Adaptive filter feature identification for structural health monitoring in aeronautical panel

Detalhes bibliográficos
Autor(a) principal: Da Silva, Samuel
Data de Publicação: 2011
Outros Autores: Gonsalez, Camila Gianini [UNESP], Lopes Jr., Vicente [UNESP]
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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spelling 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/openAccess2021-10-23T21:44:15Zoai:repositorio.unesp.br:11449/72604Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:44:15Repositório 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
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