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Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor
In this paper, Rayleigh backscattering sensors (RBS) are used to realize shape sensing of beam-like structures. Compared to conventional shape sensing systems based on fibre Bragg grating (FBG) sensors, RBS are capable of continuous lateral sensing. Compared to other types of distributed fibre optic...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411920/ https://www.ncbi.nlm.nih.gov/pubmed/32708071 http://dx.doi.org/10.3390/s20144040 |
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author | Xu, Cheng Sharif Khodaei, Zahra |
author_facet | Xu, Cheng Sharif Khodaei, Zahra |
author_sort | Xu, Cheng |
collection | PubMed |
description | In this paper, Rayleigh backscattering sensors (RBS) are used to realize shape sensing of beam-like structures. Compared to conventional shape sensing systems based on fibre Bragg grating (FBG) sensors, RBS are capable of continuous lateral sensing. Compared to other types of distributed fibre optic sensors (FOS), RBS have a higher spatial resolution. First, the RBS’s strain sensing accuracy is validated by an experiment comparing it with strain gauge response. After that, two shape sensing algorithms (the coordinate transformation method (CTM) and the strain-deflection equation method (SDEM)) based on the distributed FOS’ input strain data are derived. The algorithms are then optimized according to the distributed FOS’ features, to make it applicable to complex and/or combine loading situations while maintaining high reliability in case of sensing part malfunction. Numerical simulations are carried out to validate the algorithms’ accuracy and compare their accuracy. The simulation shows that compared to the FBG-based system, the RBS system has a better performance in configuring the shape when the structure is under complex loading. Finally, a validation experiment is conducted in which the RBS-based shape sensing system is used to configure the shape of a composite cantilever-beam-like specimen under concentrated loading. The result is then compared with the optical camera-measured shape. The experimental results show that both shape sensing algorithms predict the shape with high accuracy comparable with the optical camera result. |
format | Online Article Text |
id | pubmed-7411920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74119202020-08-25 Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor Xu, Cheng Sharif Khodaei, Zahra Sensors (Basel) Article In this paper, Rayleigh backscattering sensors (RBS) are used to realize shape sensing of beam-like structures. Compared to conventional shape sensing systems based on fibre Bragg grating (FBG) sensors, RBS are capable of continuous lateral sensing. Compared to other types of distributed fibre optic sensors (FOS), RBS have a higher spatial resolution. First, the RBS’s strain sensing accuracy is validated by an experiment comparing it with strain gauge response. After that, two shape sensing algorithms (the coordinate transformation method (CTM) and the strain-deflection equation method (SDEM)) based on the distributed FOS’ input strain data are derived. The algorithms are then optimized according to the distributed FOS’ features, to make it applicable to complex and/or combine loading situations while maintaining high reliability in case of sensing part malfunction. Numerical simulations are carried out to validate the algorithms’ accuracy and compare their accuracy. The simulation shows that compared to the FBG-based system, the RBS system has a better performance in configuring the shape when the structure is under complex loading. Finally, a validation experiment is conducted in which the RBS-based shape sensing system is used to configure the shape of a composite cantilever-beam-like specimen under concentrated loading. The result is then compared with the optical camera-measured shape. The experimental results show that both shape sensing algorithms predict the shape with high accuracy comparable with the optical camera result. MDPI 2020-07-21 /pmc/articles/PMC7411920/ /pubmed/32708071 http://dx.doi.org/10.3390/s20144040 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 Xu, Cheng Sharif Khodaei, Zahra Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title | Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title_full | Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title_fullStr | Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title_full_unstemmed | Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title_short | Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor |
title_sort | shape sensing with rayleigh backscattering fibre optic sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411920/ https://www.ncbi.nlm.nih.gov/pubmed/32708071 http://dx.doi.org/10.3390/s20144040 |
work_keys_str_mv | AT xucheng shapesensingwithrayleighbackscatteringfibreopticsensor AT sharifkhodaeizahra shapesensingwithrayleighbackscatteringfibreopticsensor |