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首页> 外文期刊>Journal of Nondestructive Evaluation >Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal Magnetic Memory Technique
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Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal Magnetic Memory Technique

机译:基于GMR传感器基于GMR传感器的金属磁记忆技术的碳钢中变形诱导磁场的映射

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摘要

Giant magneto-resistive (GMR) sensor based metal magnetic memory (MMM) technique is proposed for mapping of deformation-induced self-magnetic leakage fields (SMLFs) in carbon steel. The specimens were subjected to different amounts of tensile deformation and the deformation-induced SMLFs were measured using a GMR sensor after unloading the specimens. 3D-nonlinear finite element modeling was performed to predict stress-strain state in a steel specimen under tensile load. The experimentally obtained SMLF images were correlated with the finite element model predicted stress-strain states. Studies reveal that the MMM technique can detect the plastic deformation with signal-to-noise ratio better than 20 dB. The technique enables the mapping of plastic deformation in carbon steels for the evaluation of the severity of deformation. The study also reveals that deformation-induced SMLF is influenced by the presence of initial surface residual stress, introduced by shot peening. The intensity of SMLF signal is found to increase with increase in tensile load and decrease with shot peening.
机译:提出了一种基于巨磁阻(GMR)传感器的金属磁记忆(MMM)技术,用于绘制碳钢中形变诱导的自漏磁场(SMLF)。对试样进行不同程度的拉伸变形,并在卸载试样后使用GMR传感器测量变形引起的SMLF。采用三维非线性有限元模型预测拉伸载荷下钢试样的应力应变状态。实验获得的SMLF图像与有限元模型预测的应力应变状态相关联。研究表明,MMM技术可以检测到塑性变形,信噪比优于20dB。该技术可以绘制碳钢的塑性变形图,以评估变形的严重程度。研究还表明,变形诱发的SMLF受喷丸处理引入的初始表面残余应力的影响。发现SMLF信号强度随拉伸载荷的增加而增加,随喷丸处理而降低。

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