Magnetic Characterization of MR Fluid by Means of Neural Networks

Magnetorheological and electrorheological fluids manifest a change in rheological behavior when subjected to a magnetic or electric field, respectively, such that they require electrical and magnetic characterization. In this paper, a simple and accurate mathematical model based on a small number of...

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Bibliographic Details
Published in:Electronics (Basel) 2024-05, Vol.13 (9), p.1723
Main Authors: Kowol, Paweł, Lo Sciuto, Grazia, Brociek, Rafał, Capizzi, Giacomo
Format: Article
Language:English
Subjects:
Approximation
Electric fields
Electrical properties
Electrorheological fluids
Fluids
High temperature
Magnetic fields
Magnetic permeability
Magnetic properties
Magnetorheological fluids
Mathematical functions
Mathematical models
Mechanical engineering
Neural networks
Permeability
Radial basis function
Rheological properties
Rheology
Smart materials
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Summary:Magnetorheological and electrorheological fluids manifest a change in rheological behavior when subjected to a magnetic or electric field, respectively, such that they require electrical and magnetic characterization. In this paper, a simple and accurate mathematical model based on a small number of parameters provides the relative magnetic permeability of magnetorheological fluids as a function of the applied magnetic field. Furthermore, for the testing and magnetic characterization of magnetorheological fluids, a new metering equipment setup is implemented. Starting with the achieved experimental data, the mathematical relation μr=f(B) is represented by means of a radial basis function neural network, with neurons having a Gaussian activation function; by means of post-training pruning procedures, the trained neural network is applied using the proposed data. Therefore, the obtained mathematical relation μr=f(B) is in good agreement with the experimental data, with an approximate error of 8%.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13091723