Adaptive filter feature identification for structural health monitoring in aeronautical panel
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/978-1-4419-9834-7_78 http://hdl.handle.net/11449/72604 |
Resumo: | This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc. |
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Adaptive filter feature identification for structural health monitoring in aeronautical panelOnline damage detectionRLS filterSmart structuresStructural health monitoringT-testAuto-regressiveDiscrete-timeFeature identificationHypothesis testsLaboratory testNonstationaryPiezoelectric sensorsRecursive least squaresSquare rootsStructural conditionStructural healthTest structureAdaptive filteringAdaptive filtersAerodynamicsAlgorithmsDamage detectionElectric filtersLinear systemsOnline systemsPiezoelectricityStructural dynamicsTestingThis paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.Paraná Western State University (UNIOESTE) Centro de Engenharias e Ciências Exatas (CECE) Itaipu Technological Park (PTI), Av. Tancredo Neves, no. 6731, 85856-970, Foz do Iguaçu, PRUNESP-São Paulo State University Department of Mechanical Engineering Grupo de Materials e Sistemas Inteligentes, Av. Brasil, n.56, Centro, 15385-000, Ilha Solteira, SPUNESP-São Paulo State University Department of Mechanical Engineering Grupo de Materials e Sistemas Inteligentes, Av. Brasil, n.56, Centro, 15385-000, Ilha Solteira, SPItaipu Technological Park (PTI)Universidade Estadual Paulista (Unesp)Da Silva, SamuelGonsalez, Camila Gianini [UNESP]Lopes Jr., Vicente [UNESP]2014-05-27T11:25:58Z2014-05-27T11:25:58Z2011-08-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject875-882http://dx.doi.org/10.1007/978-1-4419-9834-7_78Conference Proceedings of the Society for Experimental Mechanics Series, v. 3, n. PART 2, p. 875-882, 2011.2191-56442191-5652http://hdl.handle.net/11449/7260410.1007/978-1-4419-9834-7_782-s2.0-800514861461457178419328525Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengConference Proceedings of the Society for Experimental Mechanics Series0,232info:eu-repo/semantics/openAccess2024-07-04T20:06:35Zoai:repositorio.unesp.br:11449/72604Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:08:44.788198Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
title |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
spellingShingle |
Adaptive filter feature identification for structural health monitoring in aeronautical panel Da Silva, Samuel Online damage detection RLS filter Smart structures Structural health monitoring T-test Auto-regressive Discrete-time Feature identification Hypothesis tests Laboratory test Nonstationary Piezoelectric sensors Recursive least squares Square roots Structural condition Structural health Test structure Adaptive filtering Adaptive filters Aerodynamics Algorithms Damage detection Electric filters Linear systems Online systems Piezoelectricity Structural dynamics Testing |
title_short |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
title_full |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
title_fullStr |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
title_full_unstemmed |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
title_sort |
Adaptive filter feature identification for structural health monitoring in aeronautical panel |
author |
Da Silva, Samuel |
author_facet |
Da Silva, Samuel Gonsalez, Camila Gianini [UNESP] Lopes Jr., Vicente [UNESP] |
author_role |
author |
author2 |
Gonsalez, Camila Gianini [UNESP] Lopes Jr., Vicente [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Itaipu Technological Park (PTI) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Da Silva, Samuel Gonsalez, Camila Gianini [UNESP] Lopes Jr., Vicente [UNESP] |
dc.subject.por.fl_str_mv |
Online damage detection RLS filter Smart structures Structural health monitoring T-test Auto-regressive Discrete-time Feature identification Hypothesis tests Laboratory test Nonstationary Piezoelectric sensors Recursive least squares Square roots Structural condition Structural health Test structure Adaptive filtering Adaptive filters Aerodynamics Algorithms Damage detection Electric filters Linear systems Online systems Piezoelectricity Structural dynamics Testing |
topic |
Online damage detection RLS filter Smart structures Structural health monitoring T-test Auto-regressive Discrete-time Feature identification Hypothesis tests Laboratory test Nonstationary Piezoelectric sensors Recursive least squares Square roots Structural condition Structural health Test structure Adaptive filtering Adaptive filters Aerodynamics Algorithms Damage detection Electric filters Linear systems Online systems Piezoelectricity Structural dynamics Testing |
description |
This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-08-15 2014-05-27T11:25:58Z 2014-05-27T11:25:58Z |
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 |
http://dx.doi.org/10.1007/978-1-4419-9834-7_78 Conference Proceedings of the Society for Experimental Mechanics Series, v. 3, n. PART 2, p. 875-882, 2011. 2191-5644 2191-5652 http://hdl.handle.net/11449/72604 10.1007/978-1-4419-9834-7_78 2-s2.0-80051486146 1457178419328525 |
url |
http://dx.doi.org/10.1007/978-1-4419-9834-7_78 http://hdl.handle.net/11449/72604 |
identifier_str_mv |
Conference Proceedings of the Society for Experimental Mechanics Series, v. 3, n. PART 2, p. 875-882, 2011. 2191-5644 2191-5652 10.1007/978-1-4419-9834-7_78 2-s2.0-80051486146 1457178419328525 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Conference Proceedings of the Society for Experimental Mechanics Series 0,232 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
875-882 |
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_ |
1808128760884494336 |