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
fDate :
9/1/1998 12:00:00 AM
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;
Journal_Title :
Magnetics, IEEE Transactions on
