April 29, 2024ElectronicsOpen Access

Magnetic Characterization of MR Fluid by Means of Neural Networks

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Authors

PKPaweł KowolSilesian University of Technology GSGrazia Lo SciutoTechnical University of Sofia RBRafał BrociekSilesian University of Technology

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Implication

Experimental study demonstrates accurate magnetic characterization in magnetorheological fluids using neural networks, indicating reliable estimation of relative magnetic permeability.

Key Points

Relative magnetic permeability in magnetorheological fluids is accurately predicted across applied magnetic fields using a compact mathematical formulation.
An approximate error of 8% is achieved when comparing the predicted relative magnetic permeability values to experimental data obtained across field strengths.
Analysis using a radial basis function neural network with post-training pruning enables reliable magnetic characterization, supporting effective device control.

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Kowol et al. (2024) studied this question.

synapsesocial.com/papers/68e6d073b6db64358764e853 https://doi.org/10.3390/electronics13091723

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Implication

Experimental study demonstrates accurate magnetic characterization in magnetorheological fluids using neural networks, indicating reliable estimation of relative magnetic permeability.

Magnetic Characterization of MR Fluid by Means of Neural Networks

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Member takes

Implication

Key Points

Cite This Study

Magnetic Characterization of MR Fluid by Means of Neural Networks

Discussion

Member takes

Implication

Key Points

Cite This Study

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