Scholarlink

<p>The natural discontinuities present within the surrounding rock significantly influence the integrity of the rock mass, particularly in underground rock engineering, where these discontinuities serve as critical geological structures that can lead to tunnel destabilization and facilitate groundwater movement. This paper systematically presents a methodology for the fine identification of complex discontinuities in surrounding rock using close-range photogrammetry. Firstly, the photogrammetry-based method tailored for various rock engineering scenarios and the 3D digital reconstruction technology specifically devised for surrounding rock images are presented. Building upon this foundation, we propose a human–machine interaction method aimed at the meticulous identification and extraction of discontinuities in surrounding rock. This method comprises several key steps: (1) enhancement of the Laplace smoothing algorithm to eliminate noise of non-rock structures; (2) segmentation and detection of discontinuities; (3) labeling and assignment of key feature points associated with these discontinuities; and (4) identification and fitting of the identified discontinuities. To investigate the performance of the proposed methods, we selected two representative cases: a section of an underground excavation tunnel and a surface granite outcrop located at China’s first high-level waste geological disposal site. The results demonstrate that employing high-resolution images combined with high-precision point clouds effectively captures intricate texture details associated with discontinuities. The proposed approach exhibits exceptional performance in the fine identification and extraction of complex discontinuities, with interpreted discontinuity orientations aligning well with in-site geological compass measurements. In comparison to the widely utilized state-of-the-art Discontinuity Set Extractor (DSE), the method presented herein achieves significant improvements in both identification efficiency and result visualization. This advancement contributes to addressing challenges associated with fine identification of complex linearly exposed discontinuities. Overall, this study offers a convenient and cost-effective solution for accurately identifying complex exposed planar and linear discontinuities encountered in rock engineering applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Human-machine interactive refined identification of complex rock discontinuities using photogrammetric techniques: Case studies from a candidate HLW repository site in China

  • 期刊论文

  • 发表日期：

    2025年5月15日

查看全文
  • Yang Yang,
  • Wentao Xu,
  • Xiaozhao Li,
  • Xiaodong Ma,
  • Chao-Sheng Tang

摘要

The natural discontinuities present within the surrounding rock significantly influence the integrity of the rock mass, particularly in underground rock engineering, where these discontinuities serve as critical geological structures that can lead to tunnel destabilization and facilitate groundwater movement. This paper systematically presents a methodology for the fine identification of complex discontinuities in surrounding rock using close-range photogrammetry. Firstly, the photogrammetry-based method tailored for various rock engineering scenarios and the 3D digital reconstruction technology specifically devised for surrounding rock images are presented. Building upon this foundation, we propose a human–machine interaction method aimed at the meticulous identification and extraction of discontinuities in surrounding rock. This method comprises several key steps: (1) enhancement of the Laplace smoothing algorithm to eliminate noise of non-rock structures; (2) segmentation and detection of discontinuities; (3) labeling and assignment of key feature points associated with these discontinuities; and (4) identification and fitting of the identified discontinuities. To investigate the performance of the proposed methods, we selected two representative cases: a section of an underground excavation tunnel and a surface granite outcrop located at China’s first high-level waste geological disposal site. The results demonstrate that employing high-resolution images combined with high-precision point clouds effectively captures intricate texture details associated with discontinuities. The proposed approach exhibits exceptional performance in the fine identification and extraction of complex discontinuities, with interpreted discontinuity orientations aligning well with in-site geological compass measurements. In comparison to the widely utilized state-of-the-art Discontinuity Set Extractor (DSE), the method presented herein achieves significant improvements in both identification efficiency and result visualization. This advancement contributes to addressing challenges associated with fine identification of complex linearly exposed discontinuities. Overall, this study offers a convenient and cost-effective solution for accurately identifying complex exposed planar and linear discontinuities encountered in rock engineering applications.