【摘要】 桥梁钢构件虚拟预拼装工序存在费时、占地较大、成本较高等问题。研究基于超体素分割与区域生长算法，提出一种自动化桥梁钢构件虚拟预拼装技术，实现对构件点云特征面精准分割。该方案考虑到纵梁与横梁构件特殊的几何形态，利用奇异值分解算法、随机一致性拟合算法及空间几何原理自动提取拼接所需特征点，有效解决了传统点云拼接控制点在人工选取时主观性较大、精度难以控制等问题。同时提出了阈值法与设计值辅助线法，在构件扫描点云质量缺失的情况下亦实现精确拼装。实际工程应用结果显示拼装后平均误差为0.62 mm,最大误差仅为1.32 mm,夹角误差最大为0.139°,方案的精度控制合理、适用性强。基于研究成果在Cloud Compare平台上研发了一组算法插件，进一步实现拼接工序的自动化与规范化。研究成果可为桥梁钢虚拟预拼装及同类型工程项目提供理论和算法支撑，具备较好的生产应用价值。更多还原

【Abstract】 The virtual pre-assembly process of bridge steel components faces challenges such as time consumption, large footprint, and high costs. This paper proposes an automatic virtual pre-assembly technology for bridge steel components, employing supervoxel segmentation and a region-growing algorithm to achieve precise segmentation of component point cloud feature surfaces. The method accommodates the unique geometry of carling and crossbeam members. Using singular value decomposition algorithm, random consistency fitting algorithm and spatial geometry principle to automatically extract the feature points needed for Mosaic, the traditional point cloud Mosaic control points in the manual selection of large subjectivity, accuracy is difficult to control and other problems effectively solved. Moreover, the paper introduces data threshold and design value auxiliary line methods to ensure accurate assembly, even in scenarios with missing component scanning point cloud data. Engineering application results demonstrate an average error of 0.62 mm, a maximum error of only 1.32 mm, and a maximum angle error of 0.139°, indicating reasonable accuracy control and strong applicability. Based on the research results, a group of algorithm plug-ins are developed on the Cloud Compare platform to further realize the automation and standardization of the stitching process. The research results can provide theoretical and algorithmic support for virtual preassembly of bridge steel and similar engineering projects, and reflect better production and application value.更多还原