abstract
In recent years, advancements in smart cities and multifunctional monitoring have driven new demands for shape reconstruction devices. Multicore fibers (MCFs) are increasingly used due to their parallel data transmission capabilities and multiparameter sensing potential. This paper presents a Rayleigh-scattering-based distributed sensing approach with MCFs for shape reconstruction under multiplanar disturbances. Optical Frequency-Domain Reflectometry (OFDR) is utilized to analyze four cores in a seven-core fiber, enabling shape reconstruction through cross-correlation of spectral responses relative to an unstrained reference. Two configurations are compared: Configuration 1, a spatially separated core arrangement enabling independent strain independent strain measurements to be analyzed with a Frenet-Serret frame modeling and Random Forest (RF) algorithms, achieving a high accuracy with a maximum error of 8.72 x 10-3 cm; and Configuration 2, a simplified approach analyzing all cores in the same OFDR channel, yielding a higher error of 0.27 cm when a RF algorithm was fed with features derived from the Rayleigh backscattered signal (loss amplitude, strain, spectral shift, and s-and p-polarization) measured by an optical backscatter reflectometer. Three protocols-pure bending, pure torsion, and combined bending/torsion-validate these configurations. The results emphasize this multifunctional MCF-based sensor system's potential for flexible, integrated shape reconstruction solutions.
keywords
ARRAY
subject category
Engineering; Instruments & Instrumentation
authors
Macedo, L; Frizera, A; Nedoma, J; Martinek, R; Marques, C; Leal-junior, A
our authors
Carlos Marques
Assistant ProfessorProjects
Collaboratory for Emerging Technologies, CoLab (EMERGING TECHNOLOGIES)
Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)
acknowledgements
This research is financed by FAPES (1004/2022 and 629/2022) , CNPq (440064/2022-8, 310709/2021-0 and 405336/2022-5) and FINEP (2784/20, 0036/21, 2132/22 and 0322/23) . The research was co-funded by the financial support of the European Union under the REFRESH - Research Excellence For REgion Sustainability and High--tech Industries project number CZ.10.03.01/00/22-003/0000048 via the Operational Programme Just Transition. This work was also supported by the Ministry of Education, Youth, and Sports of the Czech Republic conducted by the VSB-Technical University of Ostrava, under grant no. SP2025/039. This work was also developed within the scope of the projects CICECO (LA/P/0006/2020, UIDB/50011/2020 \ & UIDP/50011/2020) financed by national funds through the (Portuguese Science and Technology Foundation/MCTES (FCT I.P.) ) .