Multidirectional bending sensor using capillary fibers and machine learning for real-time applications
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 l...
| Autores: | , , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2025 |
| País: | España |
| Recursos: | Universidad Pública de Navarra |
| Repositório: | Academica-e. Repositorio Institucional de la Universidad Pública de Navarra |
| OAI Identifier: | oai:academica-e.unavarra.es:2454/54309 |
| Acesso em linha: | https://hdl.handle.net/2454/54309 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Bend Capillary fiber Curvature Machine learning Optical fiber sensor |
| Resumo: | 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. |
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