Dynamic hysteresis modelling for nano-crystalline cores

KÜÇÜK İ., HACIİSMAİLOĞLU M. C., DEREBAŞI N.

EXPERT SYSTEMS WITH APPLICATIONS, vol.36, no.2, pp.3188-3190, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 2
  • Publication Date: 2009
  • Doi Number: 10.1016/j.eswa.2008.01.084
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.3188-3190
  • Keywords: Dynamic hysteresis model, Nano-crystal, Neural network, NEURAL-NETWORK, GENETIC ALGORITHM, TOROIDAL CORES, POWER LOSSES, PREDICTION
  • Bursa Uludag University Affiliated: Yes

Abstract

This paper presents all artificial neural network approach based oil dynamic Preisach model to compute hysteresis loops of nano-crystalline cores. The network has been trained by a Levenberg-Marquardt learning algorithm. The model is fast and does not require tremendous computational efforts. The results obtained by using the proposed model are in good agreement with experimental results. (C) 2008 Elsevier Ltd. All rights reserved.