基于均值漂移聚类算法的岩体结构面产状优势分组  

Clustering of Discontinuity Orientation Based on Mean Shift Clustering Algorithm

作　　者：彭是焱 周鑫 申壮 徐千博 PENG Shi-yan;ZHOU Xin;SHEN Zhuang;XU Qian-bo(Hohai College,Chongqing Jiaotong University,Chongqing 400074,China;Northwest Integrated Survey and Design Research Institute,Xi'an 710003,China;Shanxi Survey and Design Institute Co,Ltd.,Taiyuan 030013,China)

机构地区：[1]重庆交通大学河海学院,重庆400074 [2]西北综合勘察设计研究院,西安710003 [3]山西省勘察设计研究院有限公司,太原030013

出　　处：《科学技术与工程》2025年第4期1392-1399,共8页Science Technology and Engineering

基　　金：重庆市自然科学基金面上项目(cstc2021jcyj-msxmX0869);重庆市教委科学技术研究项目(KJQN202200709);重庆市研究生联合培养基地建设项目(JDLHPYJD2022004)。

摘　　要：岩体结构面产状的优势分组对于揭示不同类型结构面的分布规律和特征具有重要意义。传统的结构面极点密度图分组方法通常较为依赖地质经验,缺乏一定客观性,为此,引入均值漂移聚类算法开展岩体结构面产状优势分组研究。首先,人工生成不同离散程度岩体结构面产状数据。随后,将生成的产状数据转换为三维空间中的坐标,并以单位法向量的夹角正弦值γ作为相似性度量标准。接下来采用均值漂移算法对度量的数据集进行聚类分析,通过与传统的极点密度图法和K均值聚类算法进行比较,有效性检验指标和聚类错误识别率与K均值聚类算法接近一致。最后以重庆三功矿岩质边坡为工程实例,通过野外采集到的结构面数据验证了新方法的合理性及有效性。结果表明:该方法聚类效果优于传统的极点图分组方法和K均值聚类算法,聚类结果客观合理,对近水平产状也有良好的聚类效果。The clustering of discontinuity orientation is crucial for revealing the distribution and characteristics of various types of discontinuities.Conventional clustering methods based on discontinuity pole density maps often rely on geological experience and lack objectivity.Therefore,the mean shift clustering algorithm was introduced to study the clustering of discontinuity orientation.Initially,discontinuity orientations with different degrees of dispersion were manually generated.Subsequently,these orientation data were converted into coordinates in 3-D space,and the sinusoidal valueγof the unit normal vector was employed as the similarity measure.The mean shift algorithm was then used to perform clustering analysis on the measured data set.Compared with the conventional pole density map method and the K-means clustering algorithm,the validity test index and clustering error recognition rate were close to those of the K-means clustering algorithm.Finally,taking the Chongqing Sangong rock slope as an example,the rationality and effectiveness of the new method were verified by field data.The results show that the performance of the proposed method surpasses that of the conventional discontinuity pole density map and K-means clustering algorithm.The clustering results are objective and reasonable,and the clustering effect for near-horizontal discontinuities is also satisfactory.

关 键 词：岩体 结构面产状 优势分组 均值漂移聚类算法 

分 类 号：TD679[矿业工程—矿山机电]