• DocumentCode
    33021
  • Title

    Automatic selection of frequency bands for the power ratios separation technique in partial discharge measurements: part II, PD source recognition and applications

  • Author

    Ardila-Rey, J.A. ; Martinez-Tarifa, J.M. ; Robles, G.

  • Author_Institution
    Univ. Tec. Federico Santa Maria, Santiago de Chile, Chile
  • Volume
    22
  • Issue
    4
  • fYear
    2015
  • fDate
    Aug-15
  • Firstpage
    2293
  • Lastpage
    2301
  • Abstract
    Partial discharge (PD) measurement is a widely extended technique for the diagnosis of electrical machines and power cables. Since PD and noise recognition is really important in industrial environments, the authors proposed the use of the spectral Power Ratios (PR) of the detected high-frequency (HF) signals, which show promising results. However, the frequency bands selected for their calculation have a clear influence on the position of the clusters in the classification maps. Following this research trend, a new algorithm for the automatic selection of the frequency bands which gives a proper separation between the clusters, has been proposed in part I of this paper. The first results presented in this paper revealed a good behavior of the technique for PD and noise separation in simple test objects. In this second part of the paper, more results from the application of this system to PD source recognition in simple test objects and also in real equipment are developed.
  • Keywords
    electric machines; partial discharge measurement; power cables; signal detection; PD applications; PD separation; PD source recognition; classification maps; electrical machine diagnosis; frequency band automatic selection; high-frequency signal detection; industrial environments; noise recognition; noise separation; partial discharge measurement; power cable diagnosis; spectral power ratio separation technique; Bandwidth; Clustering algorithms; Corona; Discharges (electric); Noise; Partial discharges; Surface discharges; Partial discharges; clustering techniques; electrical insulation; power ratio maps; spectral power; statistical dispersion;
  • fLanguage
    English
  • Journal_Title
    Dielectrics and Electrical Insulation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1070-9878
  • Type

    jour

  • DOI
    10.1109/TDEI.2015.004822
  • Filename
    7179193