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基于具有干扰识别功能的相敏光时域反射计的光纤通信网络井监测。

Fiber-Optic Telecommunication Network Wells Monitoring by Phase-Sensitive Optical Time-Domain Reflectometer with Disturbance Recognition.

机构信息

Bauman Moscow State Technical University, 2-nd Baumanskaya 5-1, 105005 Moscow, Russia.

Department of Applied Mathematics, MIEM, National Research University Higher School of Economics, 123458 Moscow, Russia.

出版信息

Sensors (Basel). 2023 May 22;23(10):4978. doi: 10.3390/s23104978.

Abstract

The paper presents the application of a phase-sensitive optical time-domain reflectometer (phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched structure of the urban network of telecommunication wells. The encountered tasks and difficulties are described. The possibilities of usage are substantiated, and the numerical values of the event quality classification algorithms applied to experimental data are calculated using machine learning methods. Among the considered methods, the best results were shown by convolutional neural networks, with a probability of correct classification as high as 98.55%.

摘要

本文介绍了相敏光时域反射计(phi-OTDR)在城市基础设施监测领域的应用。特别是在城市网络电信井的分支结构中。描述了所遇到的任务和困难。论证了使用的可能性,并使用机器学习方法计算了应用于实验数据的事件质量分类算法的数值。在所考虑的方法中,卷积神经网络显示出最好的结果,正确分类的概率高达 98.55%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb9a/10220778/0a65ea041e59/sensors-23-04978-g001.jpg

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