Dynamic hysteresis modelling using feed-forward neural networks

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• 作者：Makaveev ; Dimitre ; Dupr&eacute ; Luc ; De Wulf ; Marc ; Melkebeek ; Jan
• 关键词：Hysteresis&mdash ; magnetic ; Magnetization&mdash ; models ; time dependent ; Neural networks
• 刊名：Journal of Magnetism and Magnetic Materials
• 出版年：2003
• 出版时间：January, 2003
• 年：2003
• 卷：254-255
• 期：Complete
• 页码：256-258
• 全文大小：93.3 K

文摘

A computational model for dynamic hysteresis in laminated SiFe alloys is proposed, based on feed-forward neural networks. The model employs the loss-separation property of ferromagnetic materials and combines a rate-independent hysteresis model with a correction technique for dynamic effects at each time point. The model yields accurate prediction of BH loops for arbitrary waveforms and frequencies, as they occur in electrical motors.