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Optical Frequency Domain Reflectometry Based on Multilayer Perceptron

We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectr...

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Detalles Bibliográficos
Autores principales: Yin, Guolu, Zhu, Zhaohao, Liu, Min, Wang, Yu, Liu, Kaijun, Yu, Kuanglu, Zhu, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057011/
https://www.ncbi.nlm.nih.gov/pubmed/36991876
http://dx.doi.org/10.3390/s23063165
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author Yin, Guolu
Zhu, Zhaohao
Liu, Min
Wang, Yu
Liu, Kaijun
Yu, Kuanglu
Zhu, Tao
author_facet Yin, Guolu
Zhu, Zhaohao
Liu, Min
Wang, Yu
Liu, Kaijun
Yu, Kuanglu
Zhu, Tao
author_sort Yin, Guolu
collection PubMed
description We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.
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spelling pubmed-100570112023-03-30 Optical Frequency Domain Reflectometry Based on Multilayer Perceptron Yin, Guolu Zhu, Zhaohao Liu, Min Wang, Yu Liu, Kaijun Yu, Kuanglu Zhu, Tao Sensors (Basel) Article We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system. MDPI 2023-03-16 /pmc/articles/PMC10057011/ /pubmed/36991876 http://dx.doi.org/10.3390/s23063165 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yin, Guolu
Zhu, Zhaohao
Liu, Min
Wang, Yu
Liu, Kaijun
Yu, Kuanglu
Zhu, Tao
Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title_full Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title_fullStr Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title_full_unstemmed Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title_short Optical Frequency Domain Reflectometry Based on Multilayer Perceptron
title_sort optical frequency domain reflectometry based on multilayer perceptron
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057011/
https://www.ncbi.nlm.nih.gov/pubmed/36991876
http://dx.doi.org/10.3390/s23063165
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