Multilayered perceptron neural networks to compute energy losses in magnetic cores

被引：13

作者：

Kucuk, Ilker ^{[1
]}

机构：

[1] Uludag Univ, Dept Phys, Fac Arts & Sci, TR-16059 Bursa, Turkey

来源：

JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS | 2006年 / 307卷 / 01期

关键词：

toroidal wound cores; energy losses; neural network;

D O I：

10.1016/j.jmmm.2006.03.043

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the specific energy losses of toroidal wound cores built from 3% SiFe 0.27 mm thick M4, 0.1 and 0.08 mm thin gauge electrical steel strips. The MLP has been trained by a back-propagation and extended delta-bar-delta learning algorithm. The results obtained by using the MLP model were compared with a commonly used conventional method. The comparison has shown that the proposed model improved loss estimation with respect to the conventional method. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：53 / 61

页数：9

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