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Automated Quality Inspection of Precast Concrete Elements with Irregular Shapes Using Terrestrial Laser Scanner and BIM Technology

机译:使用陆地激光扫描仪和BIM技术,具有不规则形状的预制混凝土元件的自动化质量检测

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Nowadays precast concrete elements are widely used in buildings, bridges, and other civil infrastructure facilities because precast elements allow rapid construction and high precision quality control. However, the quality inspection of precast concrete elements primarily relies on manual inspection, which is time consuming and error-prone. Recently, terrestrial laser scanner (TLS) has been used to improve quality inspection. The authors' group has previously developed an automated dimension estimation technique for precast concrete elements, but its applicability is limited only to precast elements with rectangular shapes. This study advances our previous work so that the dimensions of precast elements with irregular shapes can also be automatically estimated. First, a density-based clustering algorithm is adopted to extract target objects from 3D point cloud data acquired by a TLS. Then, coarse registration is conducted to match each object extracted from the 3D point cloud with the asdesign objects in building information models (BIM) one by one. Thirdly, all point cloud data points are registered onto different surfaces of the as-designed objects in BIM through fine registration. Lastly, the as-built dimensions of the precast concrete element are extracted and compared with the as-design ones in BIM. The effectiveness and accuracy of the developed technique are examined using point cloud data obtained from a laboratory-scale precast concrete bridge deck panel.
机译:如今,预制混凝土元件广泛应用于建筑物,桥梁和其他民用基础设施,因为预制元件允许快速施工和高精度的质量控制。然而,预制混凝土元件的质量检测主要依赖于手动检查,这是耗时和容易出错的。最近,陆地激光扫描仪(TLS)已被用于改善质量检验。作者组先前已经开发出一种用于预制混凝土元件的自动尺寸估计技术,但其适用性仅限于具有矩形形状的预制元件。本研究推进了我们之前的工作,以便也可以自动估计具有不规则形状的预制元素的尺寸。首先,采用基于密度的聚类算法来从TL获取的3D点云数据中提取目标对象。然后,进行粗略注册以将从3D点云提取的每个对象与ASDesign对象逐一构建信息模型(BIM)。第三,通过精细的注册将所有点云数据点注册到BIM中的设计对象的不同表面上。最后,提取了预制混凝土元件的尺寸并与BIM中的AS-设计中提取的尺寸。使用从实验室刻度预制混凝土桥甲板面板获得的点云数据来检查开发技术的有效性和准确性。

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