Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study

Atmospheric corrosion, especially in coastal environments, is a major structural problem affecting metallic structures in various sectors. Structural health monitoring systems based on satellite information can help to ensure the proper behavior of civil structures and are an interesting alternative...

Full description

Saved in:
Bibliographic Details
Main Authors: Marta Terrados-Cristos, Francisco Ortega-Fernández, Marina Díaz-Piloneta, Vicente Rodríguez Montequín, Javier García González
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2022/6557898
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832545839226028032
author Marta Terrados-Cristos
Francisco Ortega-Fernández
Marina Díaz-Piloneta
Vicente Rodríguez Montequín
Javier García González
author_facet Marta Terrados-Cristos
Francisco Ortega-Fernández
Marina Díaz-Piloneta
Vicente Rodríguez Montequín
Javier García González
author_sort Marta Terrados-Cristos
collection DOAJ
description Atmospheric corrosion, especially in coastal environments, is a major structural problem affecting metallic structures in various sectors. Structural health monitoring systems based on satellite information can help to ensure the proper behavior of civil structures and are an interesting alternative for remote locations. The aim of this case study is to relate remote sensing information to the results of experimental studies for potential structural damage characterization. The ultimate idea is to characterize any environment without long testing periods or sampling costs. Comparative nondestructive experimental tests involving different locations, sampling techniques, and study periods are performed. The results obtained are analyzed and compared with meteorological satellite data characterization at each site. The experimental test results show sufficient statistical significance (p < 0.05), confirming that the areas potentially most susceptible to corrosion can be identified using information from remote sensing satellites based on orientation, wind conditions, and wind origin. This can be used to facilitate the remote design and monitoring of structures more accurately with a stability guarantee.
format Article
id doaj-art-3915e08574724acbaf0e97dfd432f999
institution Kabale University
issn 1687-8094
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Advances in Civil Engineering
spelling doaj-art-3915e08574724acbaf0e97dfd432f9992025-02-03T07:24:27ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/6557898Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case StudyMarta Terrados-Cristos0Francisco Ortega-Fernández1Marina Díaz-Piloneta2Vicente Rodríguez Montequín3Javier García González4Project Engineering DepartmentProject Engineering DepartmentProject Engineering DepartmentProject Engineering DepartmentProject Engineering DepartmentAtmospheric corrosion, especially in coastal environments, is a major structural problem affecting metallic structures in various sectors. Structural health monitoring systems based on satellite information can help to ensure the proper behavior of civil structures and are an interesting alternative for remote locations. The aim of this case study is to relate remote sensing information to the results of experimental studies for potential structural damage characterization. The ultimate idea is to characterize any environment without long testing periods or sampling costs. Comparative nondestructive experimental tests involving different locations, sampling techniques, and study periods are performed. The results obtained are analyzed and compared with meteorological satellite data characterization at each site. The experimental test results show sufficient statistical significance (p < 0.05), confirming that the areas potentially most susceptible to corrosion can be identified using information from remote sensing satellites based on orientation, wind conditions, and wind origin. This can be used to facilitate the remote design and monitoring of structures more accurately with a stability guarantee.http://dx.doi.org/10.1155/2022/6557898
spellingShingle Marta Terrados-Cristos
Francisco Ortega-Fernández
Marina Díaz-Piloneta
Vicente Rodríguez Montequín
Javier García González
Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
Advances in Civil Engineering
title Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
title_full Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
title_fullStr Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
title_full_unstemmed Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
title_short Potential Structural Damage Characterization through Remote Sensing Data: A Nondestructive Experimental Case Study
title_sort potential structural damage characterization through remote sensing data a nondestructive experimental case study
url http://dx.doi.org/10.1155/2022/6557898
work_keys_str_mv AT martaterradoscristos potentialstructuraldamagecharacterizationthroughremotesensingdataanondestructiveexperimentalcasestudy
AT franciscoortegafernandez potentialstructuraldamagecharacterizationthroughremotesensingdataanondestructiveexperimentalcasestudy
AT marinadiazpiloneta potentialstructuraldamagecharacterizationthroughremotesensingdataanondestructiveexperimentalcasestudy
AT vicenterodriguezmontequin potentialstructuraldamagecharacterizationthroughremotesensingdataanondestructiveexperimentalcasestudy
AT javiergarciagonzalez potentialstructuraldamagecharacterizationthroughremotesensingdataanondestructiveexperimentalcasestudy