计算机科学
桥(图论)
人工智能
计算机视觉
医学
内科学
作者
Yi Tan,Limei Chen,Qian Wang,Shenghan Li,Ting Deng,Dongdong Tang
出处
期刊:Remote Sensing
[MDPI AG]
日期:2023-01-17
卷期号:15 (3): 556-556
被引量:12
摘要
Prefabricated steel box girders (SBGs) are widely adopted in bridge engineering due to their light weight and low lifecycle cost. To smoothly assemble SBG components on a construction site, it is necessary to inspect their geometric quality and ensure that all the as-is SBG components have the correct dimensions. However, the traditional inspection method is time-consuming and error-prone. This study developed a non-contact geometric quality assessment technique based on 3D laser scanning to accurately assess the locations and dimensions of SBG components. First, a robust normal-based region-growing algorithm was developed to divide the SBG components into segments with different labels. The scanned data related to the T ribs were then extracted through the proposed subtraction algorithm after the identification of the steel cabin. Lastly, the required items for geometric quality inspection were calculated based on the extracted as-is SBG components. The feasibility of the proposed geometric quality assessment method was validated through a real SBG project. Field test results showed that the developed inspection technique could assess the geometric quality of prefabricated SBG components in a more accurate and efficient manner compared to traditional measurement approaches.
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