点云和BIM的钢筋骨架质量自动检测方法

Automatic quality inspection method for reinforcement bar skeleton based on point cloud and BIM

针对复杂钢筋质量检查存在耗时耗力、自动化程度低等问题,该文以钢筋骨架点云为研究对象,结合建筑信息模型(BIM)提出了一种基于几何特征的钢筋质量自动检测算法。该方法首先将钢筋骨架扫描点云与BIM转化后的设计点云进行高精度配准,然后利用邻域搜索方法提取包含钢筋编号信息的钢筋骨架点云,最后结合设计点云和钢筋骨架点云采用比值法、随机采样一致性(RANSAC)圆柱拟合法实现钢筋数量、尺寸和间距的质量自动化检查。结果表明:该方法的复杂钢筋骨架数量检查的平均准确率为98.1%,尺寸估计的平均准确率为68.7%,间距检查的平均准确率为95.4%。提出的算法可实现工程应用上复杂钢筋骨架质量的自动检查,显著提高了工作效率,降低了成本。

In view of the problems that in the field of quality inspection for complex reinforcement bar, issues such as time-consuming, labor-intensive and low automation had been identified, an automatic quality inspection algorithm for rebar based on geometric features using rebar skeleton point cloud data as the research object, combining with building information modeling(BIM) was proposed in this paper. First, the proposed method achieved high precision registration between the scanned point cloud of the rebar and the designed point cloud converted by BIM. Second, reinforcement bar skeleton point cloud containing rebar numbers information would be extracted by neighborhood search method. Finally, combining the designed point cloud and the rebar skeleton point cloud, the ratio method and the improved random sample consensus(RANSAC) cylindrical fitting method were used to achieve automatic quality inspection of the quantity, size, and spacing of rebar. The results demonstrated that employing this algorithm, the average accuracy of quantity inspection for complex rebar reached 98.1%,dimension estimation achieved an accuracy of 68.7%,and spacing inspection achieved an accuracy of 95.4%. The proposed algorithm enabled automated quality inspection of complex rebar skeleton in engineering applications, significantly improving work efficiency and reducing costs.