Detail publikace
Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure
DEJDAR, P. MOKRÝ, O. MÜNSTER, P. HORVÁTH, T. SCHIMMEL, J.
Originální název
Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
Distributed acoustic sensing (DAS) is an emerging technology with diverse applications in monitoring infrastructure, security systems, and environmental sensing. This study presents a dataset comprising acoustic vibration patterns recorded by a commercial DAS system, providing valuable insights into the acoustic sensitivity of optical fibers. The data are crucial for evaluating the performance of DAS systems, particularly in scenarios related to security and eavesdropping. The dataset offers the possibility to develop and test algorithms aimed at enhancing signal-to-noise ratio (SNR), detecting anomalies, and improving speech intelligibility. Additionally, this resource facilitates the validation of de-noising techniques through the calculation of the speech transmission index (STI). The experimental setup, measurement procedures, and the characteristics of the DAS system employed are comprehensively documented for researchers in the field of optical fiber sensing and signal processing.
Klíčová slova
Distributed Acoustic Sensing; Fiber Optics; Fiber Sensors; Optical Communications; Speech Intelligibility Performance
Autoři
DEJDAR, P.; MOKRÝ, O.; MÜNSTER, P.; HORVÁTH, T.; SCHIMMEL, J.
Vydáno
13. 5. 2025
Nakladatel
Springer Nature
ISSN
2052-4463
Periodikum
Scientific data
Ročník
12
Číslo
5
Stát
Spojené království Velké Británie a Severního Irska
Strany od
1
Strany do
8
Strany počet
8
URL
Plný text v Digitální knihovně
BibTex
@article{BUT197888,
author="Petr {Dejdar} and Ondřej {Mokrý} and Petr {Münster} and Tomáš {Horváth} and Jiří {Schimmel}",
title="Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure",
journal="Scientific data",
year="2025",
volume="12",
number="5",
pages="1--8",
doi="10.1038/s41597-025-05119-0",
issn="2052-4463",
url="https://www.nature.com/articles/s41597-025-05119-0"
}