Mine excavation systems are usually dozens of kilometers long with varying geometry on a small scale (roughness and shape of the walls) and on a large scale (varying widths of the tunnels, turns, and crossings). In this article, the authors address the problem of analyzing laser scanning data from large mining structures that can be used for various purposes, with focus on ventilation simulations. Together with the quality of the measurement data (diverse point-cloud density, missing samples, holes induced by obstructions in the field of view, measurement noise), this creates problems that require multi-stage processing of the obtained data. The authors propose a robust methodology to process a single segmented section of the mining system. The presented approach focuses on obtaining a point cloud ready for application in the computational fluid dynamics (CFD) analysis of airflow with minimal need for additional manual corrections on the generated mesh model. This requires the point cloud to have evenly distributed points and reduced noise (together with removal of objects inside) while keeping the unique geometrical properties and shape of the scanned tunnels. Proposed methodology uses trajectory of the excavation either obtained during the measurements or by skeletonization process explained in the article. Cross-sections obtained on planes perpendicular to the trajectory are processed towards the equalization of point distribution, removing measurement noise, holes in the point cloud and objects inside the excavation. The effects of the proposed algorithm are validated by comparing the processed cloud with the original cloud and testing within the CFD environment. The algorithm proved high effectiveness in improving skewness rate of the obtained mesh and geometry mapping accuracy (standard deviation below 5 centimeters in cloud-to-mesh comparison).

中文翻译：

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用于采矿挖掘均匀网格生成的 3D 点云正则化方法


矿山开挖系统通常长达数十公里，小规模（岩壁的粗糙度和形状）和大尺度（隧道、转弯和交叉口的宽度不同）具有不同的几何形状。在本文中，作者解决了分析可用于各种目的的大型采矿结构的激光扫描数据的问题，重点是通风模拟。再加上测量数据的质量（不同的点云密度、缺失的样品、视场中的障碍物引起的孔洞、测量噪声），这会产生需要对所获得的数据进行多阶段处理的问题。作者提出了一种强大的方法来处理采矿系统的单个分段部分。所提出的方法侧重于获得可用于气流计算流体动力学 （CFD） 分析的点云，并且几乎不需要对生成的网格模型进行额外的手动校正。这要求点云具有均匀分布的点和减少的噪声（同时去除内部的物体），同时保持扫描隧道的独特几何特性和形状。所提出的方法使用在测量期间或通过文章中解释的骨架化过程获得的挖掘轨迹。在垂直于轨迹的平面上获得的横截面经过处理，以实现点分布的均衡，去除测量噪声、点云中的孔洞和挖掘内部的物体。通过将处理后的云与原始云进行比较并在 CFD 环境中进行测试，验证了所提算法的效果。 该算法在提高所得网格的偏度率和几何映射精度（云到网格比较的标准差低于 5 厘米）方面被证明是有效的。