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Lookup NU author(s): Emeritus Professor Gui Yun Tian
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© 2026 Elsevier Ltd. The magnetic anisotropy depends on service stress (or residual stress) and production-defined crystal orientation. Magnetic Barkhausen noise (MBN) can non-destructively analyze magnetic anisotropy and microstructure variations under stress. However, the traditional anisotropy measurement methods with the small-angle rotary excitation magnetic field consume a long measurement time with high data redundancy and lack to quantify the macro easy magnetization axis effected by the microstructure and the stress. In this paper, the MBN finite angular energy model is proposed to quantitatively evaluate ferromagnetic components’ magnetic anisotropy and easy magnetization axis in single-easy-axis ferromagnetic components. By measuring MBN signals at finite angles without prior knowledge of magnetic anisotropy, the model estimates the easy magnetization axis and magnetic anisotropy with lower data redundancy and faster detection than traditional small-angle rotary excitation magnetic anisotropy measurement methods. By combining electron backscattered diffraction (EBSD), the proposed model quantitatively analyzes the variation of easy magnetization axes in both oriented and non-oriented silicon steel sheets under elastic and plastic status, elucidating the effects of grain orientation and stress on micro − macro magnetic property variations. This research establishes a correlation between material microstructure and electromagnetic signals, demonstrating potential applications in micro-damage non-destructive testing for industrial applications such as rails. Future work will optimize this model to apply it to industrial applications with complex geometries, evaluating its broader applicability.
Author(s): Liu J, Tian GY, Zeng K, Chen CJ
Publication type: Article
Publication status: Published
Journal: Measurement
Year: 2026
Volume: 288
Print publication date: 15/10/2026
Online publication date: 17/07/2026
Acceptance date: 14/07/2026
ISSN (print): 0263-2241
ISSN (electronic): 1873-412X
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.measurement.2026.122585
DOI: 10.1016/j.measurement.2026.122585
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