Influence of Organic Coating on the Giant Magneto Impedance Characteristics of Fe-Rich Amorphous Wire

Abstract

Influence of organic coating on the giant mag- neto impedance effect was experimentally investigated in Zn complex-coated dielectric Fe-based amorphous wires and optimized the giant magneto impedance (GMI) effect using artificial neural networks and MATLAB. A three- node input layer, a one-node output layer and three hidden layers with 21 neurons and full connectivity between nodes were developed with the transfer functions hyperbolic tan- gent in hidden layers and sigmoid in output layer. The input parameters were frequency, static magnetic field and sample type, while the output parameter was the giant mag- neto impedance effect. When the network performance was tested using untrained sample data, the average correla- tion and prediction error of giant magneto impedance effect were found to be 99 and 0.4 %. An analytical equation as depending on experimental data has been determined by using MATLAB Curve Fitting Toolbox™for giant mag- neto impedance. The square of the correlation and the root meansquared error were found to be 99 % and 0.89 respec- tively. The models including the different kinds of samples prepared have a good prediction capability and agreement with experimental results.