NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure

Bibliographic Details
Main Author: Hansen, Cristian [UNESP]
Publication Date: 2015
Other Authors: Da Silva, Samuel [UNESP], Foltête, Emmanuel, Cogan, Scott
Format: Conference object
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://hdl.handle.net/11449/172095
Summary: The aim of this paper is to identify a nonlinear model using time responses obtained from a sine sweep excitation applied to a simplif ied solar array structure. The nonlinearity is mainly caused by impacts, gaps and friction between the clamped interfaces of adjacent panels. A nonparametric model is identif ied using Volterra series, where the kernels are expanded with Kautz functions in order to decrease the problems associated with convergence and number of samples. The multiple convolutions provided by the Volterra kernels are used to propose a decision criterion based on a threshold limit to detect the level of linear or nonlinear behavior. The approach is also able to separate the linear and nonlinear contributions of the measured total response. The application performed in the experimental setup demostrates that the proposed method is successful in identifying the main nonlinear mechanism involved, despite of the complicated nature of the nonlinear system investigated.
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spelling NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structureNonlinear system identificationNonlinearity detectionPanel structuresVolterra seriesThe aim of this paper is to identify a nonlinear model using time responses obtained from a sine sweep excitation applied to a simplif ied solar array structure. The nonlinearity is mainly caused by impacts, gaps and friction between the clamped interfaces of adjacent panels. A nonparametric model is identif ied using Volterra series, where the kernels are expanded with Kautz functions in order to decrease the problems associated with convergence and number of samples. The multiple convolutions provided by the Volterra kernels are used to propose a decision criterion based on a threshold limit to detect the level of linear or nonlinear behavior. The approach is also able to separate the linear and nonlinear contributions of the measured total response. The application performed in the experimental setup demostrates that the proposed method is successful in identifying the main nonlinear mechanism involved, despite of the complicated nature of the nonlinear system investigated.UNESP - Univ Estadual Paulista, Faculdade de Engenharia de Ilha Solteira, Departamento de Engenharia, Mecânica Av. Brasil 56Université de Franche-Comté, Institut FEMTO-ST, Département Mécanique Appliquée, 26, rue de l'EpitapheUNESP - Univ Estadual Paulista, Faculdade de Engenharia de Ilha Solteira, Departamento de Engenharia, Mecânica Av. Brasil 56Universidade Estadual Paulista (Unesp)Université de Franche-Comté, Institut FEMTO-ST, Département Mécanique AppliquéeHansen, Cristian [UNESP]Da Silva, Samuel [UNESP]Foltête, EmmanuelCogan, Scott2018-12-11T16:58:38Z2018-12-11T16:58:38Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject3014-3028COMPDYN 2015 - 5th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, p. 3014-3028.http://hdl.handle.net/11449/1720952-s2.0-84942278811Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCOMPDYN 2015 - 5th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineeringinfo:eu-repo/semantics/openAccess2024-07-04T20:06:42Zoai:repositorio.unesp.br:11449/172095Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-07-04T20:06:42Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
title NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
spellingShingle NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
Hansen, Cristian [UNESP]
Nonlinear system identification
Nonlinearity detection
Panel structures
Volterra series
title_short NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
title_full NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
title_fullStr NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
title_full_unstemmed NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
title_sort NOnlinearity detection and identification using discrete-time volterra series: Application to a solar array structure
author Hansen, Cristian [UNESP]
author_facet Hansen, Cristian [UNESP]
Da Silva, Samuel [UNESP]
Foltête, Emmanuel
Cogan, Scott
author_role author
author2 Da Silva, Samuel [UNESP]
Foltête, Emmanuel
Cogan, Scott
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Université de Franche-Comté, Institut FEMTO-ST, Département Mécanique Appliquée
dc.contributor.author.fl_str_mv Hansen, Cristian [UNESP]
Da Silva, Samuel [UNESP]
Foltête, Emmanuel
Cogan, Scott
dc.subject.por.fl_str_mv Nonlinear system identification
Nonlinearity detection
Panel structures
Volterra series
topic Nonlinear system identification
Nonlinearity detection
Panel structures
Volterra series
description The aim of this paper is to identify a nonlinear model using time responses obtained from a sine sweep excitation applied to a simplif ied solar array structure. The nonlinearity is mainly caused by impacts, gaps and friction between the clamped interfaces of adjacent panels. A nonparametric model is identif ied using Volterra series, where the kernels are expanded with Kautz functions in order to decrease the problems associated with convergence and number of samples. The multiple convolutions provided by the Volterra kernels are used to propose a decision criterion based on a threshold limit to detect the level of linear or nonlinear behavior. The approach is also able to separate the linear and nonlinear contributions of the measured total response. The application performed in the experimental setup demostrates that the proposed method is successful in identifying the main nonlinear mechanism involved, despite of the complicated nature of the nonlinear system investigated.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-12-11T16:58:38Z
2018-12-11T16:58:38Z
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 COMPDYN 2015 - 5th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, p. 3014-3028.
http://hdl.handle.net/11449/172095
2-s2.0-84942278811
identifier_str_mv COMPDYN 2015 - 5th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, p. 3014-3028.
2-s2.0-84942278811
url http://hdl.handle.net/11449/172095
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv COMPDYN 2015 - 5th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 3014-3028
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 repositoriounesp@unesp.br
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