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基于磁巴克豪森噪声的铁磁材料磁各向异性检测技术综述

A Survey of the Magnetic Anisotropy Detection Technology of Ferromagnetic Materials Based on Magnetic Barkhausen Noise.

作者信息

Wang Liting, Xu Changjie, Feng Libo, Wang Wenjie

机构信息

School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China.

School of Emergency Equipment, North China Institute of Science and Technology, Langfang 065201, China.

出版信息

Sensors (Basel). 2024 Nov 27;24(23):7587. doi: 10.3390/s24237587.

Abstract

Magnetic Barkhausen noise (MBN) is one of the most effective methods for determining the easy axis of ferromagnetic materials and for evaluating texture and residual stress in a nondestructive manner. MBN signals from multiple angles and different magnetization sections can be used to characterize magnetic anisotropy caused by various magnetization mechanisms. This paper reviews the development and application of magnetic anisotropy detection technology, and the MBN anisotropy models that take into account domain wall motion and magnetic domain rotation are analyzed thoroughly. Subsequently, the MBN anisotropy detection devices and detection methods are discussed, and the application of magnetic anisotropy detection technology in stress measurement and texture evaluation is reviewed. From the perspective of improving detection accuracy, the influence of composite mechanisms on magnetic anisotropy is analyzed. Finally, the opportunities and challenges faced by current magnetic anisotropy detection technology are summarized. The relevant conclusions obtained in this paper can be used to guide the MBN evaluation of magnetic anisotropy in ferromagnetic materials.

摘要

磁巴克豪森噪声(MBN)是确定铁磁材料易轴以及以无损方式评估织构和残余应力的最有效方法之一。来自多个角度和不同磁化截面的MBN信号可用于表征由各种磁化机制引起的磁各向异性。本文综述了磁各向异性检测技术的发展与应用,并深入分析了考虑磁畴壁运动和磁畴旋转的MBN各向异性模型。随后,讨论了MBN各向异性检测装置和检测方法,并综述了磁各向异性检测技术在应力测量和织构评估中的应用。从提高检测精度的角度分析了复合机制对磁各向异性的影响。最后,总结了当前磁各向异性检测技术面临的机遇和挑战。本文所得相关结论可用于指导铁磁材料磁各向异性的MBN评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda1/11644475/d702d90b6c7c/sensors-24-07587-g001.jpg

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