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Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures

Autor(en):





Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Journal of Information Technology in Construction, , v. 28
Seite(n): 774-805
DOI: 10.36680/j.itcon.2023.040
Abstrakt:

Bridge inspection is a time-consuming, expensive, but indispensable task. In this work, a new semi-automatic workflow for a concrete bridge condition assessment system is developed and discussed. The workflow consists of three main parts merged in the new methodology. The elements are the data acquisition with cameras, the automated damage detection and localization using a neural network, and the resulting engineering condition assessment. Furthermore, a CAD model serves as a base for the later calculations for the condition assessment. Camera images are used for both sub-millimeter crack detection using semantic segmentation by an artificial neural network and a crack localization based on a combination of a photogrammetric workflow including structure from motion (SfM) and the projection as imprinted points directly onto the as-planned CAD mesh. Moreover, an approach for crack width derivation is given. The captured crack width, crack position, and the date of detection represent the input values for subsequent crack monitoring. Thereby, this new concept is proposed as an essential step towards a time-efficient and objective life-cycle assessment of reinforced concrete structures.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.36680/j.itcon.2023.040.
  • Über diese
    Datenseite
  • Reference-ID
    10756343
  • Veröffentlicht am:
    14.01.2024
  • Geändert am:
    14.01.2024
 
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