On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series

Detalhes bibliográficos
Autor(a) principal: Villani, Luis GG [UNESP]
Data de Publicação: 2020
Outros Autores: da Silva, Samuel [UNESP], Cunha, Americo, Todd, Michael D
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1177/1475921719876086
http://hdl.handle.net/11449/199557
Resumo: In the present work, two issues that can complicate a damage detection process are considered: the uncertainties and the intrinsically nonlinear behavior. To deal with these issues, a stochastic version of the Volterra series is proposed as a baseline model, and novelty detection is applied to distinguish the condition of the structure between a reference baseline state (presumed “healthy”) and damaged. The studied system exhibits nonlinear behavior even in the reference condition, and it is exposed to a type of damage that causes the structure to display a nonlinear behavior with a different nature than the initial one. In addition, the uncertainties associated with data variation are taken into account in the application of the methodology. The results confirm that the monitoring of nonlinear coefficients and nonlinear components of the system response enables the method to detect the presence of the damage earlier than the application of some linear-based metrics. Besides that, the stochastic treatment enables the specification of a probabilistic interval of confidence for the system response in an uncertain ambient, thus providing more robust and reliable forecasts.
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spelling On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra seriesdamage detectionnonlinear behaviorstochastic Volterra modelUncertaintiesIn the present work, two issues that can complicate a damage detection process are considered: the uncertainties and the intrinsically nonlinear behavior. To deal with these issues, a stochastic version of the Volterra series is proposed as a baseline model, and novelty detection is applied to distinguish the condition of the structure between a reference baseline state (presumed “healthy”) and damaged. The studied system exhibits nonlinear behavior even in the reference condition, and it is exposed to a type of damage that causes the structure to display a nonlinear behavior with a different nature than the initial one. In addition, the uncertainties associated with data variation are taken into account in the application of the methodology. The results confirm that the monitoring of nonlinear coefficients and nonlinear components of the system response enables the method to detect the presence of the damage earlier than the application of some linear-based metrics. Besides that, the stochastic treatment enables the specification of a probabilistic interval of confidence for the system response in an uncertain ambient, thus providing more robust and reliable forecasts.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)Departamento de Engenharia Mecânica Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESPNucleus of Modeling and Experimentation with Computers (NUMERICO) Universidade do Estado do Rio de Janeiro (UERJ)Department of Structural Engineering University of California San Diego (UCSD), La JollaDepartamento de Engenharia Mecânica Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESPCAPES: 001FAPESP: 2012/09135-3FAPESP: 2015/25676-2FAPESP: 2017/15512-8FAPESP: 2017/24977-4CNPq: 307520/2016-1FAPERJ: E-26/010.000.805/2018FAPERJ: E-26/010.002.178/2015Universidade Estadual Paulista (Unesp)Universidade do Estado do Rio de Janeiro (UERJ)University of California San Diego (UCSD)Villani, Luis GG [UNESP]da Silva, Samuel [UNESP]Cunha, AmericoTodd, Michael D2020-12-12T01:43:10Z2020-12-12T01:43:10Z2020-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1137-1150http://dx.doi.org/10.1177/1475921719876086Structural Health Monitoring, v. 19, n. 4, p. 1137-1150, 2020.1741-31681475-9217http://hdl.handle.net/11449/19955710.1177/14759217198760862-s2.0-85074027848Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengStructural Health Monitoringinfo:eu-repo/semantics/openAccess2024-07-04T20:06:25Zoai:repositorio.unesp.br:11449/199557Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:54:35.907371Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
title On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
spellingShingle On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
Villani, Luis GG [UNESP]
damage detection
nonlinear behavior
stochastic Volterra model
Uncertainties
title_short On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
title_full On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
title_fullStr On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
title_full_unstemmed On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
title_sort On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
author Villani, Luis GG [UNESP]
author_facet Villani, Luis GG [UNESP]
da Silva, Samuel [UNESP]
Cunha, Americo
Todd, Michael D
author_role author
author2 da Silva, Samuel [UNESP]
Cunha, Americo
Todd, Michael D
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade do Estado do Rio de Janeiro (UERJ)
University of California San Diego (UCSD)
dc.contributor.author.fl_str_mv Villani, Luis GG [UNESP]
da Silva, Samuel [UNESP]
Cunha, Americo
Todd, Michael D
dc.subject.por.fl_str_mv damage detection
nonlinear behavior
stochastic Volterra model
Uncertainties
topic damage detection
nonlinear behavior
stochastic Volterra model
Uncertainties
description In the present work, two issues that can complicate a damage detection process are considered: the uncertainties and the intrinsically nonlinear behavior. To deal with these issues, a stochastic version of the Volterra series is proposed as a baseline model, and novelty detection is applied to distinguish the condition of the structure between a reference baseline state (presumed “healthy”) and damaged. The studied system exhibits nonlinear behavior even in the reference condition, and it is exposed to a type of damage that causes the structure to display a nonlinear behavior with a different nature than the initial one. In addition, the uncertainties associated with data variation are taken into account in the application of the methodology. The results confirm that the monitoring of nonlinear coefficients and nonlinear components of the system response enables the method to detect the presence of the damage earlier than the application of some linear-based metrics. Besides that, the stochastic treatment enables the specification of a probabilistic interval of confidence for the system response in an uncertain ambient, thus providing more robust and reliable forecasts.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T01:43:10Z
2020-12-12T01:43:10Z
2020-07-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1177/1475921719876086
Structural Health Monitoring, v. 19, n. 4, p. 1137-1150, 2020.
1741-3168
1475-9217
http://hdl.handle.net/11449/199557
10.1177/1475921719876086
2-s2.0-85074027848
url http://dx.doi.org/10.1177/1475921719876086
http://hdl.handle.net/11449/199557
identifier_str_mv Structural Health Monitoring, v. 19, n. 4, p. 1137-1150, 2020.
1741-3168
1475-9217
10.1177/1475921719876086
2-s2.0-85074027848
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Structural Health Monitoring
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1137-1150
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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