DocumentCode
1429315
Title
Improved neural network model for induction motor design
Author
Idir, Kamel ; Chang, Liuchen ; Dai, Heping
Author_Institution
Dept. of Electr. Eng., New Brunswick Univ., Fredericton, NB, Canada
Volume
34
Issue
5
fYear
1998
fDate
9/1/1998 12:00:00 AM
Firstpage
2948
Lastpage
2951
Abstract
An improved model of the artificial neural network for analysis and design of induction motors is presented. Parameters of the machine equivalent circuit are calculated using finite element method for a given motor geometry. The training of the neural network model is based on a decoupled system between geometrical variables and circuit parameters. This method efficiently improved the training and performance of the neural network model which can be used to predict machine performance and solve design optimization problems
Keywords
equivalent circuits; finite element analysis; induction motors; machine theory; neural nets; artificial neural network model; design optimization; equivalent circuit; finite element method; induction motor; training; Artificial neural networks; Coupling circuits; Equivalent circuits; Finite element methods; Induction motors; Neural networks; Niobium; Rotors; Solid modeling; Stators;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/20.717688
Filename
717688
Link To Document