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 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.