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, cilt.4132, ss.767-776, 2006 (SCI İndekslerine Giren Dergi) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4132
  • Basım Tarihi: 2006
  • Dergi Adı: ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2
  • Sayfa Sayıları: ss.767-776

Özet

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.