A neural network-based tool for magnetic performance prediction of toroidal cores
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Date
2003-01
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Journal ISSN
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Publisher
Elsevier
Abstract
Geometrical and building parameters have a strong influence on magnetic performance of wound toroidal cores made from electrical steel or similar strip products. This paper presents a neural network-based approach to predict losses and permeability in such cores of varying geometries over an induction range of 0.2-1.8T (50Hz). The approach is shown to be successful.
Description
Bu çalışma, 05-07 Eylül 2001 tarihleri arasında Bilbao[İspanya]’da düzenlenen 15. International Symposium on Soft Magnetic Materials’da bildiri olarak sunulmuştur.
Keywords
Materials science, Physics, Artificial intelligence, Magnetic losses, Neural networks, Soft magnetic materials, Strip-wound cores, Magnetic leakage, Magnetic permeability, Toroidal cores, Magnetic cores
Citation
Miti, G. K. vd. (2003). “A neural network-based tool for magnetic performance prediction of toroidal cores”. Journal of Magnetism and Magnetic Materials, 254(Special Issue), 262-264.