Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm

One of the challenges in the health monitoring of bridge structures is the "data" extraction from the structure. This is done by sensors in the structure. The layout and use of the fewest possible number of sensors, so as to provide the most needed data on structural status, has always bee...

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Autores principales:	Seyed Ali Razavian Amrei, Amin Hajizadeh Amini
Formato:	article
Lenguaje:	FA
Publicado:	Iranian Society of Structrual Engineering (ISSE) 2021
Materias:	optimal sensor placement structure health bridge genetic algorithm mse-mga Bridge engineering TG1-470 Building construction TH1-9745
Acceso en línea:	https://doaj.org/article/185af42ba0f241d1a10439e232a75715
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spelling	oai:doaj.org-article:185af42ba0f241d1a10439e232a757152021-11-08T15:55:01ZOptimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm2476-39772538-261610.22065/jsce.2020.201830.1948https://doaj.org/article/185af42ba0f241d1a10439e232a757152021-08-01T00:00:00Zhttps://www.jsce.ir/article_106971_9b62e868f6d5440cc5a84903bd5a822a.pdfhttps://doaj.org/toc/2476-3977https://doaj.org/toc/2538-2616One of the challenges in the health monitoring of bridge structures is the "data" extraction from the structure. This is done by sensors in the structure. The layout and use of the fewest possible number of sensors, so as to provide the most needed data on structural status, has always been of interest. There are shortcomings in the methods used to determine the location of sensors in bridges, such as the use of one optimization indicator, determination of the number of sensors experimentally, high environmental noise, and a long calculation time. In order to overcome these shortcomings, a new MSE-MGA (Modal Strain Energy-Modified Genetic Algorithm) method is proposed in this study. In this method, two modal strain energy indices and modal contribution coefficient are used to reduce the noise effect of vehicles passing through. All the appropriate locations of the sensors are selected by these indices, and then the optimal number of sensors and their location are determined by using the genetic algorithm. The results show that increasing the number of sensors from a given optimal value has no effect on increasing the required data. Also, the simultaneous use of two optimization indices has resulted in the elimination of a large number of inappropriate points for sensor placement, resulting in a significantly reduced computational time. To investigate the performance and practical application of this method, a model of a steel bridge is modeled and the optimal number of sensors and their layout are determined.Seyed Ali Razavian AmreiAmin Hajizadeh AminiIranian Society of Structrual Engineering (ISSE)articleoptimal sensor placementstructure healthbridgegenetic algorithmmse-mgaBridge engineeringTG1-470Building constructionTH1-9745FAJournal of Structural and Construction Engineering, Vol 8, Iss 6, Pp 5-23 (2021)
institution	DOAJ
collection	DOAJ
language	FA
topic	optimal sensor placement structure health bridge genetic algorithm mse-mga Bridge engineering TG1-470 Building construction TH1-9745
spellingShingle	optimal sensor placement structure health bridge genetic algorithm mse-mga Bridge engineering TG1-470 Building construction TH1-9745 Seyed Ali Razavian Amrei Amin Hajizadeh Amini Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
description	One of the challenges in the health monitoring of bridge structures is the "data" extraction from the structure. This is done by sensors in the structure. The layout and use of the fewest possible number of sensors, so as to provide the most needed data on structural status, has always been of interest. There are shortcomings in the methods used to determine the location of sensors in bridges, such as the use of one optimization indicator, determination of the number of sensors experimentally, high environmental noise, and a long calculation time. In order to overcome these shortcomings, a new MSE-MGA (Modal Strain Energy-Modified Genetic Algorithm) method is proposed in this study. In this method, two modal strain energy indices and modal contribution coefficient are used to reduce the noise effect of vehicles passing through. All the appropriate locations of the sensors are selected by these indices, and then the optimal number of sensors and their location are determined by using the genetic algorithm. The results show that increasing the number of sensors from a given optimal value has no effect on increasing the required data. Also, the simultaneous use of two optimization indices has resulted in the elimination of a large number of inappropriate points for sensor placement, resulting in a significantly reduced computational time. To investigate the performance and practical application of this method, a model of a steel bridge is modeled and the optimal number of sensors and their layout are determined.
format	article
author	Seyed Ali Razavian Amrei Amin Hajizadeh Amini
author_facet	Seyed Ali Razavian Amrei Amin Hajizadeh Amini
author_sort	Seyed Ali Razavian Amrei
title	Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
title_short	Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
title_full	Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
title_fullStr	Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
title_full_unstemmed	Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm
title_sort	optimal sensor placement for the structure health monitoring of bridge structures using genetic algorithm
publisher	Iranian Society of Structrual Engineering (ISSE)
publishDate	2021
url	https://doaj.org/article/185af42ba0f241d1a10439e232a75715
work_keys_str_mv	AT seyedalirazavianamrei optimalsensorplacementforthestructurehealthmonitoringofbridgestructuresusinggeneticalgorithm AT aminhajizadehamini optimalsensorplacementforthestructurehealthmonitoringofbridgestructuresusinggeneticalgorithm
_version_	1718441546570792960

Optimal Sensor Placement for the Structure Health Monitoring of Bridge Structures Using Genetic Algorithm

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