Prognostic modeling of transformer aging using Bayesian particle filtering

@article{Catterson2014PrognosticMO,
  title={Prognostic modeling of transformer aging using Bayesian particle filtering},
  author={V. M. Catterson},
  journal={2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)},
  year={2014},
  pages={413-416}
}
  • V. M. Catterson
  • Published 2014 in
    2014 IEEE Conference on Electrical Insulation and…
The goal of condition monitoring is to accurately assess the current health of an asset, in order to generate a prognosis, i.e. predict its remaining useful life. In the absence of a fault which causes premature failure, transformer degradation is linked to paper aging. Research and experience have resulted in models of paper aging where hotspot temperature is the key driver. However, these deterministic equations give a false sense of certainty about remaining insulation life. This paper… CONTINUE READING
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