Wyszukiwarka
Abstrakt
The monitoring of a structural condition of steel bridges is an important issue. Good condition of infrastructure facilities ensures the safety and economic well-being of society. At the same time, due to the continuous development, rising wealth of the society and socio-economic integration of countries, the number of infrastructural objects is growing. Therefore, there is a need to introduce an easy-to-use and relatively low-cost method of bridge diagnostics. We can achieve these benefits by the use of Unmanned Aerial Vehicle-Based Remote Sensing and Digital Image Processing. In our study, we present a state-of-the-art framework for Structural Health Monitoring of steel bridges that involves literature review on steel bridges health monitoring, drone route planning, image acquisition, identification of visual markers that may indicate a poor condition of the structure and determining the scope of applicability. The presented framework of image processing procedure is suitable for diagnostics of steel truss riveted bridges. In our considerations, we used photographic documentation of the Fitzpatrick Bridge located in Tallassee, Alabama, USA.
Cytowania
-
3 4
CrossRef
-
0
Web of Science
-
3 3
Scopus
Autorzy (3)
-
Adam Marchewka dr inż.
- University of Science and Technology in Bydgoszcz
-
Victor Aguilar-vidal dr inż.
- Auburn University
Cytuj jako
Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- Licencja
-
otwiera się w nowej karcie
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
-
SENSORS
nr 20,
strony 1 - 21,
ISSN: 1424-8220 - Język:
- angielski
- Rok wydania:
- 2020
- Opis bibliograficzny:
- Marchewka A., Ziółkowski P., Aguilar-Vidal V.: Framework for Structural Health Monitoring of Steel Bridges by Computer Vision// SENSORS -Vol. 20,iss. 3 (2020), s.1-21
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/s20030700
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 195 razy