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A Complex Network Based Classification of Covered Conductors Faults Detection

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Intelligent Data Analysis and Applications (ECC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 535))

Abstract

Presence of partial discharges implies the fault behavior on insulation system of medium voltage overhead lines, especially with covered conductors (CC). This paper covers the machine learning model based on features, which are derived from complex networks. These features are applied to predict whether the measured signal contains phenomenon indicating CC fault behavior or not. The comparison of different threshold levels of similarity values brings more information about complex network modeling. The final performance of the Random Forest classification algorithm shows valuable results for future research.

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Acknowledgment

This research was conducted within the framework of the project TUCENET Sustainable Development of Centre ENET LO1404 and Students Grant Competition project reg. no. SP2016/175, SP2016/177, SP2016/128.

Author information

Authors and Affiliations

  1. Department of Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Tomas Vantuch, Jan Gaura & Ivan Zelinka

  2. Department of Electrical Power Engineering, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Stanislav Misak

Authors
  1. Tomas Vantuch
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  2. Jan Gaura
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  3. Stanislav Misak
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  4. Ivan Zelinka
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Corresponding author

Correspondence to Tomas Vantuch .

Editor information

Editors and Affiliations

  1. College of Information Science and Engineering, Fujian University of Technology , Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Faculty of Electrical Engineering and Computer Science, VÅ B-Technical University of Ostrava , Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  3. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, China

    Tien-Wen Sung

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, China

    Xiao Dong Wang

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Vantuch, T., Gaura, J., Misak, S., Zelinka, I. (2017). A Complex Network Based Classification of Covered Conductors Faults Detection. In: Pan, JS., Snášel, V., Sung, TW., Wang, X. (eds) Intelligent Data Analysis and Applications. ECC 2016. Advances in Intelligent Systems and Computing, vol 535. Springer, Cham. https://doi.org/10.1007/978-3-319-48499-0_33

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  • DOI: https://doi.org/10.1007/978-3-319-48499-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48498-3

  • Online ISBN: 978-3-319-48499-0

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