A critical review of automated extraction of rock mass parameters using 3D point cloud data

Abstract

Abstract This paper presents a comprehensive review aimed at gaining insights into the current state of research on quantification technology used for acquiring three-dimensional (3D) point cloud data of rock masses and extracting vital structural information. Addressing this significant challenge and problem within the field of rock engineering is the main objective of this study. The timely and accurate acquisition of rock mass data and fine characterization of rock mass parameters can avoid unnecessary personnel injury and property damage. First, the methods of point cloud information acquisition and structural information extraction are systematically summarized and classified. Then, various existing methods are analyzed for their advantages and disadvantages. Based on this analysis, the future development direction of relevant technologies is proposed to improve the level of acquisition of 3D information of rock mass and the level of extraction of key information of rock mass. The results indicate that rock mass point cloud information acquisition technology can be classified into two types: laser point cloud acquisition and image reconstruction based on structure from motion (SfM) algorithm. Rock mass structural information can be classified into rock mass structural planes and their attitudes, rock mass traces and their geometric parameters, and other rock mass parameters, including structural plane roughness, spacing, and block characteristics, etc. Different acquisition technologies and feature extraction methods have their own advantages, disadvantages, and applicable ranges. Therefore, a comprehensive selection of various evaluation methods should be made based on specific engineering characteristics and existing data situations in practice.