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Unmanned Aerial Systems (UAS) – Survey and monitoring based on high-quality airborne photos

 Unmanned Aerial Systems (UAS) – Survey and monitoring based on high-quality airborne photos
Auteur(s): , ORCID,
Présenté pendant IABSE Conference: Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, September 2015, publié dans , pp. 1279-1286
DOI: 10.2749/222137815818358583
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Monitoring strategies play a major role for achieving the target service life of existing structures. Conventional inspections are based on visual investigations. The data acquisition process is th...
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Détails bibliographiques

Auteur(s): (Bauhaus-Universität Weimar, Weimar, Germany)
ORCID (Bauhaus-Universität Weimar, Weimar, Germany)
(Bauhaus-Universität Weimar, Weimar, Germany)
Médium: papier de conférence
Langue(s): anglais
Conférence: IABSE Conference: Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, September 2015
Publié dans:
Page(s): 1279-1286 Nombre total de pages (du PDF): 8
Page(s): 1279-1286
Nombre total de pages (du PDF): 8
Année: 2015
DOI: 10.2749/222137815818358583
Abstrait:

Monitoring strategies play a major role for achieving the target service life of existing structures. Conventional inspections are based on visual investigations. The data acquisition process is the most time consuming, personal as well as technical complexity and thereby a cost intensive part of inspections. This paper discusses a novel method, respectively a workflow of visual inspection including a highly-accurate survey of structures based on aerial photos taken by remote controlled professional unmanned aerial systems (UAS). This approach could provide an important contribution to monitoring strategies in terms of quality, safety and efficiency. The paper shows two case studies of UAS in condition monitoring based on the combination of conventional inspection measurements with modern photogrammetric computer vision methods for geo- referenced 3D-modelling of structures and automatic post-flight damage detection.

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