• DocumentCode
    1780263
  • Title

    Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis

  • Author

    Aziz, N.H. ; Catterson, V.M. ; Judd, M.D. ; Rowland, S. ; Bahadoorsingh, S.

  • Author_Institution
    Inst. for Energy & Environ., Univ. of Strathclyde, Glasgow, UK
  • fYear
    2014
  • fDate
    19-22 Oct. 2014
  • Firstpage
    373
  • Lastpage
    376
  • Abstract
    This paper presents a prognostic framework for estimating the time-to-failure (TTF) of insulation samples under electrical treeing stress. The degradation data is taken from electrical treeing experiments on 25 epoxy resin samples. Breakdown occurs in all tests within 2.5 hours. Partial discharge (PD) data from 18 samples are used as training data for prognostic modeling and 7 for model validation. The degradation parameter used in this model is the voltage difference between consecutive PD pulses, which decreases prior to breakdown. Every training sample shows a decreasing exponential trend when plotting the root mean squared (RMS) of the voltage difference for 5 minute batches of data. An average model from the training data is developed to determine the RMS voltage difference during breakdown. This breakdown indicator is verified over three time horizons of 25, 50 and 75 minutes. Results show the best estimation of TTF for 50 minutes of data, with error within quantified bounds. This suggests the framework is a promising approach to estimating insulation TTF.
  • Keywords
    epoxy insulation; least mean squares methods; trees (electrical); PD data; PD pulses; RMS; TTF; degradation data; electrical treeing; electrical treeing stress; epoxy resin; partial discharge data; prognostic modeling; pulse sequence analysis; root mean squared plotting; solid insulation; time-to-failure estimation; Data models; Epoxy resins; Insulation; Mathematical model; Partial discharges; Solids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Insulation and Dielectric Phenomena (CEIDP), 2014 IEEE Conference on
  • Conference_Location
    Des Moines, IA
  • Type

    conf

  • DOI
    10.1109/CEIDP.2014.6995906
  • Filename
    6995906