发表机构
Eindhoven University of Technology; Kinetron - ASSAABLOY（埃因霍温理工大学; 基特隆-亚萨拜罗）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出无模型逆方法，利用谐波近似从边界测量重建内部磁场，空间平均恢复主方向B-H特性，实现软磁材料非线性各向异性磁性能的非侵入式识别，噪声下误差低于5%。
AI 中文摘要
本研究提出了一种无模型逆方法，用于从边界测量中识别软磁材料的非线性各向异性单值磁本构特性。利用谐波近似，内部磁通密度B和磁场强度H从测量的边界数据中独立重建，从而避免了使用预定义参数化B-H映射函数的局限性。随后，重建的场沿选定的采集线进行空间平均，以恢复主方向的B-H特性。数值结果表明，对无扰动数据具有较高的重建精度，并且对边界测量的高斯扰动具有良好的鲁棒性，在10%噪声水平下总体平均误差保持在5%以下。这些结果表明，在谐波场假设下，基于场的重建为非线性各向异性磁本构特性的非侵入式识别提供了一种简单且计算高效的框架。
英文摘要
This research proposes a model-free inverse approach for identifying the nonlinear anisotropic single-valued magnetic constitutive characteristics of soft magnetic materials from boundary measurements. Using the harmonic approximation, the internal magnetic flux density B and magnetic field strength H are independently reconstructed from the measured boundary data, thus avoiding the limitation of using a predefined parametric B--H mapping function. Subsequently, the reconstructed fields are spatially averaged along selected collection lines to recover the B--H characteristics of the principal directions. Numerical results demonstrate high reconstruction accuracy for unperturbed data and good robustness against Gaussian perturbations of the boundary measurements, with the overall mean error remaining below 5% for a 10% noise level. These results indicate that under the harmonic-field assumptions, the field-based reconstruction provides a simple and computationally efficient framework for non-invasive identification of nonlinear anisotropic magnetic constitutive characteristics.
