Deep learning-based macro-bending loss detection by plastic optical fiber specklegram analysis

Nikhil Vangety; Sourabh Roy

doi:10.1117/12.3015912

18 June 2024 Deep learning-based macro-bending loss detection by plastic optical fiber specklegram analysis

Nikhil Vangety, Sourabh Roy

Proceedings Volume 13017, Machine Learning in Photonics; 130170U (2024) https://doi.org/10.1117/12.3015912
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Conference Poster

Abstract

The specklegram analysis due to macro-bending of optical fibers has been widely employed for different sensing purposes. In this work, we mainly detect the random, multiple macro-bending loss by employing a deep learning-based convolutional neural network (CNN) namely the AlexNet model. Here, we detect the discrete losses corresponding to six macro-bends of different radii at six different locations of plastic optical fiber (POF). The proposed model can detect the macro-bending losses with 100% detection accuracy which signifies the efficacy of the proposed AlexNet model. In perspective, our results may pave the way for developing a deep-learning methodology for the smart detection of several, discrete macro-bending losses in POFs for several sensing applications.

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

Citation Download Citation

Nikhil Vangety and Sourabh Roy "Deep learning-based macro-bending loss detection by plastic optical fiber specklegram analysis", Proc. SPIE 13017, Machine Learning in Photonics, 130170U (18 June 2024); https://doi.org/10.1117/12.3015912

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