基于点云数据的大型复杂钢结构智能化施工方法

Intelligent construction of large and complex steel structure based on point cloud data

大型复杂钢结构施工过程中,常面临施工尺寸质量难以把控、构件提升变形监测困难和合拢段现场配切效率低等问题。三维激光扫描技术可全覆盖地、快速精准地获取复杂构部件在施工过程中的点云数据,这为解决上述问题提供了新方法。为此,该文以重庆两江新区寨子路钢拱桥为工程背景,开展基于点云数据的大型复杂钢拱桥智能化施工方法的全流程研究。基于标靶球检测算法、快速四点一致集算法、迭代最近邻算法等实现标靶球点云数据的自动检测及多站点云数据之间的自动配准;通过BIM点云化技术、kNN算法等完成目标点云数据的半自动化提取,实现拱肋尺寸的智能化检测;基于八叉树算法、区域增长算法等实现拱肋提升变形的智能检测;为缩短拱肋的合拢工期,基于BIM模型焊缝信息提取技术、主成分分析算法、Canny边界检测算法、霍夫变换算法等提出数字化预拼装算法,得到合拢段的配切量。工程应用表明,该文所提出的智能施工方法效率高、自动化程度好,研究成果可为大型复杂钢结构的施工质量和安装效率的提升提供理论和算法支撑。

In the construction of large and complex steel structure(LCSS),many challenges are frequently faced.For example,dimensional construction quality is hard to control,lifting deformation is hard to inspect,and closing section cutting at site is ineffi-cient.Three three-dimensional laser scanning technology can obtain the accurate point cloud data(PCD)of LCSS to solve above problems.Aiming at the steel arch bridge located at Zhaizi road,Two-rivers district,Chongqing city,full-process researches about intelligent construction methods of LCSS based on the PCD were studied.The target ball detection algo-rithm,4-Points Congruent Sets algorithm and Iterative Closest Point algorithm were utilized for automated detection of target balls and automated registration of multiple scans.Based on the BIM transforming technology and kNN algorithm,target PCD were extracted in a semi-automated way and then arch rib dimensional quality was automatically inspected.A lifting deformation inspection method was proposed based on the Octree algorithm and Region Growing algorithm.In order to shorten the closing construction period,a virtual trial assembly algorithm was proposed using welding information extraction of BIM model,Principle Component Analysis algorithm,Canny edge detector and Hough Transform algorithm.And then cutting lengths of closing sections were obtained.The research results show that the proposed intelligent construction methods are effective and highly automated,which can provide supports for improving the construction quality and efficiency of LCSS with theories and algorithms.