东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (8): 1161-1166.DOI: 10.12068/j.issn.1005-3026.2020.08.016

• 资源与土木工程 • 上一篇    下一篇

基于三维点云的岩体结构面自动分类与参数计算

郭甲腾, 张紫瑞, 毛亚纯, 刘善军   

  1. (东北大学 资源与土木工程学院, 辽宁 沈阳110819)
  • 收稿日期:2019-11-18 修回日期:2019-11-18 出版日期:2020-08-15 发布日期:2020-08-28
  • 通讯作者: 郭甲腾
  • 作者简介:郭甲腾(1980-),男,安徽桐城人,东北大学副教授; 刘善军(1965-),男,河北涿鹿人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(41671404,51874069,51674063); 中国地质调查局智能地质调查支撑平台建设项目(DD20190416); 中央高校基本科研业务费专项资金资助项目(N180101028,N170104019).

Automatic Discontinuity Classification and Parameter Calculation from Rock Mass 3D Point Cloud

GUO Jia-teng, ZHANG Zi-rui, MAO Ya-chun, LIU Shan-jun   

  1. School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2019-11-18 Revised:2019-11-18 Online:2020-08-15 Published:2020-08-28
  • Contact: GUO Jia-teng
  • About author:-
  • Supported by:
    -

摘要: 结构面间距是岩体稳定性和力学特性分析中的一个重要参数,在岩石力学、采矿工程、边坡监测等领域的数值计算中广泛应用.本文以岩体边坡露头为研究对象,基于非接触测量获得的三维点云数据,提出一种基于密度聚类的结构面细化分类方法;在结构面粗略分组提取的基础上,通过投影变换、散乱点拟合等算法,求得结构面间距和岩体体积节理数.设计开发了结构面细化分类及间距等参数计算与分析原型系统,实际案例分析表明,本文方法可有效实现结构面的自动细化分类,并能够计算出间距等相关参数,可为岩体质量分级和岩体稳定性分析等提供方法支撑.

关键词: 三维点云, 结构面, 细化分类, DBSCAN聚类, 结构面间距

Abstract: The structural plane spacing is an important parameter in rock mass stability and mechanical properties analysis. It is widely used in the numerical computation of rock mechanics, mining engineering, slope monitoring and other fields. Based on the three-dimensional rock mass slope point cloud data acquired by non-contacting surveying method, this paper proposes a structural surface refinement classification method using density clustering. Projection transformation and scattered point fitting are used after a previous step of general discontinuity classification. The refinement classification is used to compute the structural plane spacing and the rock mass joint number. A prototype system for parameter calculation and analysis of structural surface refinement classification and spacing was designed and developed. The real case experiment and analysis show that the proposed method performs effectively in realizing the automatic refinement classification of structural planes, and in calculating the related parameters such as structural surface spacing, which may provide further support for rock mass quality classification and rock mass stability analysis.

Key words: 3D point cloud, structural surface, refinement classification, DBSCAN clustering, structural plane spacing

中图分类号: