Quantitative characterization method of point cloud distribution in tunnel for optimizing TLS scanning plan

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Tunnelling and Underground Space Technology Pub Date : 2024-11-22 DOI:10.1016/j.tust.2024.106226

Haitong Sui , Kensuke Asaba , Kazuo Sakai , Syuntaro Miyanaga , Ying Cui

{"title":"Quantitative characterization method of point cloud distribution in tunnel for optimizing TLS scanning plan","authors":"Haitong Sui , Kensuke Asaba , Kazuo Sakai , Syuntaro Miyanaga , Ying Cui","doi":"10.1016/j.tust.2024.106226","DOIUrl":null,"url":null,"abstract":"<div><div>A novel method for quantitatively describing the distribution of point clouds in tunnels is introduced to optimize tunnel scanning schemes. The method uses point cloud spacing and thickness to represent the density and unevenness of the point cloud, respectively. Point cloud spacing is categorized into point spacing and ring spacing based on the scanning trajectory, and these metrics are calculated using coordinates from a regularly distributed point cloud. Point cloud thickness is derived by combining the measurement error range in the laser incidence direction with the laser incidence angle. The above calculation method has been validated through tunnel field tests. The quantitative characterization method evaluates the effects of resolution, station spacing, and linearity error on point cloud spacing and thickness. It helps determine the necessary resolution, station spacing, and TLS scanner specifications to ensure that point cloud spacing and thickness meet the requirements for tunnel health assessment. By addressing the lack of comprehensive quantitative consideration of point cloud distribution in selecting scanning parameters, this method provides a robust framework for optimizing scanning schemes, ensuring accurate and reliable point cloud data for tunnel inspection.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"156 ","pages":"Article 106226"},"PeriodicalIF":6.7000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tunnelling and Underground Space Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0886779824006448","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

A novel method for quantitatively describing the distribution of point clouds in tunnels is introduced to optimize tunnel scanning schemes. The method uses point cloud spacing and thickness to represent the density and unevenness of the point cloud, respectively. Point cloud spacing is categorized into point spacing and ring spacing based on the scanning trajectory, and these metrics are calculated using coordinates from a regularly distributed point cloud. Point cloud thickness is derived by combining the measurement error range in the laser incidence direction with the laser incidence angle. The above calculation method has been validated through tunnel field tests. The quantitative characterization method evaluates the effects of resolution, station spacing, and linearity error on point cloud spacing and thickness. It helps determine the necessary resolution, station spacing, and TLS scanner specifications to ensure that point cloud spacing and thickness meet the requirements for tunnel health assessment. By addressing the lack of comprehensive quantitative consideration of point cloud distribution in selecting scanning parameters, this method provides a robust framework for optimizing scanning schemes, ensuring accurate and reliable point cloud data for tunnel inspection.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

隧道内点云分布的定量表征方法，用于优化 TLS 扫描计划

本文介绍了一种定量描述隧道内点云分布的新方法，用于优化隧道扫描方案。该方法使用点云间距和厚度分别表示点云的密度和不均匀性。根据扫描轨迹，点云间距可分为点间距和环间距，这些指标都是利用规则分布的点云坐标计算得出的。点云厚度由激光入射方向上的测量误差范围与激光入射角相结合得出。上述计算方法已通过隧道现场测试得到验证。定量表征方法评估了分辨率、站点间距和线性误差对点云间距和厚度的影响。它有助于确定必要的分辨率、站点间距和 TLS 扫描仪规格，以确保点云间距和厚度满足隧道健康评估的要求。通过解决在选择扫描参数时缺乏对点云分布的全面定量考虑的问题，该方法为优化扫描方案提供了一个稳健的框架，确保隧道检测所需的点云数据准确可靠。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Tunnelling and Underground Space Technology 工程技术-工程：土木

CiteScore

11.90

自引率

18.80%

发文量

454

审稿时长

10.8 months

期刊介绍： Tunnelling and Underground Space Technology is an international journal which publishes authoritative articles encompassing the development of innovative uses of underground space and the results of high quality research into improved, more cost-effective techniques for the planning, geo-investigation, design, construction, operation and maintenance of underground and earth-sheltered structures. The journal provides an effective vehicle for the improved worldwide exchange of information on developments in underground technology - and the experience gained from its use - and is strongly committed to publishing papers on the interdisciplinary aspects of creating, planning, and regulating underground space.