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

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Trains Detection Using State of Polarization Changes Measurement and Convolutional Neural Networks
Original language description
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.
Czech name
—
Czech description
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Project
<a href="/en/project/VI20192022146" target="_blank" >VI20192022146: Distributed fiber optic sensing system for use in perimeter and line structures protection</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Proceedings
ISBN
978-1-7281-5099-4
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
1-4
Publisher name
IEEE
Place of publication
neuveden
Event location
Hawai (virtual)
Event date
Mar 22, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000680838400015

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