A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

Abstract

In underground mining, new workings (tunnels) are constructed by blasting or mechanical excavation. The blasting technique used in underground mines is supported by economic aspects, especially for deposits characterized by hard rocks. Unfortunately, the quality of the result may be different than expected in terms of the general geometry of work or the roughness of excavation surfaces. The blasting technique is also a source of vibrations that may affect other existing structures, affecting their stability. Therefore, it is of great importance to monitor both the quality of the new tunnels and changes in existing tunnels that may cause rockfall from the sidewalls and ceilings of both new and existing tunnels. The length of mining tunnels and support structures in underground mines is massive. Even if one would like to limit monitoring of tunnel geometry to those used every day for major technological processes such as transport, it is a vast amount of work. What is more, any stationary monitoring system is hard to utilize both due to everyday blasting procedures and mobile machine operation. The method proposed here is based on quick LiDAR/Terrestrial Laser Scanner measurements to obtain a cloud of points, which allows generating the spatial model of a mine’s geometry. Data processing procedures are proposed to extract several parameters describing the geometry of the tunnels. Firstly, the model is re-sampled to obtain its uniform structure. Next, a segmentation technique is applied to separate the cross sections with a specific resolution. Statistical parameters are selected to describe each cross section for final 1D feature analysis along the tunnel length. Such a set of parameters may serve as a basis for blasting evaluation, as well as long-term deformation monitoring. The methodology was tested and validated for the data obtained in a former gold and arsenic mine Zloty Stok, Poland.

Keywords

• underground mining
• mining excavations
• tunneling
• LiDAR
• terrestrial laser scanning
• point cloud