Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742020000100001 |
Resumo: | Abstract We present a general investigation of a Long-Period Grating (LPG) for transverse strain measurement. The transverse strain sensing characteristics, for instance, the load intensity and azimuthal angle, are analyzed with the data set generated by the LPG sensor and probed by artificial neural network (ANN). Furthermore, we evaluate and compare the predictive performance of the interrogation model considering the square correlation coefficient (R2), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results indicate that the ANN model could be successfully employed to estimate the load intensity and azimuthal angle using a single LPG sensor. |
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Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
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Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural NetworkArtificial neural networklong period gratingoptical fiber sensortransverse loadAbstract We present a general investigation of a Long-Period Grating (LPG) for transverse strain measurement. The transverse strain sensing characteristics, for instance, the load intensity and azimuthal angle, are analyzed with the data set generated by the LPG sensor and probed by artificial neural network (ANN). Furthermore, we evaluate and compare the predictive performance of the interrogation model considering the square correlation coefficient (R2), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results indicate that the ANN model could be successfully employed to estimate the load intensity and azimuthal angle using a single LPG sensor.Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo2020-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742020000100001Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.19 n.1 2020reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applicationsinstname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)instacron:SBMO10.1590/2179-10742020v19i11809info:eu-repo/semantics/openAccessBarino,F. O.Delgado,F. S.Santos,A. Bessa doseng2021-03-24T00:00:00Zoai:scielo:S2179-10742020000100001Revistahttp://www.jmoe.org/index.php/jmoe/indexONGhttps://old.scielo.br/oai/scielo-oai.php||editor_jmoe@sbmo.org.br2179-10742179-1074opendoar:2021-03-24T00:00Journal of Microwaves. Optoelectronics and Electromagnetic Applications - Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)false |
dc.title.none.fl_str_mv |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
title |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
spellingShingle |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network Barino,F. O. Artificial neural network long period grating optical fiber sensor transverse load |
title_short |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
title_full |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
title_fullStr |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
title_full_unstemmed |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
title_sort |
Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network |
author |
Barino,F. O. |
author_facet |
Barino,F. O. Delgado,F. S. Santos,A. Bessa dos |
author_role |
author |
author2 |
Delgado,F. S. Santos,A. Bessa dos |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Barino,F. O. Delgado,F. S. Santos,A. Bessa dos |
dc.subject.por.fl_str_mv |
Artificial neural network long period grating optical fiber sensor transverse load |
topic |
Artificial neural network long period grating optical fiber sensor transverse load |
description |
Abstract We present a general investigation of a Long-Period Grating (LPG) for transverse strain measurement. The transverse strain sensing characteristics, for instance, the load intensity and azimuthal angle, are analyzed with the data set generated by the LPG sensor and probed by artificial neural network (ANN). Furthermore, we evaluate and compare the predictive performance of the interrogation model considering the square correlation coefficient (R2), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results indicate that the ANN model could be successfully employed to estimate the load intensity and azimuthal angle using a single LPG sensor. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742020000100001 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742020000100001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2179-10742020v19i11809 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo |
publisher.none.fl_str_mv |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo |
dc.source.none.fl_str_mv |
Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.19 n.1 2020 reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applications instname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) instacron:SBMO |
instname_str |
Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) |
instacron_str |
SBMO |
institution |
SBMO |
reponame_str |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
collection |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
repository.name.fl_str_mv |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications - Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) |
repository.mail.fl_str_mv |
||editor_jmoe@sbmo.org.br |
_version_ |
1752122126664466432 |