Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/137761 |
Resumo: | Nonlinear structures are frequent in structural dynamics, specially considering screwed components, with joints, clearance or flexible components presenting large displacements. In this sense the monitoring of systems based on classical linear methods, as the ones based on modal parameters, can drastically fail to characterize nonlinear effects. This thesis proposed the use of Volterra series for nonlinear system identification aiming applications in damage detection and parameter quantification. The property of this model of representing the linear and nonlinear components of the response of a system was used to formulate damage features to make clear the need of nonlinear modeling. Also metrics based on the linear and nonlinear residues of the terms of the Volterra model were employed to identify parametric models of the structure. The proposed methodologies are illustrated in experimental setups to show the relevance of nonlinear phenomena in the structural health monitoring. |
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Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problemsAplicação de séries de Volterra na identificação de sistemas mecânicos não lineares e em problemas de detecção e quantificação de danosNonlinear structuresStructural health monitoringVolterra modelsKautz filtersNonlinear model updatingEstruturas não linearesMonitoramento de integridade estruturalModelos de VolterraFiltros de KautzAjuste de modelos não linearesNonlinear structures are frequent in structural dynamics, specially considering screwed components, with joints, clearance or flexible components presenting large displacements. In this sense the monitoring of systems based on classical linear methods, as the ones based on modal parameters, can drastically fail to characterize nonlinear effects. This thesis proposed the use of Volterra series for nonlinear system identification aiming applications in damage detection and parameter quantification. The property of this model of representing the linear and nonlinear components of the response of a system was used to formulate damage features to make clear the need of nonlinear modeling. Also metrics based on the linear and nonlinear residues of the terms of the Volterra model were employed to identify parametric models of the structure. The proposed methodologies are illustrated in experimental setups to show the relevance of nonlinear phenomena in the structural health monitoring.Estruturas com comportamento não-linear são frequentes em dinâmica estrutural, principalmente considerando componentes parafusados, com juntas, folgas ou estruturas flexíveis sujeitas à grandes deslocamentos. Desse modo, o monitoramento de estruturas com métodos lineares clássicos, como os baseados em parâmetros modais, podem falhar drasticamente em caracterizar efeitos não-lineares. Neste trabalho foi proposta a utilização de séries de Volterra para identificação de sistemas mecânicos não-lineares em aplicações de detecção de danos e quantificação de parâmetros. A propriedade deste modelo de representar separadamente os componentes de resposta linear e não-linear do sistema foi aplicada para se construir índices de dano que evidenciam a necessidade de modelagem não-linear. Além disso métricas de resíduo linear e não-linear dos termos do modelo de Volterra são empregadas para identificar modelos paramétricos da estrutura. As metodologias propostas são ilustradas em bancadas experimentais de modo a evidenciar a importância de fenômenos não-lineares para o monitoramento de estruturas.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP: 2012/04757-6FAPESP: 2013/25148-0FAPESP: 2012/21195-1FAPESP: 2015/03560-2Universidade Estadual Paulista (Unesp)Silva, Samuel da [UNESP]Kerschen, Gaëtan [UNESP]Universidade Estadual Paulista (Unesp)Shiki, Sidney Bruce [UNESP]2016-04-05T14:42:00Z2016-04-05T14:42:00Z2016-03-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://hdl.handle.net/11449/13776100087269633004099082P21457178419328525enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESP2024-08-05T18:39:28Zoai:repositorio.unesp.br:11449/137761Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:39:28Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems Aplicação de séries de Volterra na identificação de sistemas mecânicos não lineares e em problemas de detecção e quantificação de danos |
title |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
spellingShingle |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems Shiki, Sidney Bruce [UNESP] Nonlinear structures Structural health monitoring Volterra models Kautz filters Nonlinear model updating Estruturas não lineares Monitoramento de integridade estrutural Modelos de Volterra Filtros de Kautz Ajuste de modelos não lineares |
title_short |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
title_full |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
title_fullStr |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
title_full_unstemmed |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
title_sort |
Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems |
author |
Shiki, Sidney Bruce [UNESP] |
author_facet |
Shiki, Sidney Bruce [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Silva, Samuel da [UNESP] Kerschen, Gaëtan [UNESP] Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Shiki, Sidney Bruce [UNESP] |
dc.subject.por.fl_str_mv |
Nonlinear structures Structural health monitoring Volterra models Kautz filters Nonlinear model updating Estruturas não lineares Monitoramento de integridade estrutural Modelos de Volterra Filtros de Kautz Ajuste de modelos não lineares |
topic |
Nonlinear structures Structural health monitoring Volterra models Kautz filters Nonlinear model updating Estruturas não lineares Monitoramento de integridade estrutural Modelos de Volterra Filtros de Kautz Ajuste de modelos não lineares |
description |
Nonlinear structures are frequent in structural dynamics, specially considering screwed components, with joints, clearance or flexible components presenting large displacements. In this sense the monitoring of systems based on classical linear methods, as the ones based on modal parameters, can drastically fail to characterize nonlinear effects. This thesis proposed the use of Volterra series for nonlinear system identification aiming applications in damage detection and parameter quantification. The property of this model of representing the linear and nonlinear components of the response of a system was used to formulate damage features to make clear the need of nonlinear modeling. Also metrics based on the linear and nonlinear residues of the terms of the Volterra model were employed to identify parametric models of the structure. The proposed methodologies are illustrated in experimental setups to show the relevance of nonlinear phenomena in the structural health monitoring. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-04-05T14:42:00Z 2016-04-05T14:42:00Z 2016-03-04 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11449/137761 000872696 33004099082P2 1457178419328525 |
url |
http://hdl.handle.net/11449/137761 |
identifier_str_mv |
000872696 33004099082P2 1457178419328525 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.source.none.fl_str_mv |
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_ |
1808128189525917696 |