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

Şengül M., Öztürk S., Çetinkaya H. B., Erfidan T.

16th International Conference on Artificial Neural Networks, ICANN 2006, Athens, Yunanistan, 10 - 14 Eylül 2006, cilt.4132 LNCS - II, ss.767-776 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 4132 LNCS - II
  • Doi Numarası: 10.1007/11840930_80
  • Basıldığı Şehir: Athens
  • Basıldığı Ülke: Yunanistan
  • Sayfa Sayıları: ss.767-776
  • Kocaeli Üniversitesi Adresli: Evet

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. © Springer-Verlag Berlin Heidelberg 2006.