Publication detail
Optimization of Stator Channels Positions Using Neural Network Approximators
SIKORA, M. ANČÍK, Z.
English title
Optimization of Stator Channels Positions Using Neural Network Approximators
Type
Paper in proceedings (conference paper)
Language
en
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 in English
CFD model, generator, neural network aproximator, optimization
Released
2011-09-21
Publisher
Springer
Location
Berlin
ISBN
978-3-642-23243-5
Book
Mechatronics Recent Technological and Scientific Advances
Pages from–to
365–373
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"
}