By Topic

Neural-Network-Based Model for Dynamic Hysteresis in the Magnetostriction of Electrical Steel Under Sinusoidal Induction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)

In this paper, we present a model for the dynamic hysteresis behavior of magnetostriction in electrical steel under sinusoidal induction. The model can be used for the numerical calculation of vibrations in magnetic cores. In order to keep the calculation time of the method to an acceptable level, we developed a neural-network-based model, which predicts magnetostriction loop shapes of the material under a limited set of circumstances but offers fast evaluation time. As an example, we apply the model to a grain-oriented electrical steel and present an error analysis. The model can be extended for use with nonsinusoidal induction.

Published in:

Magnetics, IEEE Transactions on  (Volume:43 ,  Issue: 8 )