Development of an Intelligent Monitoring System Based on the Use of Fiber-Optic Sensors and Deep Learning

A. Neftissov, Assiya Sarinova, Ilyas Kazambaev, L. Kirichenko, S. Bronin
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Abstract

Fiber-optic sensors are commonly used in modern monitoring systems. This article discusses a monitoring system using a fiber-optic sensor built using a camera. As the study showed, the newly proposed method requires a machine learning system to determine the displacement of stone slabs accurately. However, this system needs to have higher accuracy in determining the distance to the damage. This work aims to develop a deep learning system that considers external disturbances affecting a light spot's image.
基于光纤传感器和深度学习的智能监测系统的开发
光纤传感器在现代监控系统中得到广泛应用。本文讨论了一种利用摄像机构建的光纤传感器的监控系统。正如研究表明的那样,新提出的方法需要一个机器学习系统来准确地确定石板的位移。然而,该系统在确定损伤距离方面需要更高的精度。这项工作旨在开发一种深度学习系统,该系统可以考虑影响光点图像的外部干扰。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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