The connection between precast concrete (PC) components is vital during the construction of prefabricated structures. However, PC components are generally inspected and measured manually, which is laborious and error-prone. Therefore, a novel approach was developed for automated recognition and measurement of rebars, concrete, and sleeves of PC components based on three-dimensional point clouds. The proposed approach recognizes rebars, concrete planes, and the edge points of sleeve ports using a one-class classifier, a clustering algorithm, and an alpha-shape algorithm, respectively. Furthermore, boundary estimation was performed to determine the dimensions and positions of the subcomponents. The obtained experimental results validate that an average distance of 3.0 mm exists between the center of rebar cross-sections and their corresponding sleeve ports. The proposed approach provides a novel solution for automatically recognizing rebars, concrete, and sleeves of PC components. Furthermore, it can potentially control the quality of PC components and reduce the cost of construction.

在预制结构的建造过程中，预制混凝土 (PC) 组件之间的连接至关重要。然而，PC 组件通常是手动检查和测量的，这既费力又容易出错。因此，开发了一种基于三维点云的 PC 组件钢筋、混凝土和套管自动识别和测量的新方法。所提出的方法分别使用一类分类器、聚类算法和阿尔法形状算法来识别钢筋、混凝土平面和套管端口的边缘点。此外，执行边界估计以确定子组件的尺寸和位置。获得的实验结果验证了平均距离为 3。钢筋横截面的中心与其对应的套管端口之间存在 0 mm。所提出的方法为自动识别钢筋、混凝土和 PC 组件的套管提供了一种新颖的解决方案。此外，它还可以潜在地控制 PC 组件的质量并降低构建成本。