Abstract
This work introduces an innovative capillary (hollow core) optical fiber-based sensor designed to measure turbidity using light reflection along its cladding. The structure consists of two capillary sections surrounding a single-mode fiber (SMF) section. The final capillary has been optimized to maximize light interaction with the external liquid. Experimentation includes data collection from different turbidity levels using the reflected light spectrum. Machine learning has been implemented to improve the measuring by exploring the effectiveness of various algorithms and neural network architectures in achieving a good root mean square error. We have obtained a maximum testing error of 5.88% NTU.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.
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Acknowledgments
Authors want to thanks to Armando Rodriguez and Arturo Sanchez for their helpful discussions.
Funding
This work was supported by MCIN/AEI/https://doi.org/10.13039/501100011033 and FEDER “A way to make Europe” under Grant PID2022-137269OB-C21.
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Vanegas-Tenezaca, E., Correa Serrano, A.I., Galarza, M. et al. Capillary-based optical fiber sensor for turbidity measurement. Sci Rep (2026). https://doi.org/10.1038/s41598-026-47586-4
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DOI: https://doi.org/10.1038/s41598-026-47586-4
