| 基于点云数据的大型复杂钢拱桥智能虚拟预拼装方法 |
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| 引用本文： | 周绪红,刘界鹏,程国忠,李东声,黄涛,梁俊海,刘虎,刘雨鑫.基于点云数据的大型复杂钢拱桥智能虚拟预拼装方法[J].中国公路学报,2021,34(11):1-9. |
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| 作者姓名： | 周绪红 刘界鹏 程国忠 李东声 黄涛 梁俊海 刘虎 刘雨鑫 |
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| 作者单位： | 1. 重庆大学 山地城镇建设与新技术教育部重点实验室, 重庆 400045;2. 重庆大学 土木工程学院, 重庆 400045;3. 深圳大学 土木与交通工程学院, 广东 深圳 518061;4. 中建科工集团有限公司重庆分公司, 重庆 400000 |
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| 基金项目： | 国家自然科学基金项目（U20A20312，52008055）；中央高校基本科研业务费专项资金项目（2021CDJQY-016） |
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| 摘 要： | 基于点云数据的虚拟预拼装主要包括点云数据采集、拼接控制点提取和拼接控制点匹配。针对完整点云数据存在采集困难、处理成本高等问题，提出用局部点云数据代替完整点云数据进行虚拟预拼装的策略；针对目前拼接控制点提取存在依赖专用软件、效率低且主观性大等问题，基于随机采样一致性、霍夫变换等经典算法和图像处理技术提出大型复杂构件横截面和侧面点云数据的拼接控制点智能提取方法；针对拼接控制点对应关系需人工设定的问题，基于超四点快速鲁棒匹配算法、迭代最近邻算法和广义普氏算法提出拼接控制点智能匹配方法。以大型复杂钢拱桥为例，采用所提的方法对拱肋牛腿-拱间横梁节段和拱肋节段-拱肋节段进行智能虚拟预拼装。工程应用结果表明：所提出的智能虚拟预拼装方法不依赖专用软件、效率高、自动化程度好。研究成果可为钢桥施工质量和安装效率的提升提供理论和算法支撑。
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| 关 键 词： | 桥梁工程 大型复杂钢桥 智能虚拟预拼装 点云数据 智能算法 |
| 收稿时间： | 2021-02-01 |
Intelligent Virtual Trial Assembly of Large and Complex Steel Arch Bridges Based on Point Cloud Data |
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| ZHOU Xu-hong,LIU Jie-peng,CHENG Guo-zhong,LI Dong-sheng,HUANG Tao,LIANG Jun-hai,LIU Hu,LIU Yu-xin.Intelligent Virtual Trial Assembly of Large and Complex Steel Arch Bridges Based on Point Cloud Data[J].China Journal of Highway and Transport,2021,34(11):1-9. |
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| Authors: | ZHOU Xu-hong LIU Jie-peng CHENG Guo-zhong LI Dong-sheng HUANG Tao LIANG Jun-hai LIU Hu LIU Yu-xin |
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| Affiliation: | 1. Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing 400045, China;2. School of Civil Engineering, Chongqing University, Chongqing 400045, China;3. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, Guangdong, China;4. Chongqing Branch, China Construction Science and Industry Corporation Ltd., Chongqing 400000, China |
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| Abstract: | The virtual trial assembly based on point cloud data includes the data acquisition, control point extraction, and control point matching. To address the difficult data acquisition and high-cost processing of complete point cloud data, partial point cloud data were utilized in the virtual trial assembly. To address the fact that current control point extraction methods are software dependent, ineffective, and subjective, an intelligent control point extraction method was developed for both the cross sections and sides of large and complex components based on the point cloud data, random sample consensus, Hough transform, and image-processing techniques. To address the fact that these relationships between control points are manually determined, an intelligent control point matching method was developed based on the super four-point congruent sets, iterative closest point, and generalized Procrustes analysis. The proposed methods were adopted in the intelligent virtual trial assembly of a large and complex steel bridge, where a beam was assembled to an arch rib, and one arch rib was assembled to another arch rib. The proposed intelligent virtual trial assembly method is found to be software independent, effective, and highly automated, providing supports for improving the construction quality and efficiency of steel bridges with theories and algorithms. |
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| Keywords: | bridge engineering large and complex steel bridges intelligent virtual trial assembly point cloud data intelligent algorithm |
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