基于SLAM激光雷达点云数据的岩体结构面自动识别方法

Automatic Identification of Rock Structural Planes Based on LiDAR Point Cloud Data and Discontinuity Set Extraction

随着工程项目不断向复杂地质环境条件区域发展,也随着三维激光扫描技术的快速发展,激光雷达点云数据已成为地质工程领域获取地质信息的重要手段。为了利用SLAM激光雷达点云数据并结合岩体不连续性提取的方法,以实现结构面的自动识别,以某抽水蓄能勘探平洞为例,首先采用SLAM手持激光雷达技术获取岩体的三维点云数据,然后通过点云建图重定向、去噪、配准等图像处理技术对原始点云进行处理,接着运用DSE软件进行结构面的特征提取和分类,最后对识别结果与罗盘测量结果进行了对比。结果表明:该方法能够有效识别出不同类型的结构面,且与传统方法相比效率更高,参与人员更少,可为岩体结构分析提供一种新的技术手段,对于提高复杂环境条件下勘察作业安全与效率提升具有重要意义。

With the continuous development of engineering projects in areas with complex geological conditions and the rapid development of 3D laser scanning technology,LiDAR point cloud data has become an important means of obtaining geological information in the field of geological engineering.This article aims to use LiDAR point cloud data combined with the method of extracting rock discontinuity to achieve automatic recognition of structural planes.It takes a pumped storage exploration adit as an example.First,SLAM handheld LiDAR technology is used to obtain three-dimensional point cloud data of the rock mass.Then,image processing techniques such as point cloud mapping redirection,denoising,and registration are used to process the original point cloud.Then,DSE software is used for feature extraction and classification of the structural surface.Finally,the recognition results are compared with the compass measurement results.The results indicate that this method can effectively identify different types of structural planes and is more efficient than traditional methods,requiring fewer staff.The automatic identification method proposed in this article provides a new technical means for rock structure analysis,which is of great significance for improving the safety and efficiency of operations under complex environmental conditions.