On the detection of a nonlinear damage in an uncertain nonlinear beam using stochastic Volterra series
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1808129472496402432 |