Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity

Damage identification methods based on structural modal parameters are influenced by the structure form, number of measuring sensors and noise, resulting in insufficient modal data and low damage identification accuracy. The additional virtual mass method introduced in this study is based on the vir...

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Autores principales:	Qingxia Zhang, Dengzheng Xu, Jilin Hou, Łukasz Jankowski, Haiyan Wang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	structural health monitoring (SHM) damage identification virtual mass sparse constraint IOMP method Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/3830761809da4dda9cf0dfb2927291d0
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spelling	oai:doaj.org-article:3830761809da4dda9cf0dfb2927291d02021-11-11T15:13:01ZDamage Identification Method Using Additional Virtual Mass Based on Damage Sparsity10.3390/app1121101522076-3417https://doaj.org/article/3830761809da4dda9cf0dfb2927291d02021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10152https://doaj.org/toc/2076-3417Damage identification methods based on structural modal parameters are influenced by the structure form, number of measuring sensors and noise, resulting in insufficient modal data and low damage identification accuracy. The additional virtual mass method introduced in this study is based on the virtual deformation method for deriving the frequency-domain response equation of the virtual structure and identify its mode to expand the modal information of the original structure. Based on the initial condition assumption that the structural damage was sparse, the damage identification method based on sparsity with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>1</mn></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> norm of the damage-factor variation and the orthogonal matching pursuit (OMP) method based on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>0</mn></msub></mrow></semantics></math></inline-formula> norm were introduced. According to the characteristics of the additional virtual mass method, an improved OMP method (IOMP) was developed to improve the localization of optimal solution determined using the OMP method and the damage substructure selection process, analyze the damage in the entire structure globally, and improve damage identification accuracy. The accuracy and robustness of each damage identification method for multi-damage scenario were analyzed and verified through simulation and experiment.Qingxia ZhangDengzheng XuJilin HouŁukasz JankowskiHaiyan WangMDPI AGarticlestructural health monitoring (SHM)damage identificationvirtual masssparse constraintIOMP methodTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10152, p 10152 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	structural health monitoring (SHM) damage identification virtual mass sparse constraint IOMP method Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	structural health monitoring (SHM) damage identification virtual mass sparse constraint IOMP method Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Qingxia Zhang Dengzheng Xu Jilin Hou Łukasz Jankowski Haiyan Wang Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
description	Damage identification methods based on structural modal parameters are influenced by the structure form, number of measuring sensors and noise, resulting in insufficient modal data and low damage identification accuracy. The additional virtual mass method introduced in this study is based on the virtual deformation method for deriving the frequency-domain response equation of the virtual structure and identify its mode to expand the modal information of the original structure. Based on the initial condition assumption that the structural damage was sparse, the damage identification method based on sparsity with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>1</mn></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> norm of the damage-factor variation and the orthogonal matching pursuit (OMP) method based on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>l</mi><mn>0</mn></msub></mrow></semantics></math></inline-formula> norm were introduced. According to the characteristics of the additional virtual mass method, an improved OMP method (IOMP) was developed to improve the localization of optimal solution determined using the OMP method and the damage substructure selection process, analyze the damage in the entire structure globally, and improve damage identification accuracy. The accuracy and robustness of each damage identification method for multi-damage scenario were analyzed and verified through simulation and experiment.
format	article
author	Qingxia Zhang Dengzheng Xu Jilin Hou Łukasz Jankowski Haiyan Wang
author_facet	Qingxia Zhang Dengzheng Xu Jilin Hou Łukasz Jankowski Haiyan Wang
author_sort	Qingxia Zhang
title	Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
title_short	Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
title_full	Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
title_fullStr	Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
title_full_unstemmed	Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity
title_sort	damage identification method using additional virtual mass based on damage sparsity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3830761809da4dda9cf0dfb2927291d0
work_keys_str_mv	AT qingxiazhang damageidentificationmethodusingadditionalvirtualmassbasedondamagesparsity AT dengzhengxu damageidentificationmethodusingadditionalvirtualmassbasedondamagesparsity AT jilinhou damageidentificationmethodusingadditionalvirtualmassbasedondamagesparsity AT łukaszjankowski damageidentificationmethodusingadditionalvirtualmassbasedondamagesparsity AT haiyanwang damageidentificationmethodusingadditionalvirtualmassbasedondamagesparsity
_version_	1718436643731406848

Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity

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