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Verification of Building Structures Using Point Clouds and Building Information Models

Autor(en): ORCID
ORCID
ORCID
ORCID

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 12, v. 12
Seite(n): 2218
DOI: 10.3390/buildings12122218
Abstrakt:

The effort towards automation of the building industry processes has increased significantly over the last years worldwide. One of the key tools in this process is the modeling of buildings using Building Information Modeling (BIM). When following fundamental principles, a BIM model serves as an up-to-date pool of information. Combining the results of effective spatial data collection techniques with the information from a BIM model, it is possible to increase the effectiveness of as-built documentation of the structures or in-site clash detection between the built and planned parts. In this paper, we describe an approach for the verification of building structures by comparing the as-built model created from point clouds with the as-planned model of the building. The point clouds can be collected by laser scanning or photogrammetry, while the geometry of the planned (designed) structures is derived from the BIM model in the Industry Foundation Classes (IFC) format. The advantage of the approach is that the as-built model is created by regression models from point clouds preprocessed by detailed segmentation. The deviations from the design and the relative geometry (e.g., flatness) of the elements are expressed by signed color maps. The presented workflow enables semi-automated verification of building structures.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10712426
  • Veröffentlicht am:
    21.03.2023
  • Geändert am:
    10.05.2023
 
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