Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F22%3A43966044" target="_blank" >RIV/49777513:23220/22:43966044 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9905173" target="_blank" >https://ieeexplore.ieee.org/document/9905173</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/Diagnostika55131.2022.9905173" target="_blank" >10.1109/Diagnostika55131.2022.9905173</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition
Original language description
This paper compares the performance of one-dimensional and two-dimensional convolutional neural networks in the task of analyzing a reference signal while determining the degradation level of single-core polymer-insulated cable. In this work was designed the set of reference signals and several forms of representing of these signals in the form of one-dimensional and two-dimensional tensors. Then, an experimental determination of the most effective version of the reference signal is carried out in terms of classification accuracy and the most effective form of representation of this signal was found, as well as most efficient type of neural network.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika) : CDEE 2022
ISBN
978-1-66548-082-6
ISSN
—
e-ISSN
2464-708X
Number of pages
4
Pages from-to
—
Publisher name
University of West Bohemia in Pilsen
Place of publication
Pilsen
Event location
Pilsen, Czech Republic
Event date
Sep 6, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—