• DocumentCode
    1990373
  • Title

    Prediction of core losses on a three-phase transformer using neural networks

  • Author

    Souza, Kleymilson N. ; Castro, Thiago N. ; Pereira, Thiago M. ; Pontes, Ricardo S T ; Braga, Arthur P S

  • Author_Institution
    Dept. de Eng. Eletr.-DEE, Univ. Fed. do Ceara-UFC, Fortaleza, Brazil
  • fYear
    2011
  • fDate
    15-18 May 2011
  • Firstpage
    1105
  • Lastpage
    1108
  • Abstract
    This work is a study of intelligent tools for forecasting losses in the transformer core, comparing with the traditionally accepted model. The uses of Artificial Neural Networks (ANN) search a best estimator of losses in the transformer core. Two models of ANN were proposed: Multi-Layer Percepton (MLP) and Neo-Fuzzy Neuron (NFN). After an analysis of the model they were evaluated and it was concluded that the MLP model for this application had the best performance.
  • Keywords
    intelligent sensors; perceptrons; power transformer testing; artificial neural networks; core losses; intelligent tools; multilayer percepton; neo fuzzy neuron; three phase transformer; Artificial neural networks; Core loss; Magnetic hysteresis; Neurons; Power transformers; Transformer cores;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2011 IEEE International Symposium on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    0271-4302
  • Print_ISBN
    978-1-4244-9473-6
  • Electronic_ISBN
    0271-4302
  • Type

    conf

  • DOI
    10.1109/ISCAS.2011.5937763
  • Filename
    5937763
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1990373