Identification and Grouping Method of Strike Information of Rock Mass Based on the HDBSCAN Algorithm

doi:10.12068/j.issn.1005-3026.2022.06.018

Abstract

Abstract: Accurate acquisition of the strike information of the rock discontinuities is the first and key step in rock stability analysis. To solve the problems of insufficient clustering criteria and strong parameter sensitivity of the basic DBSCAN algorithm in processing the point cloud data， the HDBSCAN algorithm was proposed to extend the clustering criteria based on additional attributes of point clouds to improve the accuracy and robustness of the clustering algorithm. Meanwhile， based on the color and density attributes of the point cloud， the segmentation and extraction of the studied area of non-fully exposed rock in natural state were realized and the influence of the point cloud at non-rock structural planes on the identification and grouping of rock discontinuities production was reduced. The method was applied to a typical overburden rock slope of Dashidong tuff mine， and the results show that the method proposed can effectively eliminate non-target point cloud data， while the maximum relative error is less than 0.59% compared with the manual method， the method of rock discontinuities strike extraction and grouping are satisfactory and has practical engineering value.

Key words: UAV measurement; 3D point cloud processing; rock discontinuities identification; rock discontinuities grouping

CLC Number:

TU452

WANG Shu-hong， WEI Wei， CHEN Hao， YIN Hong. Identification and Grouping Method of Strike Information of Rock Mass Based on the HDBSCAN Algorithm[J]. Journal of Northeastern University(Natural Science), 2022, 43(6): 888-896.

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