Signal Event List Generation Using Neural Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F23%3A00369786" target="_blank" >RIV/68407700:21340/23:00369786 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Signal Event List Generation Using Neural Networks
Original language description
The goal of this paper is to apply deep learning methods to the signal event detection task. In this paper we propose a novel architecture that combines both 2D and 1D convolutional layers. This model is then compared to architectures based on processing raw signal data. The potential of these methods is demonstrated on both synthetic tone data and burst acoustic emission from material fatigue testing. The trained neural networks can be used to automate the analysis of ultrasonic signals, e.g. for real-time detection of emission events.
Czech name
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Czech description
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Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
SPMS 2022/23 Stochastic and Physical Monitoring Systems, Proceedings of the international conferences
ISBN
978-80-01-07250-9
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
27-36
Publisher name
České vysoké učení technické v Praze
Place of publication
Praha
Event location
Sloup v Čechách
Event date
Jun 26, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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