文献类型：期刊文献

英文题名：Automatic identification and characterization of discontinuities in rock masses from 3D point clouds

作者：Kong, Deheng[1];Wu, Faquan[1,2];Saroglou, Charalampos[3]

机构：[1]Tongji Univ, Coll Civil Engn, Dept Geotech Engn, Shanghai 200092, Peoples R China;[2]Shaoxing Univ, Key Lab Rock Mech & Geohasards Zhejiang Prov, Shaoxing 312000, Peoples R China;[3]Natl Tech Univ Athens, Sch Civil Engn, Dept Geotech, Athens 15780, Greece

年份：2020

卷号：265

外文期刊名：ENGINEERING GEOLOGY

收录：SCI-EXPANDED(收录号：WOS:000517660100040)、、EI(收录号：20195007815212)、Scopus(收录号：2-s2.0-85076086569)、WOS

基金：This research was supported by the National Natural Science Foundation of China (Grant No. 41831290) and the Zhejiang Provincial Natural Science Foundation of China (Grant No. LGF18D020002). The authors gratefully acknowledge Chen et al. (2016) and Riquelme et al. (2014) for their previous studies. The authors also thank Rockbench repository for providing data of the study area. And the authors appreciate the editor and reviewers whose detailed comments and suggestions helped improve this manuscript significantly.

语种：英文

外文关键词：3D point cloud; Rock mass; Automatic; Discontinuity; LiDAR; UAV

外文摘要：The routine application of remote surveying techniques which can quickly acquire 3D digital data with high resolution, in particular digital photogrammetry, light detection and ranging (LiDAR) and unmanned aerial vehicle (UAV) for rock mass characterization has rapidly grown over the past decade. In this paper, a new method for automatic identification and interpretation of rock mass discontinuities, clustering of discontinuity sets and characterization of discontinuity orientation, persistence and spacing using 3D point clouds, is presented. The proposed method is based on a four-stage procedure consisting of: (1) normal vector calculation using the iterative reweighted plane fitting (IRPF) method, (2) discontinuity sets clustering by fast search and find of density peaks (CFSFDP) algorithm, and Fisher's K value iterative calculation to eliminate noise points, (3) discontinuity segmentation using density-ratio based method, and discontinuity plane fitting using the random sample consensus (RANSAC) algorithm, (4) persistence and spacing calculation using the theory of analytic geometry. The method is applied to two case studies (i.e. rock slopes) and compared with the results from previous studies and from manual survey. It is concluded that the proposed method is reliable and yields a great accuracy for automatic identification of discontinuities in rock masses.