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Sliding Mean Value Subtraction-Based DC Drift Correction of B-H Curve for 3D-Printed Magnetic Materials

机译:基于滑动平均值减法的3D打印磁性材料B-H曲线的直流漂移校正

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摘要

This paper presents an algorithm to remove the DC drift from the B-H curve of an additively manufactured soft ferromagnetic material. The removal of DC drift from the magnetization curve is crucial for the accurate estimation of iron losses. The algorithm is based on the sliding mean value subtraction from each cycle of calculated magnetic flux density (B) signal. The sliding mean values (SMVs) are calculated using the convolution theorem, where a DC kernel with a length equal to the size of one cycle is convolved with B to recover the drifting signal. The results are based on the toroid measurements made by selective laser melting (SLM)-based 3D printing mechanism. The measurements taken at different flux density values show the effectiveness of the method.
机译:本文介绍了一种算法,用于从加质制造的软铁磁材料的B-H曲线上移除DC漂移。从磁化曲线中去除直流漂移对于准确估计铁损失是至关重要的。该算法基于来自计算磁通密度(B)信号的每个循环的滑动平均值减法。使用卷积定理计算滑动平均值(SMV),其中长度等于一个循环尺寸的DC内核是用B卷积的,以恢复漂移信号。结果基于通过选择性激光熔化(SLM)的3D印刷机构制备的环形测量。在不同助焊剂密度值下拍摄的测量显示了该方法的有效性。

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