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

被引：10

作者：

Zhirnov, Andrey A. ^{[1
]}

Chesnokov, German Y. ^{[2
]}

Stepanov, Konstantin V. ^{[1
]}

Gritsenko, Tatyana V. ^{[1
]}

Khan, Roman I. ^{[1
]}

Koshelev, Kirill I. ^{[1
]}

Chernutsky, Anton O. ^{[1
]}

Svelto, Cesare ^{[3
]}

Pnev, Alexey B. ^{[1
]}

Valba, Olga V. ^{[2
,4
]}

机构：

[1] Bauman Moscow State Tech Univ, 2nd Baumanskaya 5-1, Moscow 105005, Russia

[2] Natl Res Univ Higher Sch Econ, Dept Appl Math, MIEM, Moscow 123458, Russia

[3] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy

[4] Brain & Consciousness Res Ctr, Lab Complex Networks, Moscow 119991, Russia

来源：

SENSORS | 2023年 / 23卷 / 10期

基金：

俄罗斯科学基金会;

关键词：

fiber optic sensor; distributed fiber optic sensor; phi-OTDR; acoustic monitoring; machine learning; telecommunication well; OTDR SENSING SYSTEM; SENSOR; TRANSFORM;

D O I：

10.3390/s23104978

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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%.

引用

页数：15

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