Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
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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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 |
|
_version_ |
1808129524111507456 |