hazards in Mining Areas Based on DeeplabV3+Network and Attention Mechanism:Taking 30507 Working Face of the Tashan Coal Mine as an Example
In order to solve the problem of monitoring hidden dangers on the surface of the mine area,a method for rapid monitoring and identification of hidden dangers on the surface of the mine area is proposed with the background of the 30507 working face of the Tashan Coal Mine.Using UAV-mounted sensors and tilt photogrammetry technology,a three-dimensional live model of the mine surface is constructed,and orthophotos and spatial point clouds are generated,a fissure identification method based on the DeeplabV3+network and the attention mechanism is proposed,and the improvement effect is better than that of the current mainstream network,a subsidence analysis method based on the three-dimensional spatial point clouds is proposed,and the noise is removed with the density-noise spatial clustering algorithm,and the noise is removed through the KD Tree-based K-nearest neighbour algorithm based on KD Tree and point cloud surface reconstruction technology based on Delaunay triangulation network for subsidence analysis,to achieve the monitoring of surface data in the mining area.
inclined photogrammetryartificial intelligence techniques3D spatial point cloud of mining areaidentification of surface fissuresintelligent analysis of subsidence
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