Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 24 von 100

Details

Autor(en) / Beteiligte
Titel
Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections
Ist Teil von
  • Journal of robotics and mechatronics, 2020-12, Vol.32 (6), p.1244-1258
Ort / Verlag
Tokyo: Fuji Technology Press Co. Ltd
Erscheinungsjahr
2020
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • In recent years, aging of bridges has become a growing concern, and the danger of bridge collapse is increasing. To appropriately maintain bridges, it is necessary to perform inspections to accurately understand their current state. Until now, bridge inspections have involved a visual inspection in which inspection personnel come close to the bridges to perform inspection and hammering tests to investigate abnormal noises by hammering the bridges with an inspection hammer. Meanwhile, as there are a large number of bridges (for example, 730,000 bridges in Japan), and many of these are constructed at elevated spots; the issue is that the visual inspections are laborious and require huge cost. Another issue is the wide disparity in the quality of visual inspections due to the experience, knowledge, and competence of inspectors. Accordingly, the authors are trying to resolve or ameliorate these issues using unmanned aerial vehicle (UAV) technology, artificial intelligence (AI) technology, and telecommunications technology. This is discussed first in this paper. Next, the authors discuss the future prospects of bridge inspection using robot technology such as a 3-D model of bridges. The goal of this paper is to show the areas in which deployment of the UAV, robots, telecommunications, and AI is beneficial and the requirements of these technologies.
Sprache
Englisch
Identifikatoren
ISSN: 0915-3942
eISSN: 1883-8049
DOI: 10.20965/jrm.2020.p1244
Titel-ID: cdi_proquest_journals_2471158951

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX