首页|地面激光扫描点云与无人机影像点云融合应用

地面激光扫描点云与无人机影像点云融合应用

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  • 国家科技期刊平台
  • NETL
  • NSTL
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通过建立高精度的桥梁三维点云模型,检查桥梁病害情况并拟合绘制出桥梁线形.首先以无人机近景摄影、环绕飞行、井字飞行获取某双线特大桥梁主体与细部纹理数据,然后将不同航线采集的数据在Context Capture软件里面进行三维重建,将桥梁主体与细部影像融合生成完整桥梁点云1.运用Trimble SX12仪器完成对桥梁一体化扫描,获得完整桥梁点云2.提出基于双向KD-tree优化的ICP(Iterative Closest Point)算法对无人机航摄桥梁点云1与地面激光扫描桥梁点云数据2进行配准融合,加密后的桥梁点云用于建立运营铁路双线特大桥精细化三维实景建模.提出基于KD-tree的PCA(Principal Component Analysis)算法完整提取出桥梁吊索点云,运用最小二乘法拟合出桥梁拱轴线线形、RANSAC算法拟合出桥面线形.通过与单一无人机、单一地面激光扫描精度及完整性对比分析,以验证融合建模的有效性.研究结果表明:融合建模的模型水平精度1.71 cm、垂直方向精度1.25 cm,较单一无人机建模精度在水平与竖直方向分别提升16.59%与20.89%;融合建模的完整性为98.17%,纹理效果更加真实,并检查出桥墩存在蜂窝麻面、渗水等病害,拱肋存在涂装锈蚀、破裂等病害.该研究可为桥梁三维点云模型应用研究提供思路参考,具有较好的应用前景.
Integration application of terrestrial laser scanner point clouds and unmanned aerial vehicle image point clouds
This study was to establish a high-precision 3D point cloud model of bridges,inspect bridge health conditions,and fit and draw the bridge geometry.Firstly,close-range photography,orbiting flights,and grid flights with drones were employed to acquire detailed texture data of a certain large twin-line bridge.Subsequently,the data collected from different flight routes were processed in context capture software for 3D reconstruction,merging the main and detailed images to generate a comprehensive bridge point cloud 1.The Trimble SX12 instrument was used for integrated scanning of the entire bridge,obtaining a complete bridge point cloud 2.An iterative closest Point(ICP)algorithm based on a bi-directional KD-tree optimization was proposed to register and merge the drone-surveyed bridge point cloud 1 with the terrestrial laser-scanned bridge point cloud data 2.The encrypted bridge point cloud was then used to establish a refined 3D realistic model of the operational twin-line bridge for railways.Additionally,a Principal Component Analysis(PCA)algorithm based on KD-tree was introduced to extract the suspension point cloud of the bridge.The least squares method was applied to fit the bridge arch axis alignment,and the RANSAC algorithm was used to fit the bridge deck profile.Validation of the effectiveness of the fusion modeling was conducted through comparative analysis with the accuracy and completeness of single unmanned aerial vehicle(UAV)and terrestrial laser scanning.The results indicate that the horizontal accuracy of the fusion model is 1.71 cm.The vertical accuracy is 1.25 cm.This represents an improvement of 16.59%in the horizontal direction and 20.89%in the vertical direction compared to the accuracy of the single UAV modeling.The completeness of the fusion model is 98.17%,providing a more realistic texture effect.The model can identify bridge pier conditions,such as honeycomb surface and water seepage,as well as arch rib issues like painted rust and cracks.This study can provide valuable insights and references for the application research of 3D point cloud models for bridges,demonstrating promising prospects.

operating railway bridge alignmentoblique photogrammetric surveyterrestrial laser scanningpoint cloud data fusionbridge defect detection

彭仪普、李剑、邹魁、汤致远、李子超、韩衍群

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中南大学 土木工程学院,湖南 长沙 410075

湖南中大设计院有限公司,湖南 长沙 410075

运营铁路桥梁线形 倾斜摄影测量 地面激光扫描 点云数据融合 桥梁病害检测

湖南省自然科学基金资助项目国家自然科学基金资助项目国家自然科学基金资助项目中国中铁股份有限公司科技研究开发计划

2019JJ4038552078499523784242020-重点-09

2024

10.19713/j.cnki.43-1423/u.T20231517

铁道科学与工程学报
中南大学 中国铁道学会

铁道科学与工程学报

CSTPCD北大核心EI
影响因子：0.837
ISSN：1672-7029
年,卷(期)：2024.21(7)
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