Trains Detection Using State of Polarization Changes Measurement and Convolutional Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU140943" target="_blank" >RIV/00216305:26220/21:PU140943 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9430469" target="_blank" >https://ieeexplore.ieee.org/document/9430469</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/INERTIAL51137.2021.9430469" target="_blank" >10.1109/INERTIAL51137.2021.9430469</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Trains Detection Using State of Polarization Changes Measurement and Convolutional Neural Networks

Popis výsledku v původním jazyce

Fiber optic infrastructure security is of growing interest. The current distributed sensor systems are robust and expensive solutions, and their practical applications are uncommon. Research into simple and cost-effective solutions based on changes in the state of polarization is crucial. This paper expands the use of a vibration sensor based on the sensing of rapid changes in the state of polarization (SOP) of light in a standard single-mode optical fiber by using a convolutional neural network to detect trains running along the optical fiber infrastructure. It is a simple system that determines ongoing events near the optical fiber route by simply determining the signal boundaries that define the idle state. By using a neural network, it is possible to eliminate the distortion caused by the temperature changes and, for example, to improve detection in the the zones where the vibrations are not strong enough for a simple threshold resolution.

Název v anglickém jazyce

Trains Detection Using State of Polarization Changes Measurement and Convolutional Neural Networks

Popis výsledku anglicky

Fiber optic infrastructure security is of growing interest. The current distributed sensor systems are robust and expensive solutions, and their practical applications are uncommon. Research into simple and cost-effective solutions based on changes in the state of polarization is crucial. This paper expands the use of a vibration sensor based on the sensing of rapid changes in the state of polarization (SOP) of light in a standard single-mode optical fiber by using a convolutional neural network to detect trains running along the optical fiber infrastructure. It is a simple system that determines ongoing events near the optical fiber route by simply determining the signal boundaries that define the idle state. By using a neural network, it is possible to eliminate the distortion caused by the temperature changes and, for example, to improve detection in the the zones where the vibrations are not strong enough for a simple threshold resolution.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/VI20192022146" target="_blank" >VI20192022146: Distribuovaný optický vláknový senzorický systém pro ochranu perimetru a liniových staveb</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Proceedings

ISBN

978-1-7281-5099-4

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

1-4

Název nakladatele

IEEE

Místo vydání

neuveden

Místo konání akce

Hawai (virtual)

Datum konání akce

22. 3. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000680838400015