Preisach function identification by neural networks

被引:40
作者
Cirrincione, M [1 ]
Miceli, R
Galluzzo, GR
Trapanese, M
机构
[1] Univ Palermo, CNR, I-90128 Palermo, Italy
[2] Univ Palermo, Dept Elect Engn, I-90128 Palermo, Italy
关键词
hysteresis; measurements; modeling; soft magnetic materials;
D O I
10.1109/TMAG.2002.803614
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a novel technique for the identification of the Preisach density function which is based on a neural-network approach and which requires a relatively limited amount of experimental parameters. The fundamental idea of this method is to identify Preisach function of the material by training a neural network with a set of loops whose identification function is known. In the final section of the paper, the method is verified on several cases.
引用
收藏
页码:2421 / 2423
页数:3
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