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Vision-based deformation monitoring of large scale structures using Unmanned Aerial Systems

 Vision-based deformation monitoring of large scale structures using Unmanned Aerial Systems
Autor(en): , ORCID,
Beitrag für IABSE Symposium: Engineering for Progress, Nature and People, Madrid, Spain, 3-5 September 2014, veröffentlicht in , S. 2852-2859
DOI: 10.2749/222137814814070343
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The monitoring and inspection of structures is typically based on visual investigations. Especially the examination of very large structures, for example large retaining walls or dams, is an excep...
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Bibliografische Angaben

Autor(en):
ORCID

Medium: Tagungsbeitrag
Sprache(n): Englisch
Tagung: IABSE Symposium: Engineering for Progress, Nature and People, Madrid, Spain, 3-5 September 2014
Veröffentlicht in:
Seite(n): 2852-2859 Anzahl der Seiten (im PDF): 8
Seite(n): 2852-2859
Anzahl der Seiten (im PDF): 8
Jahr: 2014
DOI: 10.2749/222137814814070343
Abstrakt:

The monitoring and inspection of structures is typically based on visual investigations. Especially the examination of very large structures, for example large retaining walls or dams, is an exceptionally complex task for civil engineers and closely associated with high risks regarding to the assessment of structural stability. For a reliable assessment of the structural stability detailed data of all parts of the structure are required. But an all-embracing inspection of such structures is technically complex and time consuming. This leads to high inspection costs.

This paper presents a new vision-based monitoring method of large scale structures based on aerial photos taken by remote controlled unmanned aerial systems. The approach offers the possibility of detailed automatic displacement detection by using photogrammetric computer vision algorithms in post flight analysis. The currently available high-end flight systems and new computer vision methods can contribute to the improvement of quality and efficiency of the inspection and safety of large structures.

Stichwörter:
Bauwerksprüfung Monitoring UAS