Prediction of dynamic hysteresis loops of nano-crystalline cores


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

EXPERT SYSTEMS WITH APPLICATIONS, vol.36, no.2, pp.2225-2227, 2009 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 2
  • Publication Date: 2009
  • Doi Number: 10.1016/j.eswa.2007.12.051
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.2225-2227
  • Keywords: Dynamic hysteresis modelling, Nano-crystalline cores, Neural network, TOROIDAL CORES

Abstract

Dynamic hysteresis loops of a range of nano-crystalline cores have been obtained over a wide frequency range (1-50 kHz). A dynamic hysteresis model front measurements using an artificial neural network trained by the delta-bar-delta learning algorithm has been developed. The input parameters include the geometrical dimensions of cores, peak magnetic induction and magnetizing frequency. The results show the neural network model has an acceptable estimation capability for dynamic hysteresis loops of toroidal nano-crystalline cores. (C) 2007 Elsevier Ltd. All rights reserved.