Potentials of Autonomous UAS and Automated Image Analysis for Structural Health Monitoring
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Détails bibliographiques
| Auteur(s): |
Jens Kersten
(Bauhaus-Universität Weimar, Weimar, Germany)
Volker Rodehorst (Bauhaus-Universität Weimar, Weimar, Germany) Norman Hallermann (Bauhaus-Universität Weimar, Weimar, Germany) Paul Debus (Bauhaus-Universität Weimar, Weimar, Germany) Guido Morgenthal 
(Bauhaus-Universität Weimar, Weimar, Germany)
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| Médium: | papier de conférence | ||||
| Langue(s): | anglais | ||||
| Conférence: | IABSE Symposium: Tomorrow’s Megastructures, Nantes, France, 19-21 September 2018 | ||||
| Publié dans: | IABSE Symposium Nantes 2018 | ||||
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| Page(s): | S24-119 | ||||
| Nombre total de pages (du PDF): | 8 | ||||
| DOI: | 10.2749/nantes.2018.s24-119 | ||||
| Abstrait: |
Unmanned aircraft systems (UAS) are increasingly used for the inspection of buildings and critical infrastructures. Manual inspection efforts can be reduced by a camera equipped UAS in combination with advanced image analysis. Tailored methods for the planning of UAS-based image acquisition are required here. In order to ensure efficient inspection procedures, the geo-location, view direction and imaging properties of each image have to be reconstructed. Furthermore, accurate and reliable methods for the extraction of 3D object information as well as visible damages can be exploited to automatically identify potentially affected areas. In this paper, the components and required methods for an inspection system supported by an autonomous UAS and automated image analysis are identified, discussed and evaluated. The results show the great potential and value of process automation and the benefit of image analysis in a decision support system. |
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