Seven-core fiber spatial multiplexing refractometer based on convolutional neural networks

Hongjie Cao; Huan Liu; Jiajun He; Yanqing Qiu; Bangning Mao; Yanlong Meng; Yanghui Li; Juan Kang; Le Wang; Yi Li

doi:10.1117/12.3021942

25 January 2024 Seven-core fiber spatial multiplexing refractometer based on convolutional neural networks

Hongjie Cao, Huan Liu, Jiajun He, Yanqing Qiu, Bangning Mao, Yanlong Meng, Yanghui Li, Juan Kang, Le Wang, Yi Li

Proceedings Volume 12972, International Academic Conference on Optics and Photonics (IACOP 2023); 1297203 (2024) https://doi.org/10.1117/12.3021942
Event: International Academic Conference on Optics and Photonics (IACOP 2023), 2023, ONLINE, China

Abstract

The measurement of refractive index plays a crucial role in biosensing. This paper proposes a novel solution for refractive index sensing by utilizing seven-core fiber spatial multiplexing to receive the spectrum of a no-core fiber. Compared to existing high-sensitivity fiber sensing structures like core offset and polishing, this solution offers the advantages of easy production and a simplified process. In terms of spectral demodulation methods, this solution employs deep neural networks to replace the traditional approach of tracking spectral peaks or troughs. By utilizing the entire spectrum information, the accuracy of spectral demodulation is significantly improved. Additionally, the use of seven-core fiber with spatial multiplexing characteristics allows for the reception of a larger amount of information compared to single-mode fiber, thereby further enhancing the refractive index sensing capability. The results demonstrate that this solution achieves a remarkable refractive index sensing accuracy rate of 2.25×10^-5.

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

Citation Download Citation

Hongjie Cao, Huan Liu, Jiajun He, Yanqing Qiu, Bangning Mao, Yanlong Meng, Yanghui Li, Juan Kang, Le Wang, and Yi Li "Seven-core fiber spatial multiplexing refractometer based on convolutional neural networks", Proc. SPIE 12972, International Academic Conference on Optics and Photonics (IACOP 2023), 1297203 (25 January 2024); https://doi.org/10.1117/12.3021942

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