东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (8): 1167-1173.DOI: 10.12068/j.issn.1005-3026.2020.08.017

• 资源与土木工程 • 上一篇    下一篇

地下工程岩体节理迹长统计下限值的确定方法

吴超， 李元辉， 徐帅， 戴星航   

  1. (东北大学 资源与土木工程学院， 辽宁 沈阳110819)
  • 收稿日期:2019-09-08 修回日期:2019-09-08 出版日期:2020-08-15 发布日期:2020-08-28
  • 通讯作者: 吴超
  • 作者简介:吴超(1993-)，男，河北邢台人，东北大学博士研究生; 李元辉(1968-)，男，山东莱州人，东北大学教授，博士生导师.
  • 基金资助:
    国家重点研发计划项目(2018YFC0604601)； 中央高校基本科研业务费专项资金资助项目(N182608003，N180115010)； 东北大学深部金属矿山安全开采教育部重点实验室开放基金项目(2017SMDM-KF-A01).

Method for Determining the Lower Limit of Statistical Joints Trace Length in Underground Engineering Rock Mass

WU Chao， LI Yuan-hui， XU Shuai， DAI Xing-hang   

  1. School of Resources & Civil Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2019-09-08 Revised:2019-09-08 Online:2020-08-15 Published:2020-08-28
  • Contact: LI Yuan-hui
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摘要： 以山东某金矿为工程依托，以实际获得的岩体节理信息为样本，借助聚类分析方法及其指标，采用全面实验法，开展地下工程岩体节理迹长统计下限值的确定方法研究.从节理迹长统计下限值的定义及特征入手，借助DBI指标(Davies-Bouldin index， DBI)实现优势节理组的划分与最佳优势节理分组方案的确定.取离散性系数k是否大于或等于20作为判别节理组能否作为优势节理组的条件，采用离散性系数k及其概率分布指标n综合分析确定岩体区域节理迹长统计下限值，构建在不同岩体条件下确定节理迹长统计下限值的方法，旨在剔除随机节理，优化节理样本数据，精确获取岩体节理空间分布特征.

关键词: 地下工程岩体, 节理迹长, 统计下限值, 随机节理, 聚类评价指标, 节理数据优化

Abstract: Taking the actual rock mass joint information from a gold mine in Shandong Province as samples， a method is studied to determine the lower limit of the statistical joints trace length in underground engineering rock mass by cluster analysis and its evaluating indicators with the full-scale test. Starting from the definition and characteristics of the lower limit， the DBI (Davies-Bould in index) is used to divide dominant joint sets and determine the best setting scheme of dominant joints. The joint set can become the dominant one if the discrete coefficient k is greater than 20， and the discrete coefficient k with its probability distribution index n together is used to analyze and determine the lower limit value. Furthermore， the method of determining the lower limit value of the statistical joints trace length under different rock mass conditions is developed in order to eliminate random joints and optimize the sample data of rock mass joints， thus getting spatial distribution characteristics of rock mass joints.

Key words: underground engineering rock mass, joint trace length, statistical lower limit, random joint, cluster evaluation index, joint data optimization

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