Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring

For a practical structural health monitoring (SHM) system, the traditional single objective methods for optimal sensor placement (OSP) cannot always obtain the optimal result of sensor deployment without sacrificing other targets, which creates obstacles to the efficient use of the sensors. This stu...

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Autores principales:	Shao-Xiao Nong, Dong-Hui Yang, Ting-Hua Yi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	structural health monitoring optimal sensor placement bi-objective optimization Pareto optimization non-dominated sorting genetic algorithm Building construction TH1-9745
Acceso en línea:	https://doaj.org/article/17917874d3d44a6ba6fcc34f90bd7bf9
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id	oai:doaj.org-article:17917874d3d44a6ba6fcc34f90bd7bf9
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spelling	oai:doaj.org-article:17917874d3d44a6ba6fcc34f90bd7bf92021-11-25T17:00:19ZPareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring10.3390/buildings111105492075-5309https://doaj.org/article/17917874d3d44a6ba6fcc34f90bd7bf92021-11-01T00:00:00Zhttps://www.mdpi.com/2075-5309/11/11/549https://doaj.org/toc/2075-5309For a practical structural health monitoring (SHM) system, the traditional single objective methods for optimal sensor placement (OSP) cannot always obtain the optimal result of sensor deployment without sacrificing other targets, which creates obstacles to the efficient use of the sensors. This study mainly focuses on establishing a bi-objective optimization method to select the sensor placement positions. The practical significance of several single-objective criteria for OSP is firstly discussed, based on which a novel bi-objective optimization method is proposed based on the Pareto optimization process, and the corresponding objective functions are established. Furthermore, the non-dominated sorting genetic algorithm is introduced to obtain a series of the Pareto optimal solutions, from which the final solution can be determined based on a new defined membership degree index. Finally, a numerical example of a plane truss is applied to illustrate the proposed method. The Pareto optimization-based bi-objective OSP framework presented in this study could be well suited for solving the problem of multi-objective OSP, which can effectively improve the efficiency of the limited sensors in SHM system.Shao-Xiao NongDong-Hui YangTing-Hua YiMDPI AGarticlestructural health monitoringoptimal sensor placementbi-objective optimizationPareto optimizationnon-dominated sorting genetic algorithmBuilding constructionTH1-9745ENBuildings, Vol 11, Iss 549, p 549 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	structural health monitoring optimal sensor placement bi-objective optimization Pareto optimization non-dominated sorting genetic algorithm Building construction TH1-9745
spellingShingle	structural health monitoring optimal sensor placement bi-objective optimization Pareto optimization non-dominated sorting genetic algorithm Building construction TH1-9745 Shao-Xiao Nong Dong-Hui Yang Ting-Hua Yi Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
description	For a practical structural health monitoring (SHM) system, the traditional single objective methods for optimal sensor placement (OSP) cannot always obtain the optimal result of sensor deployment without sacrificing other targets, which creates obstacles to the efficient use of the sensors. This study mainly focuses on establishing a bi-objective optimization method to select the sensor placement positions. The practical significance of several single-objective criteria for OSP is firstly discussed, based on which a novel bi-objective optimization method is proposed based on the Pareto optimization process, and the corresponding objective functions are established. Furthermore, the non-dominated sorting genetic algorithm is introduced to obtain a series of the Pareto optimal solutions, from which the final solution can be determined based on a new defined membership degree index. Finally, a numerical example of a plane truss is applied to illustrate the proposed method. The Pareto optimization-based bi-objective OSP framework presented in this study could be well suited for solving the problem of multi-objective OSP, which can effectively improve the efficiency of the limited sensors in SHM system.
format	article
author	Shao-Xiao Nong Dong-Hui Yang Ting-Hua Yi
author_facet	Shao-Xiao Nong Dong-Hui Yang Ting-Hua Yi
author_sort	Shao-Xiao Nong
title	Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
title_short	Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
title_full	Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
title_fullStr	Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
title_full_unstemmed	Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring
title_sort	pareto-based bi-objective optimization method of sensor placement in structural health monitoring
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/17917874d3d44a6ba6fcc34f90bd7bf9
work_keys_str_mv	AT shaoxiaonong paretobasedbiobjectiveoptimizationmethodofsensorplacementinstructuralhealthmonitoring AT donghuiyang paretobasedbiobjectiveoptimizationmethodofsensorplacementinstructuralhealthmonitoring AT tinghuayi paretobasedbiobjectiveoptimizationmethodofsensorplacementinstructuralhealthmonitoring
_version_	1718412760705925120

Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring

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