Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/173738 |
Resumo: | The consideration of nonlinearities in mechanical structures is a question of high importance because several common features as joints, large displacements and backlash may give rise to these kinds of phenomena. However, nonlinear tools for the area of structural dynamics are still not consolidated and need further research effort. In this sense, the Volterra series is an interesting mathematical framework to deal with nonlinear dynamics since it is a clear generalization of the linear convolution for weakly nonlinear systems. Unfortunately, the main drawback of this non-parametric model is the need of a large number of terms for accurately identifying the system, but it can be overcomed by expanding the Volterra kernels with orthonormal basis functions. In this paper, this technique is used to identify a Volterra model of a nonlinear buckled beam and the kernels are used for the detection of the nonlinear behavior of the structure. The main advantages and drawbacks of the proposed methodology are highlighted in the final remarks of the paper. |
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Non-parametric identification of a non-linear buckled beam using discrete-time Volterra SeriesDetection of nonlinearitiesNonlinear buckled beamOrthonormal basis functionVolterra seriesThe consideration of nonlinearities in mechanical structures is a question of high importance because several common features as joints, large displacements and backlash may give rise to these kinds of phenomena. However, nonlinear tools for the area of structural dynamics are still not consolidated and need further research effort. In this sense, the Volterra series is an interesting mathematical framework to deal with nonlinear dynamics since it is a clear generalization of the linear convolution for weakly nonlinear systems. Unfortunately, the main drawback of this non-parametric model is the need of a large number of terms for accurately identifying the system, but it can be overcomed by expanding the Volterra kernels with orthonormal basis functions. In this paper, this technique is used to identify a Volterra model of a nonlinear buckled beam and the kernels are used for the detection of the nonlinear behavior of the structure. The main advantages and drawbacks of the proposed methodology are highlighted in the final remarks of the paper.Departamento de Engenharia Mecânica Faculdade de Engenharia de Ilha Solteira UNESP - Univ Estadual Paulista, Av. Brasil 56Departamento de Engenharia Mecânica Faculdade de Engenharia de Ilha Solteira UNESP - Univ Estadual Paulista, Av. Brasil 56Universidade Estadual Paulista (Unesp)Hansen, Cristian [UNESP]Shiki, Sidney Bruce [UNESP]Lopes, Vicente [UNESP]Da Silva, Samuel [UNESP]2018-12-11T17:07:31Z2018-12-11T17:07:31Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2013-2018Proceedings of the International Conference on Structural Dynamic , EURODYN, v. 2014-January, p. 2013-2018.2311-9020http://hdl.handle.net/11449/1737382-s2.0-84994454808Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the International Conference on Structural Dynamic , EURODYN0,165info:eu-repo/semantics/openAccess2024-07-04T20:06:43Zoai:repositorio.unesp.br:11449/173738Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:27:15.019601Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
title |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
spellingShingle |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series Hansen, Cristian [UNESP] Detection of nonlinearities Nonlinear buckled beam Orthonormal basis function Volterra series |
title_short |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
title_full |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
title_fullStr |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
title_full_unstemmed |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
title_sort |
Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series |
author |
Hansen, Cristian [UNESP] |
author_facet |
Hansen, Cristian [UNESP] Shiki, Sidney Bruce [UNESP] Lopes, Vicente [UNESP] Da Silva, Samuel [UNESP] |
author_role |
author |
author2 |
Shiki, Sidney Bruce [UNESP] Lopes, Vicente [UNESP] Da Silva, Samuel [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Hansen, Cristian [UNESP] Shiki, Sidney Bruce [UNESP] Lopes, Vicente [UNESP] Da Silva, Samuel [UNESP] |
dc.subject.por.fl_str_mv |
Detection of nonlinearities Nonlinear buckled beam Orthonormal basis function Volterra series |
topic |
Detection of nonlinearities Nonlinear buckled beam Orthonormal basis function Volterra series |
description |
The consideration of nonlinearities in mechanical structures is a question of high importance because several common features as joints, large displacements and backlash may give rise to these kinds of phenomena. However, nonlinear tools for the area of structural dynamics are still not consolidated and need further research effort. In this sense, the Volterra series is an interesting mathematical framework to deal with nonlinear dynamics since it is a clear generalization of the linear convolution for weakly nonlinear systems. Unfortunately, the main drawback of this non-parametric model is the need of a large number of terms for accurately identifying the system, but it can be overcomed by expanding the Volterra kernels with orthonormal basis functions. In this paper, this technique is used to identify a Volterra model of a nonlinear buckled beam and the kernels are used for the detection of the nonlinear behavior of the structure. The main advantages and drawbacks of the proposed methodology are highlighted in the final remarks of the paper. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-01 2018-12-11T17:07:31Z 2018-12-11T17:07:31Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Proceedings of the International Conference on Structural Dynamic , EURODYN, v. 2014-January, p. 2013-2018. 2311-9020 http://hdl.handle.net/11449/173738 2-s2.0-84994454808 |
identifier_str_mv |
Proceedings of the International Conference on Structural Dynamic , EURODYN, v. 2014-January, p. 2013-2018. 2311-9020 2-s2.0-84994454808 |
url |
http://hdl.handle.net/11449/173738 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the International Conference on Structural Dynamic , EURODYN 0,165 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
2013-2018 |
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_ |
1808129522582683648 |