4.6 Article

Discontinuity Recognition and Information Extraction of High and Steep Cliff Rock Mass Based on Multi-Source Data Fusion

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 21, Pages -

Publisher

MDPI
DOI: 10.3390/app122111258

Keywords

rock discontinuities; multi-source point cloud; point cloud fusion; automated extraction

Funding

  1. National Natural Science Foundation of China [41861054]

Ask authors/readers for more resources

This article introduces an intelligent identification method for rock discontinuities based on the multi-source fusion of point clouds, combining 3D laser scanning and UAV photogrammetry technology. It effectively solves the problem of data acquisition in complex geological conditions and provides a feasible solution.
It is fundamental to acquire accurate point cloud information on rock discontinuities efficiently and comprehensively when evaluating the stability of rock masses. Taking a high and steep cliff as an example, we combined 3D laser scanning and UAV photogrammetry technology to collect rock data, and proposed an intelligent identification method for rock discontinuities based on the multi-source fusion of point clouds. First, the 3D-laser-collected point cloud data were used as the basis to fuse with the UAV-photogrammetry-collected data, and the unified coordinate system and improved ICP algorithm were used to obtain the complete 3D point cloud in the study area. Secondly, we used neighborhood information entropy to achieve adaptive neighborhood-scale selection and to obtain the optimal neighborhood radius for the KNN search, to effectively calculate the point cloud normal vector and rock mass orientation information. Finally, the KDE algorithm and DBSCAN algorithm were combined for rock discontinuity clustering to achieve intelligent identification and information extraction of the rock structural plane. The clustering results were imported into the DSE program developed based on Matlab to calculate the discontinuity spacing and continuity of the rock mass structure, and to efficiently obtain the parameters of rock mass occurrence. The research results showed that this method can effectively solve the problem of incomplete-data-acquisition ground 3D laser scanning in complex geological conditions, and UAV photogrammetry prone to blurred images in depressed areas. When the extraction results were compared with the field-measured rock occurrence, the average dip angle error was about 2 degrees, the average dip direction error was 1 degrees, and the recognition results met the accuracy requirements. The research results provide a feasible scheme for the identification and extraction of discontinuities of high and steep rock masses.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available