Publication detail

Optimization of Stator Channels Positions Using Neural Network Approximators

SIKORA, M. ANČÍK, Z.

Original Title

Optimization of Stator Channels Positions Using Neural Network Approximators

Type

conference paper

Language

English

Original Abstract

This paper deals with an improvement of synchronous generator cooling. Finding of the best positions of stator radial channels is a way to cooling improvement. An optimization method for finding of the best channels positions is presented here. The main goal of optimization is to achieve uniform temperatures field of winding along slot length, without overheated locations. The Computational Fluid Dynamic (CFD) is used for estimating of stator temperatures. Input parameters for CFD models are computed by optimization algorithm which is able to predict stator temperatures behavior. This algorithm is based on neural networks approximators. There is a feedback between CFD models and optimization algorithm.

Keywords

CFD model, generator, neural network aproximator, optimization

Authors

SIKORA, M.; ANČÍK, Z.

RIV year

2011

Released

21. 9. 2011

Publisher

Springer

Location

Berlin

ISBN

978-3-642-23243-5

Book

Mechatronics Recent Technological and Scientific Advances

Edition

Springer

Edition number

1

Pages from

365

Pages to

373

Pages count

9

BibTex

@inproceedings{BUT73882,
  author="Michal {Sikora} and Zdeněk {Ančík}",
  title="Optimization of Stator Channels Positions Using Neural Network Approximators",
  booktitle="Mechatronics Recent Technological and Scientific Advances",
  year="2011",
  series="Springer",
  number="1",
  pages="365--373",
  publisher="Springer",
  address="Berlin",
  isbn="978-3-642-23243-5"
}