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Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses

This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of...

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Detalles Bibliográficos
Autores principales: Hou, Jilin, Wang, Pengfei, Jing, Tianyu, Jankowski, Łukasz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358787/
https://www.ncbi.nlm.nih.gov/pubmed/30634432
http://dx.doi.org/10.3390/s19020220
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author Hou, Jilin
Wang, Pengfei
Jing, Tianyu
Jankowski, Łukasz
author_facet Hou, Jilin
Wang, Pengfei
Jing, Tianyu
Jankowski, Łukasz
author_sort Hou, Jilin
collection PubMed
description This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of a storage tank is established to verify the proposed method; the relation between the added virtual masses and the sensitivity of the virtual structure is analyzed to determine the optimal mass and the corresponding frequency with the highest sensitivity with respect to potential damages. Thereupon, the damage can be localized and quantified by comparing the damage factors of substructures. Finally, an experimental study is conducted on a storage tank. The results confirm that the proposed method is feasible and practical, and that it can be applied for damage identification of storage tanks.
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spelling pubmed-63587872019-02-06 Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses Hou, Jilin Wang, Pengfei Jing, Tianyu Jankowski, Łukasz Sensors (Basel) Article This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of a storage tank is established to verify the proposed method; the relation between the added virtual masses and the sensitivity of the virtual structure is analyzed to determine the optimal mass and the corresponding frequency with the highest sensitivity with respect to potential damages. Thereupon, the damage can be localized and quantified by comparing the damage factors of substructures. Finally, an experimental study is conducted on a storage tank. The results confirm that the proposed method is feasible and practical, and that it can be applied for damage identification of storage tanks. MDPI 2019-01-09 /pmc/articles/PMC6358787/ /pubmed/30634432 http://dx.doi.org/10.3390/s19020220 Text en © 2019 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
Hou, Jilin
Wang, Pengfei
Jing, Tianyu
Jankowski, Łukasz
Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title_full Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title_fullStr Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title_full_unstemmed Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title_short Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses
title_sort experimental study for damage identification of storage tanks by adding virtual masses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358787/
https://www.ncbi.nlm.nih.gov/pubmed/30634432
http://dx.doi.org/10.3390/s19020220
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