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Framework for Structural Health Monitoring of Steel Bridges by Computer Vision
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 coun...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039231/ https://www.ncbi.nlm.nih.gov/pubmed/32012791 http://dx.doi.org/10.3390/s20030700 |
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author | Marchewka, Adam Ziółkowski, Patryk Aguilar-Vidal, Victor |
author_facet | Marchewka, Adam Ziółkowski, Patryk Aguilar-Vidal, Victor |
author_sort | Marchewka, Adam |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7039231 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70392312020-03-09 Framework for Structural Health Monitoring of Steel Bridges by Computer Vision Marchewka, Adam Ziółkowski, Patryk Aguilar-Vidal, Victor Sensors (Basel) Article 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. MDPI 2020-01-27 /pmc/articles/PMC7039231/ /pubmed/32012791 http://dx.doi.org/10.3390/s20030700 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Marchewka, Adam Ziółkowski, Patryk Aguilar-Vidal, Victor Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title | Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title_full | Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title_fullStr | Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title_full_unstemmed | Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title_short | Framework for Structural Health Monitoring of Steel Bridges by Computer Vision |
title_sort | framework for structural health monitoring of steel bridges by computer vision |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039231/ https://www.ncbi.nlm.nih.gov/pubmed/32012791 http://dx.doi.org/10.3390/s20030700 |
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