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An efficient method for extracting and clustering rock mass discontinuities from 3D point clouds

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Abstract

A rock mass discontinuity is a fundamental element of a rock mass structure that regulates its mechanical and hydrogeological properties and has significant engineering implications. In this research, we offer a method for extracting discontinuities and performing efficient clustering analysis based on 3D point cloud data for rock outcrops. First, the K-d tree approach is utilized to organize the point cloud data so that the normal vector and curvature can be calculated quickly. Discontinuities are then extracted using a multirule region growing algorithm, and the dip directions and dip angles of the discontinuities are calculated. Then, the improved farthest point sampling algorithm and the elbow method are used to optimize the K-means algorithm and finally automatically determine the main discontinuity set and average direction for the rock mass. The approach is tested on two real cases and compared to the methods of international researchers, and it is discovered that the method proposed in this work shows good accuracy, with an average deviation of less than 5° from the dip direction and dip angle. Comparative tests with many point cloud data sets show that this new method can be used to extract discontinuities from massive-scale rock outcrop point cloud data and perform cluster analysis with high efficiency. The proposed method gives geologists and geological engineers a new tool for quickly and efficiently understanding rock outcrop discontinuities.

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Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research was funded by the National Natural Science Foundation of China (Grant No. 41977252), the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (Grant No. SKLGP2020Z001) and the Scientific Research Project of Xinhua Hydropower Co., Ltd (XHWY-2020-DL-KY01). The authors gratefully acknowledge the RockBench Repository for providing the point cloud data. Finally, we thank the anonymous reviewers and the editor for their constructive feedback and suggestions that encouraged us to improve the quality of this paper.

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Authors and Affiliations

  1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China

    Xiaoyu Yi, Wenkai Feng, Yunpeng Hu & Yongjian Zhou

  2. College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, 610059, China

    Xiaoyu Yi, Wenkai Feng, Yunpeng Hu & Yongjian Zhou

  3. College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China

    Di Wang & Ronghao Yang

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  1. Xiaoyu Yi
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Yi, X., Feng, W., Wang, D. et al. An efficient method for extracting and clustering rock mass discontinuities from 3D point clouds. Acta Geotech. 18, 3485–3503 (2023). https://doi.org/10.1007/s11440-023-01803-w

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