YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    3D Reconstruction and Measurement of Surface Defects in Prefabricated Elements Using Point Clouds

    Source: Journal of Computing in Civil Engineering:;2020:;Volume ( 034 ):;issue: 005
    Author:
    Zhao Xu
    ,
    Rui Kang
    ,
    Ruodan Lu
    DOI: 10.1061/(ASCE)CP.1943-5487.0000920
    Publisher: ASCE
    Abstract: Due to a higher efficiency and lower cost, prefabricated construction is gradually gaining acceptance within the market. Laser scanning has already been adopted in civil engineering to reconstruct a three-dimensional (3D) model of a structure, to monitor the deformation, and so on. This paper seeks to explore a more automated and accurate quality control process, focusing on the surface defects in prefabricated elements. Laser scanning is adopted for data collection and the 3D reconstruction of the prefabricated components. Besides, a new point cloud preprocessing, involving the K-nearest neighbors (KNN) algorithm, a reduction of the data dimension, and data gridding, is developed to improve the efficiency and accuracy of subsequent algorithms. The Delaunay triangle is used to extract the contour of the point cloud, and then the contour is fitted to further determine the geometric data. Meanwhile, a comprehensive quality control system of prefabricated components based on relevant specifications is proposed, and the quality of prefabricated components is monitored intuitively by the values of indicators. In order to integrate it into the building information modeling (BIM) platform and better store the obtained quality information, the production quality information is designed to be extended to the Industry Foundation Classes (IFC) standard. The proposed approach will be applied to analyze the causes of quality problems in the production process and strengthen the quality control. This study designs a more efficient and accurate quality evaluation process, including data collection, data processing, indicator calculation, and quality evaluation. Moreover, the results moving forward can provide feedback to the cause of the quality issues and further improve the production quality of prefabricated elements.
    • Download: (5.088Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      3D Reconstruction and Measurement of Surface Defects in Prefabricated Elements Using Point Clouds

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4268385
    Collections
    • Journal of Computing in Civil Engineering

    Show full item record

    contributor authorZhao Xu
    contributor authorRui Kang
    contributor authorRuodan Lu
    date accessioned2022-01-30T21:32:26Z
    date available2022-01-30T21:32:26Z
    date issued9/1/2020 12:00:00 AM
    identifier other%28ASCE%29CP.1943-5487.0000920.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4268385
    description abstractDue to a higher efficiency and lower cost, prefabricated construction is gradually gaining acceptance within the market. Laser scanning has already been adopted in civil engineering to reconstruct a three-dimensional (3D) model of a structure, to monitor the deformation, and so on. This paper seeks to explore a more automated and accurate quality control process, focusing on the surface defects in prefabricated elements. Laser scanning is adopted for data collection and the 3D reconstruction of the prefabricated components. Besides, a new point cloud preprocessing, involving the K-nearest neighbors (KNN) algorithm, a reduction of the data dimension, and data gridding, is developed to improve the efficiency and accuracy of subsequent algorithms. The Delaunay triangle is used to extract the contour of the point cloud, and then the contour is fitted to further determine the geometric data. Meanwhile, a comprehensive quality control system of prefabricated components based on relevant specifications is proposed, and the quality of prefabricated components is monitored intuitively by the values of indicators. In order to integrate it into the building information modeling (BIM) platform and better store the obtained quality information, the production quality information is designed to be extended to the Industry Foundation Classes (IFC) standard. The proposed approach will be applied to analyze the causes of quality problems in the production process and strengthen the quality control. This study designs a more efficient and accurate quality evaluation process, including data collection, data processing, indicator calculation, and quality evaluation. Moreover, the results moving forward can provide feedback to the cause of the quality issues and further improve the production quality of prefabricated elements.
    publisherASCE
    title3D Reconstruction and Measurement of Surface Defects in Prefabricated Elements Using Point Clouds
    typeJournal Paper
    journal volume34
    journal issue5
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)CP.1943-5487.0000920
    page17
    treeJournal of Computing in Civil Engineering:;2020:;Volume ( 034 ):;issue: 005
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian