Octree parallel identification method of rock mass structural plane based on point cloud

• Main Authors: Zhou, Xiaohang, Wei, Shuangfeng, Liu, Guangzu, Zlatanova, Sisi
• Format: Conference Proceeding
• Language: English
• Published: SPIE 19.01.2024
• ISBN: 9781510672789; 1510672788
• ISSN: 0277-786X
• DOI: 10.1117/12.3020975

The rock body of the slope of the open pit mine will be affected by water, wind, sunlight, chemistry and other influences for a long time, which will cause the rock body to produce weathering phenomenon, and the weathering of the rock body will increase the difficulty of the identification of the structural surface, and the data volume of the point cloud is large, and the efficiency of the identification of the structural surface of the rock body needs to be improved, this paper adopts two sets of data for the identification of structural surfaces, and adopts the sphere fitting algorithm for the estimation of the normal vectors of the rock structural surface, and adopts a parallel The octree algorithm is used to segment the point cloud data of the structural surface of the rock body, and the Euclidean clustering algorithm based on the normal vectoris used to identify the structural surface in each subspace in parallel, and the structural surface is identified by the Euclidean clustering algorithm, the regional growth algorithm, the K-mean algorithm, and the algorithm proposed in this paper, and it can be obtained that the efficiency of the structural surface identification using the algorithm of this paper is significantly improved by experimental analysis, and it provides methodological support for the subsequent slope deformation analysis and early warning. deformation analysis and early warning to provide methodological support.