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Review of UHF-Based Signal Processing Approaches for Partial Discharge Detection

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Book cover Computer Aided Systems Theory – EUROCAST 2017 (EUROCAST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10672))

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Abstract

Partial Discharge (PD) events are due to local defects in dielectrics and can cause damages to the electrical insulation and eventually to the whole power station. This paper reviews approaches describing procedures and numerical techniques for detecting, denoising, clustering, and classifying PDs in the ultra-high frequency range. For each method the mathematical background is recalled and one or few representative examples from selected papers are shortly described.

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Acknowledgment

This work was funded by the State Grid Corporation of China (SGCC) through the R&D project “Research of Key Technology of UHF Wireless Sensing based Substation Partial Discharge Monitoring and Location”.

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Authors and Affiliations

  1. Global Energy Interconnection Research Institute Europe GmbH, Markgrafenstr. 34, 10117, Berlin, Germany

    Benjamin Schubert, Mauro Palo & Thomas Schlechter

Authors
  1. Benjamin Schubert
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  2. Mauro Palo
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  3. Thomas Schlechter
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Corresponding author

Correspondence to Benjamin Schubert .

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Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Schubert, B., Palo, M., Schlechter, T. (2018). Review of UHF-Based Signal Processing Approaches for Partial Discharge Detection. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2017. EUROCAST 2017. Lecture Notes in Computer Science(), vol 10672. Springer, Cham. https://doi.org/10.1007/978-3-319-74727-9_26

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  • DOI: https://doi.org/10.1007/978-3-319-74727-9_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74726-2

  • Online ISBN: 978-3-319-74727-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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