New phenemenon on power transformers and fault identification using artificial neural networks

Sengul M. , Ozturk S., Cetinkaya H. B. , Erfidan T.

ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2, vol.4132, pp.767-776, 2006 (Journal Indexed in SCI) identifier

  • Publication Type: Article / Article
  • Volume: 4132
  • Publication Date: 2006
  • Title of Journal : ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2
  • Page Numbers: pp.767-776


In this paper voltage recovery after voltage dip that cause magnetizing inrush current which is a new phenomenon in power transformers are discussed and a new technique is proposed to distinquish internal fault conditions from no-fault conditions that is also containing these new phenomenons. The proposed differential algorithm is based on Artificial Neural Network (ANN). The training and testing data sets are obtained using SIMPOW-STRI power system simulation program and laboratory transformer. A novel neural network is designed and trained using back-propagation algorithm. It is seen that the proposed network is well trained and able to discriminate no-fault examples from fault examples with high accuracy.