Assessment of magnetoelastic resonance parameters retrieval for sensor applications

Magnetoelastic resonance sensors have been widely used for several sensing applications, as their resonance behavior is very sensitive to different external factors and they can be operated remotely. Nevertheless, under some working conditions, such as when the sensor signal is low, has considerable...

Descripción completa

Detalles Bibliográficos
Autores: Sisniega Soriano, Beatriz, Barandiarán García, José Manuel, Gutiérrez Etxebarria, Jon, García Arribas, Alfredo
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/68198
Acceso en línea:http://hdl.handle.net/10810/68198
Access Level:acceso abierto
Palabra clave:magnetoelastic resonance
resonance curve fitting
magnetoelastic sensor
id ES_7ea1b0aba8f3d0369e956db9c7aada77
oai_identifier_str oai:addi.ehu.eus:10810/68198
network_acronym_str ES
network_name_str España
repository_id_str
spelling Assessment of magnetoelastic resonance parameters retrieval for sensor applicationsSisniega Soriano, BeatrizBarandiarán García, José ManuelGutiérrez Etxebarria, JonGarcía Arribas, Alfredomagnetoelastic resonanceresonance curve fittingmagnetoelastic sensorMagnetoelastic resonance sensors have been widely used for several sensing applications, as their resonance behavior is very sensitive to different external factors and they can be operated remotely. Nevertheless, under some working conditions, such as when the sensor signal is low, has considerable noise, or the medium viscosity causes damping of the signal, the accuracy in obtaining the parameters that characterize the resonance response of these sensors by direct methods can decrease. The aim of this work is to improve the performance of magnetoelastic sensors through the use of numerical fittings of the resonance curves to obtain accurately the resonance parameters used for detection. The capability of these numerical fittings to retrieve the parameters when signals present different levels of noise is evaluated, and the accuracy of this fitting method is compared with the precision of classical direct methods.This work was supported by the Basque Government under µ4IIoT project (KK-2021/00082, Elkartek program), the University Basque Research Groups Funding (IT1479-22) and the PFI Grant PRE_2021_2_0145.Elsevier202420242023info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/68198reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://www.sciencedirect.com/science/article/pii/S0304885322010988info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/3.0/es/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).Atribución-NoComercial-SinDerivadas 3.0 Españaoai:addi.ehu.eus:10810/681982026-06-18T09:23:17Z
dc.title.none.fl_str_mv Assessment of magnetoelastic resonance parameters retrieval for sensor applications
title Assessment of magnetoelastic resonance parameters retrieval for sensor applications
spellingShingle Assessment of magnetoelastic resonance parameters retrieval for sensor applications
Sisniega Soriano, Beatriz
magnetoelastic resonance
resonance curve fitting
magnetoelastic sensor
title_short Assessment of magnetoelastic resonance parameters retrieval for sensor applications
title_full Assessment of magnetoelastic resonance parameters retrieval for sensor applications
title_fullStr Assessment of magnetoelastic resonance parameters retrieval for sensor applications
title_full_unstemmed Assessment of magnetoelastic resonance parameters retrieval for sensor applications
title_sort Assessment of magnetoelastic resonance parameters retrieval for sensor applications
dc.creator.none.fl_str_mv Sisniega Soriano, Beatriz
Barandiarán García, José Manuel
Gutiérrez Etxebarria, Jon
García Arribas, Alfredo
author Sisniega Soriano, Beatriz
author_facet Sisniega Soriano, Beatriz
Barandiarán García, José Manuel
Gutiérrez Etxebarria, Jon
García Arribas, Alfredo
author_role author
author2 Barandiarán García, José Manuel
Gutiérrez Etxebarria, Jon
García Arribas, Alfredo
author2_role author
author
author
dc.subject.none.fl_str_mv magnetoelastic resonance
resonance curve fitting
magnetoelastic sensor
topic magnetoelastic resonance
resonance curve fitting
magnetoelastic sensor
description Magnetoelastic resonance sensors have been widely used for several sensing applications, as their resonance behavior is very sensitive to different external factors and they can be operated remotely. Nevertheless, under some working conditions, such as when the sensor signal is low, has considerable noise, or the medium viscosity causes damping of the signal, the accuracy in obtaining the parameters that characterize the resonance response of these sensors by direct methods can decrease. The aim of this work is to improve the performance of magnetoelastic sensors through the use of numerical fittings of the resonance curves to obtain accurately the resonance parameters used for detection. The capability of these numerical fittings to retrieve the parameters when signals present different levels of noise is evaluated, and the accuracy of this fitting method is compared with the precision of classical direct methods.
publishDate 2023
dc.date.none.fl_str_mv 2023
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/68198
url http://hdl.handle.net/10810/68198
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.sciencedirect.com/science/article/pii/S0304885322010988
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Atribución-NoComercial-SinDerivadas 3.0 España
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Atribución-NoComercial-SinDerivadas 3.0 España
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869411749730451456
score 15,301603

Similares en LA Referencia