.png){kind=icon}
返回
LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization
.png){kind=icon}
OA
AI
DOI：10.3390/s20247117.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on the continuous load for a long time. Therefore, in this study, we propose a method for estimating the vertical displacement of structures using light detection and ranging, which enables non-contact measurement. The point cloud acquired through laser scanning was rearranged into a three-dimensional space, and internal nodes were created by continuously dividing the space. The generated node has its own location information, and the vertical displacement value was calculated by searching for the node where the deformation occurred. The performance of the proposed displacement estimation technique was verified through static loading experiments, and the octree space partitioning method is expected to be applied and utilized in structural health monitoring.
Keyword:
light detection and ranging (LiDAR)
terrestrial laser scanning (TLS)
deflection
octree space partitioning (OSP)
structural health monitoring (SHM)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Comparison of Non-Destructive Techniques for Technological Bridge Deflection Testing.png)
MATERIALSOAAI
MATERIALSIF3.2
OAAI分享收藏Computer Vision-Based Bridge Displacement Measurements Using Rotation-Invariant Image Processing TechniqueSUSTAINABILITYOAAI
SUSTAINABILITYIF3.3
OAAI分享收藏Automated processing of large point clouds for structural health monitoring of masonry arch bridges
PREAI
分享收藏OctoMap: an efficient probabilistic 3D mapping framework based on octreesOctoMap: 一种基于八叉树的高效概率三维映射框架AUTONOMOUS ROBOTSOAAI
AUTONOMOUS ROBOTSIF4.3
OAAI分享收藏
查看更多内容