Modeling of Magnetorheological Fluids Relative Magnetic Permeability by using a Neural Network approach

被引：0

作者：

Kowol, Pawel ^{[1
]}

Szczygiel, Marcin ^{[1
]}

Lo Sciuto, Grazia ^{[2
]}

Capizzi, Giacomo ^{[2
]}

机构：

[1] Silesian Tech Univ, Dept Mechatron, Fac Elect Engn, Gliwice, Poland

[2] Univ Catania, Dept Elect Elect & Informat Engn, Catania, Italy

来源：

20TH IEEE MEDITERRANEAN ELETROTECHNICAL CONFERENCE (IEEE MELECON 2020) | 2020年

关键词：

magnetic permeability; magnetorheological fluids; Gabor system; neural network;

D O I：

10.1109/melecon48756.2020.9140517

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：

In this paper, starting from the experimental data obtained with an empirical measurement device developed for this purpose, it has been determined a simple and accurate model (based on a small number of parameters) that allows to represent the relative magnetic permeability of the magnetorheological fluids as a function of the magnetic field in which it is immersed in. The model thus obtained is in excellent agreement with the experimental data. In fact the obtained error is approximately of 8%.

引用

页码：25 / 28

页数：4

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