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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