# A Coal Mine Excavation Tunnels Modeling Method Based on Point Clouds
###### Abstract  
The excavation tunnel model is an important reference for mine equipment control and tunnel deformation monitoring. Currently, tunnel models are mainly created manually, and point cloud reconstruction algorithms are difficult to directly apply to tunnel point clouds. To address these issues, this paper proposes a point cloud-based excavation tunnel modeling method. First, preprocessing algorithms such as point cloud coordinate transformation, tunnel point cloud extraction, and tunnel point cloud completion are used to filter out equipment point clouds inside the tunnel and repair occluded holes. Then, the tunnel centerline is extracted, and consistency optimization is performed on the point cloud normal vectors. Finally, a tunnel model is established based on the Poisson modeling algorithm, enabling high-precision tunnel modeling. The proposed algorithm's accuracy and effectiveness are demonstrated through experiments on four different coal mine tunnels. surface reconstruction; coal mine excavation tunnels; point cloud +
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enhancing mine safety and prevention capabilities [11; 12]. By taking appropriate reinforcement measures, this can reduce the probability of accidents, ensuring the safety of coal mines. Therefore, tunnel modeling is crucial for both mining production and safety. In recent years, with the development of point cloud acquisition technologies, such as 3D scanners or LiDAR, it has become possible to capture point cloud data quickly and accurately [13]. A point cloud is a dataset composed of a large number of three-dimensional coordinate points, often including millions of points, which can accurately reflect the shape and structure of objects. Point cloud-based modeling methods have made significant progress in the field of 3D reconstruction. Point cloud surface reconstruction techniques refer to the establishment of a three-dimensional mesh from scattered points to lines and from lines to surfaces through certain topological connection rules [14]. Depending on whether the vertices of the mesh surface belong to the original point cloud, modeling algorithms can be classified into implicit methods based on implicit functions and explicit methods based on computational geometry. The Poisson reconstruction [15] and radial basis function [16] methods are representative implicit modeling methods. They involve fitting a smooth implicit function, constructing a contour surface, and discretizing the zero level set of the implicit function into a triangular mesh. Explicit modeling methods include Delaunay triangulation [17], region growing [18], etc., which connect discrete points in three-dimensional space to form different polygons based on certain topological connection rules. However, the above modeling methods are mainly designed for single objects. For modeling coal mine tunnels, challenges arise due to the limited space in tunnels, limited angles for point cloud acquisition, and the presence of a large amount of industrial equipment causing occlusion during data collection. Therefore, the above modeling algorithms cannot directly achieve good results in tunnel point cloud modeling. The traditional method of tunnel modeling involves manually modeling the tunnel using software based on tunnel images and dimensions [19; 20]. For example, based on the designed cross-section and length of the tunnel, a tunnel model can be created using software like Revit2024. This method has been widely used in various fields, including the construction of subway [21], road [22], and coal mine tunnels [23]. However, this modeling technique is time-consuming and complex. Additionally, the centerline and cross-section (usually rectangular) of excavation tunnels are typically specified during tunnel design. However, due to factors such as equipment and manual operations, the excavated tunnel cross-section often deviates from the designed shape and is not a regular rectangle, resulting in overex excavation and underexcavation, as shown in Figure 1a.