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金属矿山 ›› 2024, Vol. 53 ›› Issue (2): 219-.

• 机电与自动化 • 上一篇    下一篇

基于改进模糊算法的节理分组软件开发

郭怡宁1 刘铁新1 董自岩1 郑洪春2 韩 鞠3 詹必雄3   

  1. (1. 大连海事大学交通运输工程学院,辽宁 大连 116026;2. 中国长江三峡集团有限公司,北京 100382; 3. 中建一局集团建设发展有限公司,北京 100102
  • 出版日期:2024-02-15 发布日期:2024-04-03

Software Development for Grouping Joints Based on Improved Fuzzy Algorithm

GUO Yining1 LIU Tiexin1 DONG Ziyan1 ZHENG Hongchun2 HAN Ju3 ZHAN Bixiong3   

  1. 1. College of Transportation Engineering,Dalian Maritime University,Dalian 116026,China;2. China Three Gorges Corporation, Beijing 100382,China;3. China Construction First Group Construction & Development Co. ,Ltd. ,Beijing 100102,China
  • Online:2024-02-15 Published:2024-04-03

摘要: 节理广泛存在于岩体中,其发育情况影响着岩体的稳定及渗流特性。由于节理数量众多,目前对其研 究时需进行分组处理。传统的分组方法如依靠玫瑰图、极点等密度图等,无法确定每组节理的具体数据,同时对离散 点的分组效果有限。当下使用机器学习的聚类算法也存在选择的聚类数影响分组效果的不足。鉴于此,在MATLAB 平台上开发了基于改进模糊聚类算法的节理产状聚类程序(JOCP)。JOCP 考虑节理的倾向倾角,使用基于聚拢度的 模糊聚类算法进行分组,将结果使用Xie-beni 指数判断优劣性,最终生成节理分组的最优解。JOCP 以原始坐标数据 及目标聚类数为输入,以节理产状数据、聚类中心、聚类结果分布图以及有效性指标为输出。将程序用于大连某边坡 千条节理数据的分析中,结果证明程序可提高分组确定性,达到分组效果客观准确的目的。此程序可为地质勘探,灾 害预测等领域提供技术支持。

关键词: 岩体 节理分组 聚类分析 程序开发 改进模糊算法

Abstract: Joints are widely present in rock masses,and their development affects the stability and seepage characteristics of the rock masses. Due to the large number of joints,grouping is currently required for their study. Traditional grouping methods, such as relying on rose diagrams and density maps such as poles,cannot determine the specific data of each group of joints and have limited effect on grouping of discrete points. The contemporary clustering algorithm using machine learning also suffers from the deficiency that the number of clusters selected affects the grouping effect. In view of this,a joints' orientation clustering program (JOCP) based on an improved fuzzy clustering algorithm was developed on the MATLAB platform. JOCP takes the original coordinate data and the target number of clusters as the input,and the nodal yield data,the cluster centers,the distribution of clustering results and the validity index as the output. The program is used in the analysis of a thousand slope nodal data in Dalian,and the results prove that the program can improve the grouping certainty and achieve the objective and accurate grouping effect. This program can provide technical support for geological exploration,disaster prediction and other fields.

Key words: rock mass,nodal grouping,cluster analysis,program development,improved fuzzy algorithm