| 引用本文: | 杨泽,李保天,宋盛渊,秦龙,刘殿泽,黄迪.基于无人机点云与改进RS表征法的结构面粗糙度定量分析[J].哈尔滨工业大学学报,2023,55(11):72.DOI:10.11918/202303075 |
| YANG Ze,LI Baotian,SONG Shengyuan,QIN Long,LIU Dianze,HUANG Di.Quantitative analysis of structural surface roughness based on UAV point cloud and improved RS characterization method[J].Journal of Harbin Institute of Technology,2023,55(11):72.DOI:10.11918/202303075 |
|
| 摘要: |
| 为研究采样尺寸、采样间距对高陡斜坡岩体结构面粗糙度评价结果的影响,选取藏东南某铁路察达车站工点左岸高陡岩质斜坡为研究区,提出采用无人机多角度贴近摄影测量技术获取毫米级点云数据以建立研究区斜坡岩体高精度三维模型,并从中选取典型区域裁剪出带有点云信息的27条面状结构面,使用Delaunay三角化原理对结构面进行网格化重建。基于此,提出一种采用点云拟合平面代替RS表征法中垂直投影平面的新方法,并研究结构面粗糙度在不同采样尺寸、采样间距下的变化规律,结果表明:不同三角剖分方式对RS表征值影响较小；结构面粗糙度具有尺寸效应与间距效应,其粗糙度表征值随结构面尺寸的增加逐渐趋于稳定,随结构面采样间距增大逐渐减小；部分存在尺寸效应的结构面存在“假有效采样尺寸”与“真有效采样尺寸”。在进行粗糙度评价时应确保所得有效采样尺寸为“真有效采样尺寸”。 |
| 关键词: 多角度贴近摄影 结构面粗糙度 改进RS表征法 尺寸效应 间距效应 三角剖分 |
| DOI：10.11918/202303075 |
| 分类号:TU45 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(9,7)；吉林省自然科学基金(20230101088JC)；吉林省教育厅科学研究项目(JJKH20231182KJ) |
|
| Quantitative analysis of structural surface roughness based on UAV point cloud and improved RS characterization method |
|
YANG Ze1,LI Baotian2,SONG Shengyuan1,QIN Long3,LIU Dianze1,HUANG Di1
|
|
(1.College of Construction Engineering, Jilin University, Changchun 130026, China; 2.The Sixth Engineering Co., Ltd. of China Railway Third Engineering Group, Jinzhong 030600,Shanxi, China; 3.Guizhou Transportation Planning, Survey and Design Institute Co., Ltd., Guiyang 550081,China)
|
| Abstract: |
| In order to study the impact of sampling size and spacing on the roughness evaluation results of rock mass structural planes on high and steep slopes, a high and steep rock slope on the left bank of a certain railway station in southeastern Tibet was selected as the research area, and multi-angle approach photogrammetry technology of UAV was proposed to acquire millimeter-level point cloud data to establish a high-precision three-dimensional model of rock mass on slopes in the study area. 27 planar structural planes with point cloud information were clipped from the typical region, and the Delaunay triangulation principle was used to reconstruct the structural plane meshing. Based on this, a new method was proposed to replace the vertical projection plane in the RS characterization method with point cloud fitting plane, and the variation law of structural surface roughness under different sampling sizes and sampling spacing was studied. The results showed that: different triangulation methods have little impact on RS characterization values. The structural surface roughness has the size effect and the spacing effect, and the characteristic value of the roughness tends to be stable with the increase of the structural surface size, and decreases with the increase of the sampling spacing of the structural surface. Some structural planes with size effect have “false effective sampling size” and “true effective sampling size”. Therefore, the effective sampling size obtained should be “true effective sampling size” when conducting roughness evaluation. |
| Key words: multi angle close to photography roughness of structural surface improve RS characterization method size effect spacing effect triangulation |
