Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments

Detalhes bibliográficos
Autor(a) principal: de Castro, Bruno Albuquerque [UNESP]
Data de Publicação: 2019
Outros Autores: Baptista, Fabricio Guimarães [UNESP], Ciampa, Francesco
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.ymssp.2019.02.034
http://hdl.handle.net/11449/188750
Resumo: Structural health monitoring (SHM) systems have been extensively studied in recent decades to determine the health statuses of mechanical, naval and aerospace engineering components. Currently, one of the most promising non-destructive tests for the detection of structural damage is the electromechanical impedance (EMI) technique, which uses low-cost, surface-bonded piezoelectric transducers operating both as sensors and actuators. Although many studies have reported the effectiveness of the EMI method, numerous practical issues, such as signal noise effects caused by environmental conditions, may severely affect the detection and quantification of damage. Therefore, this paper presents a comparative analysis of three signal processing techniques used in the context of the EMI method, which have the potential to enhance the detection of structural damage under environmental signal noise effects. These signal analysis methods include (i) damage indices, such as the correlation coefficient deviation metric, computed directly on impedance signatures; (ii) the wavelet transform computed on transducer response signals in the time domain; and (iii) a novel approach of damage feature extraction in the EMI method based on the Hinkley criterion. Experimental tests were carried out to analyse the three signal processing techniques on a damaged aerospace composite carbon fibre structure subjected to various signal noise levels. The experimental results revealed that conventional damage indices and wavelet transform were significantly affected by noise, whereas the proposed approach based on the Hinkley criterion was more effective for detecting damage in noisy environments.
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spelling Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environmentsCarbon fibreHinkley criterionImpedanceSHMSignal processingWavelet transformStructural health monitoring (SHM) systems have been extensively studied in recent decades to determine the health statuses of mechanical, naval and aerospace engineering components. Currently, one of the most promising non-destructive tests for the detection of structural damage is the electromechanical impedance (EMI) technique, which uses low-cost, surface-bonded piezoelectric transducers operating both as sensors and actuators. Although many studies have reported the effectiveness of the EMI method, numerous practical issues, such as signal noise effects caused by environmental conditions, may severely affect the detection and quantification of damage. Therefore, this paper presents a comparative analysis of three signal processing techniques used in the context of the EMI method, which have the potential to enhance the detection of structural damage under environmental signal noise effects. These signal analysis methods include (i) damage indices, such as the correlation coefficient deviation metric, computed directly on impedance signatures; (ii) the wavelet transform computed on transducer response signals in the time domain; and (iii) a novel approach of damage feature extraction in the EMI method based on the Hinkley criterion. Experimental tests were carried out to analyse the three signal processing techniques on a damaged aerospace composite carbon fibre structure subjected to various signal noise levels. The experimental results revealed that conventional damage indices and wavelet transform were significantly affected by noise, whereas the proposed approach based on the Hinkley criterion was more effective for detecting damage in noisy environments.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)São Paulo State University (UNESP) School of Engineering Bauru Department of Electrical EngineeringUniversity of Surrey Department of Mechanical Engineering SciencesSão Paulo State University (UNESP) School of Engineering Bauru Department of Electrical EngineeringUniversidade Estadual Paulista (Unesp)University of Surreyde Castro, Bruno Albuquerque [UNESP]Baptista, Fabricio Guimarães [UNESP]Ciampa, Francesco2019-10-06T16:18:05Z2019-10-06T16:18:05Z2019-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article326-340http://dx.doi.org/10.1016/j.ymssp.2019.02.034Mechanical Systems and Signal Processing, v. 126, p. 326-340.1096-12160888-3270http://hdl.handle.net/11449/18875010.1016/j.ymssp.2019.02.0342-s2.0-8506180986924263302049198140000-0002-1200-4354Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMechanical Systems and Signal Processinginfo:eu-repo/semantics/openAccess2024-06-28T13:34:25Zoai:repositorio.unesp.br:11449/188750Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:28:33.695634Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
title Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
spellingShingle Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
de Castro, Bruno Albuquerque [UNESP]
Carbon fibre
Hinkley criterion
Impedance
SHM
Signal processing
Wavelet transform
title_short Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
title_full Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
title_fullStr Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
title_full_unstemmed Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
title_sort Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
author de Castro, Bruno Albuquerque [UNESP]
author_facet de Castro, Bruno Albuquerque [UNESP]
Baptista, Fabricio Guimarães [UNESP]
Ciampa, Francesco
author_role author
author2 Baptista, Fabricio Guimarães [UNESP]
Ciampa, Francesco
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
University of Surrey
dc.contributor.author.fl_str_mv de Castro, Bruno Albuquerque [UNESP]
Baptista, Fabricio Guimarães [UNESP]
Ciampa, Francesco
dc.subject.por.fl_str_mv Carbon fibre
Hinkley criterion
Impedance
SHM
Signal processing
Wavelet transform
topic Carbon fibre
Hinkley criterion
Impedance
SHM
Signal processing
Wavelet transform
description Structural health monitoring (SHM) systems have been extensively studied in recent decades to determine the health statuses of mechanical, naval and aerospace engineering components. Currently, one of the most promising non-destructive tests for the detection of structural damage is the electromechanical impedance (EMI) technique, which uses low-cost, surface-bonded piezoelectric transducers operating both as sensors and actuators. Although many studies have reported the effectiveness of the EMI method, numerous practical issues, such as signal noise effects caused by environmental conditions, may severely affect the detection and quantification of damage. Therefore, this paper presents a comparative analysis of three signal processing techniques used in the context of the EMI method, which have the potential to enhance the detection of structural damage under environmental signal noise effects. These signal analysis methods include (i) damage indices, such as the correlation coefficient deviation metric, computed directly on impedance signatures; (ii) the wavelet transform computed on transducer response signals in the time domain; and (iii) a novel approach of damage feature extraction in the EMI method based on the Hinkley criterion. Experimental tests were carried out to analyse the three signal processing techniques on a damaged aerospace composite carbon fibre structure subjected to various signal noise levels. The experimental results revealed that conventional damage indices and wavelet transform were significantly affected by noise, whereas the proposed approach based on the Hinkley criterion was more effective for detecting damage in noisy environments.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-06T16:18:05Z
2019-10-06T16:18:05Z
2019-07-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.ymssp.2019.02.034
Mechanical Systems and Signal Processing, v. 126, p. 326-340.
1096-1216
0888-3270
http://hdl.handle.net/11449/188750
10.1016/j.ymssp.2019.02.034
2-s2.0-85061809869
2426330204919814
0000-0002-1200-4354
url http://dx.doi.org/10.1016/j.ymssp.2019.02.034
http://hdl.handle.net/11449/188750
identifier_str_mv Mechanical Systems and Signal Processing, v. 126, p. 326-340.
1096-1216
0888-3270
10.1016/j.ymssp.2019.02.034
2-s2.0-85061809869
2426330204919814
0000-0002-1200-4354
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Mechanical Systems and Signal Processing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 326-340
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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