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Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine

The fiber Bragg grating (FBG) sensor calibration process is critical for optimizing performance. Real-time dynamic calibration is essential to improve the measured accuracy of the sensor. In this paper, we present a dynamic calibration method for FBG sensor temperature measurement, utilizing the onl...

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Detalles Bibliográficos
Autores principales: Shang, Qiufeng, Qin, Wenjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181166/
https://www.ncbi.nlm.nih.gov/pubmed/32224936
http://dx.doi.org/10.3390/s20071840
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author Shang, Qiufeng
Qin, Wenjie
author_facet Shang, Qiufeng
Qin, Wenjie
author_sort Shang, Qiufeng
collection PubMed
description The fiber Bragg grating (FBG) sensor calibration process is critical for optimizing performance. Real-time dynamic calibration is essential to improve the measured accuracy of the sensor. In this paper, we present a dynamic calibration method for FBG sensor temperature measurement, utilizing the online sequential extreme learning machine (OS-ELM). During the measurement process, the calibration model is continuously updated instead of retrained, which can reduce tedious calculations and improve the predictive speed. Polynomial fitting, a back propagation (BP) network, and a radial basis function (RBF) network were compared, and the results showed the dynamic method not only had a better generalization performance but also had a faster learning process. The dynamic calibration enabled the real-time measured data of the FBG sensor to input calibration models as online learning samples continuously, and could solve the insufficient coverage problem of static calibration training samples, so as to improve the long-term stability, accuracy of prediction, and generalization ability of the FBG sensor.
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spelling pubmed-71811662020-04-28 Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine Shang, Qiufeng Qin, Wenjie Sensors (Basel) Article The fiber Bragg grating (FBG) sensor calibration process is critical for optimizing performance. Real-time dynamic calibration is essential to improve the measured accuracy of the sensor. In this paper, we present a dynamic calibration method for FBG sensor temperature measurement, utilizing the online sequential extreme learning machine (OS-ELM). During the measurement process, the calibration model is continuously updated instead of retrained, which can reduce tedious calculations and improve the predictive speed. Polynomial fitting, a back propagation (BP) network, and a radial basis function (RBF) network were compared, and the results showed the dynamic method not only had a better generalization performance but also had a faster learning process. The dynamic calibration enabled the real-time measured data of the FBG sensor to input calibration models as online learning samples continuously, and could solve the insufficient coverage problem of static calibration training samples, so as to improve the long-term stability, accuracy of prediction, and generalization ability of the FBG sensor. MDPI 2020-03-26 /pmc/articles/PMC7181166/ /pubmed/32224936 http://dx.doi.org/10.3390/s20071840 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shang, Qiufeng
Qin, Wenjie
Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title_full Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title_fullStr Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title_full_unstemmed Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title_short Fiber Bragg Grating Dynamic Calibration Based on Online Sequential Extreme Learning Machine
title_sort fiber bragg grating dynamic calibration based on online sequential extreme learning machine
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181166/
https://www.ncbi.nlm.nih.gov/pubmed/32224936
http://dx.doi.org/10.3390/s20071840
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