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An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters

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Abstract

The paper presents an artificial neural network (ANN) software tool that has been developed in order to assess the electric field around medium-voltage surge arresters. The knowledge of the electric field around gapless metal oxide surge arresters is very useful for diagnostic tests and design procedures. For the training, validating, and testing of the ANNs, real data have been used collected from hundreds of measurements. The developed ANN software can be used by electric utilities in order to diagnose the condition of the surge arresters without stopping their operation and by laboratories and manufacturing/retail companies dealing with medium-voltage surge arresters and either face a lack of suitable measuring equipment or want to compare/verify their own measurements.

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City University London, London, EC1V 0HB, UK

    Lambros Ekonomou

  2. Department of Electrical Engineering, Technological Educational Institute (T.E.I.) of Central Greece, 35100, Lamia, Greece

    Christos A. Christodoulou

  3. Department of Theoretical Electrical Engineering, Technical University of Sofia, Sofia 1000, “Kliment Ohridski” Blvd. 8, Sofia, Bulgaria

    Valeri Mladenov

Authors
  1. Lambros Ekonomou
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  2. Christos A. Christodoulou
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  3. Valeri Mladenov
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Corresponding author

Correspondence to Lambros Ekonomou.

Appendix

Appendix

See Table 3.

Table 3 Electric field measurements obtained across a polymeric surge arrester with height of 502 mm and creepage distance of 1365 mm
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Ekonomou, L., Christodoulou, C.A. & Mladenov, V. An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters. Neural Comput & Applic 27, 1143–1148 (2016). https://doi.org/10.1007/s00521-015-1969-x

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  • DOI: https://doi.org/10.1007/s00521-015-1969-x

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