Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Marchewka, Adam, Ziółkowski, Patryk, Aguilar-Vidal, Victor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
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
_version_ 1783500785511825408
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
work_keys_str_mv AT marchewkaadam frameworkforstructuralhealthmonitoringofsteelbridgesbycomputervision
AT ziołkowskipatryk frameworkforstructuralhealthmonitoringofsteelbridgesbycomputervision
AT aguilarvidalvictor frameworkforstructuralhealthmonitoringofsteelbridgesbycomputervision