Curvature and temperature sensing based on liquid-core fiber Bragg grating

Zhi-hong Ke; Shu-hui Liu

doi:10.1117/12.3032596

10 October 2024 Curvature and temperature sensing based on liquid-core fiber Bragg grating

Zhi-hong Ke, Shu-hui Liu

Proceedings Volume 13278, Seventh Global Intelligent Industry Conference (GIIC 2024); 132781K (2024) https://doi.org/10.1117/12.3032596
Event: Seventh Global Intelligent Industry Conference (GIIC 2024), 2024, Shenzhen, China

Abstract

A liquid core fiber Bragg grating (FBG) sensor is proposed for curvature and temperature sensing. The sensor isfabricated by inscribing two FBGs with different periods on both sides of the hollow-core fiber(HCF) using femtosecondlaser direct writing technique, and filling the hollow core with liquid. Due to the overlap of propagation modes formedby liquid fibre cores and the grating, the reflection spectrum of FBG exhibits two well-defined resonance peaks. Bendinginfluences the fibre gratings on both sides of the air core differently, causing the intensity of the reflection peaks of thegratings to change. In the small curvature range, Bragg grating close to and far from the direction of bendingarestretched and compressed respectively, thus the resonance peaks show opposite trends, which can be used to determinethe direction of bending. As the curvature further increases, bending loss is the dominating factor that affects thereflectivity, and the peak intensity exhibit a decrease response, with sensitivity of -2.15468 dB/m^-1and -1.93504 dB/m^-1 . The temperature sensitivity of the FBG is improved due to the presence of the liquid with high thermo-optic coefficient, and blue shift response is observed when temperature is increased, with sensitivities of 86.67 pm/℃and 66.61pm/℃, respectively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhi-hong Ke and Shu-hui Liu "Curvature and temperature sensing based on liquid-core fiber Bragg grating", Proc. SPIE 13278, Seventh Global Intelligent Industry Conference (GIIC 2024), 132781K (10 October 2024); https://doi.org/10.1117/12.3032596

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