Multidirectional bending sensor using capillary fibers and machine learning for real-time applications
| dc.contributor.author | Vanegas Tenezaca, Evelyn Dayanara | |
| dc.contributor.author | Galarza Galarza, Marko | |
| dc.contributor.author | Dauliat, Romain | |
| dc.contributor.author | Jamier, Raphael | |
| dc.contributor.author | Roy, Philippe | |
| dc.contributor.author | López-Amo Sáinz, Manuel | |
| dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
| dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.contributor.funder | Universidad Publica de Navarra / Nafarroako Unibertsitate Publikoa | |
| dc.date.accessioned | 2025-06-24T17:31:28Z | |
| dc.date.available | 2025-06-24T17:31:28Z | |
| dc.date.issued | 2025-02-25 | |
| dc.date.updated | 2025-06-24T17:17:07Z | |
| dc.description.abstract | In this article, the design and implementation of a bidirectional curvature sensor based on a fiber-optic interferometer are presented. The sensor structure was fabricated by fusing a capillary fiber fragment between single-mode fibers (SMFs), with the addition of a long end capillary to promote a long interferometric section, forming a Fabry-Perot (FP) cavity. Detailed analysis of the curvature data was carried out using machine learning techniques, allowing accurate classification of curvature in both directions of rotation. The experimental results showed excellent agreement (R2: 0.9998) with the predicted values. The sensor exhibits a maximum error of 1.9485°. This approach presents significant potential for applications requiring accurate real-time curvature measurements. | en |
| dc.description.sponsorship | This work was supported in part by CIN/AEI/10.13039/501100011033 and FEDER "AWay to Make Europe" under Project PID2022-137269OB and in part by MCIN/AEI/10.13039/501100011033 and European Union "Next Generation EU"/PRTR under Project TED2021-130378B. Open access funding provided by Universidad Publica de Navarra. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Vanegas-Tenezaca, E., Galarza, M., Dauliat, R., Jamier, R., Roy, P., Lopez-Amo, M. (2025) Multidirectional bending sensor using capillary fibers and machine learning for real-time applications. IEEE Sensors Journal, 25(8), 12734-12741. https://doi.org/10.1109/JSEN.2025.3543700. | |
| dc.identifier.doi | 10.1109/JSEN.2025.3543700 | |
| dc.identifier.issn | 1530-437X | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/54309 | |
| dc.language.iso | eng | |
| dc.publisher | IEEE | |
| dc.relation.ispartof | IEEE Sensors Journal 25(8), 2025, 12734-12741 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-137269OB-C21/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI//TED2021-130378B/ | |
| dc.relation.publisherversion | https://doi.org/10.1109/JSEN.2025.3543700 | |
| dc.rights | © 2025 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Bend | en |
| dc.subject | Capillary fiber | en |
| dc.subject | Curvature | en |
| dc.subject | Machine learning | en |
| dc.subject | Optical fiber sensor | en |
| dc.title | Multidirectional bending sensor using capillary fibers and machine learning for real-time applications | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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