施工技术(中英文)2024,Vol.53Issue(20) :42-50.DOI:10.7672/sgjs2024200042

基于机器视觉算法的隧道岩体质量智能评估方法

Intelligent Evaluation Method of Tunnel Rock Mass Quality Based on Machine Vision Algorithm

唐德密 邓乃夫 李庆文
施工技术(中英文)2024,Vol.53Issue(20) :42-50.DOI:10.7672/sgjs2024200042

基于机器视觉算法的隧道岩体质量智能评估方法

Intelligent Evaluation Method of Tunnel Rock Mass Quality Based on Machine Vision Algorithm

唐德密 1邓乃夫 2李庆文2
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作者信息

  • 1. 中交一公局集团有限公司,北京 102200
  • 2. 北京科技大学土木与资源工程学院,北京 100083
  • 折叠

摘要

路罗隧道1号横洞隧址区为第四系全新统崩积碎石土,节理密集,岩石破碎,地质条件较差.针对该工况,基于岩体结构面三维点云模型,对结构面产状、节理组数、粗糙度和块体体积的统计分析方法展开研究,进一步完善岩体结构面智能表征在三维指标中的应用.基于机器视觉统计的6个岩体结构面特征指标,快速获取隧道围岩分级结果.结果表明,所选隧道横洞开挖面围岩质量一般,整体属于Ⅲ级围岩,与地质勘察结果相符,验证了基于机器视觉算法的岩体质量评估方法的可靠性.

Abstract

The site area of No.1 cross-hole of Luluo Tunnel is colluvial rubble soil of Quaternary Holocene series,with dense joints,broken rocks and poor geological conditions.In view of this condition,based on the constructed 3D point cloud model of rock mass structure surface,the statistical analysis method of structural plan occurrence,number of joint groups,roughness and block size is studied,and the application of intelligent characterization of rock mass structure surface in 3D indexes is further improved.The classification results of tunnel surrounding rock are quickly obtained based on the six major structure surface characteristics of rock mass based on machine vision statistics.The results show that the quality of the surrounding rock of the selected tunnel transverse tunnel excavation face is average,and the whole is in level Ⅲ,which is consistent with the geological exploration results,which verifies the reliability of the rock mass quality assessment method based on machine vision algorithm.

关键词

隧道/围岩/质量评价/机器视觉算法/三维点云模型/特征指标

Key words

tunnels/surrounding rocks/quality evaluation/machine vision algorithm/3D point cloud model/indicator characteristics

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出版年

2024
施工技术(中英文)
亚太建设科技信息研究院 中国建筑设计研究院 中国建筑工程总公司 中国土木工程学会

施工技术(中英文)

影响因子:1.244
ISSN:2097-0897
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