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Frequency domain analysis of magnetic field images obtained using TMR array sensors for subsurface defect detection and quantification
NDT & E International ( IF 4.2 ) Pub Date : 2020-05-30 , DOI: 10.1016/j.ndteint.2020.102284
Chaofeng Ye , Yang Wang , Meiling Wang , Lalita Udpa , Satish S. Udpa

Quantitative characterization of subsurface defects is a challenging problem in eddy current testing (ECT), not only due to the limitation of the penetration depth of eddy currents, but also due to the ill-posed nature of the inverse problem associated with quantifying a defect's 3D dimensions and its location in the test sample from measurements made on the sample surface. This paper presents a new ECT method for subsurface defect detection and quantification. Eddy currents with continuously varying frequency in a selected frequency band is induced in the conductive sample by using a chirp modulated excitation scheme. The frequency band of the chirp waveform is chosen so that the penetration depth of eddy current in the selected frequency band covers the thickness of the sample under test. The presence of a defect will disturb the distribution of the induced eddy currents. This disturbance is measured in terms of a varying magnetic field using an array of tunneling magneto-resistance (TMR) sensors. A C-scan image is obtained by linearly scanning the specimen. The footprint of the defect is calculated using spatial features of the C-scan image while the depth of the defect is estimated by analyzing the frequency characteristics of the measured chirp signal. A three-dimensional estimate of the dimensions of any subsurface defect can be obtained using the empirical procedure. The operating principle of this method is studied with a finite element method (FEM) model and then validated experimentally with a prototype array probe consisting of 180 TMR sensors. Thanks to its high sensitivity, the TMR sensors are suitable for measuring the weak low frequency magnetic field signal caused by a deep defect. The spacing between each two adjacent sensors is as small as 0.5 mm providing a magnetic field image with fine spatial resolution, which is beneficial for defect quantification. An aluminum sample with embedded defects was tested using the prototype probe. It is seen that the proposed scheme utilizing spatial and frequency domain features is capable of quantitatively characterizing subsurface defects.



中文翻译:

使用TMR阵列传感器对地下缺陷进行检测和量化的磁场图像的频域分析

地下缺陷的定量表征在涡流测试(ECT)中是一个具有挑战性的问题,这不仅是由于涡流穿透深度的限制,而且还在于与定量缺陷3D相关的反问题的不适定性尺寸和它在测试样品中的位置(通过在样品表面上进行的测量)。本文提出了一种新的ECT方法,用于地下缺陷的检测和定量。通过使用线性调频调制激励方案,在导电样品中感应出选定频带中频率连续变化的涡流。选择线性调频波形的频带,以使所选频带中涡流的穿透深度覆盖被测样品的厚度。缺陷的存在将干扰感应涡流的分布。使用一组隧道磁阻(TMR)传感器根据变化的磁场测量此干扰。通过线性扫描样本获得C扫描图像。使用C扫描图像的空间特征来计算缺陷的足迹,同时通过分析所测量的线性调频信号的频率特性来估算缺陷的深度。可以使用经验方法获得任何地下缺陷尺寸的三维估算。使用有限元方法(FEM)模型研究此方法的工作原理,然后使用由180个TMR传感器组成的阵列探头原型进行实验验证。由于灵敏度高,TMR传感器适用于测量由深缺陷引起的微弱的低频磁场信号。每个两个相邻传感器之间的间距小至0.5 mm,可提供具有精细空间分辨率的磁场图像,这对于缺陷定量很有帮助。使用原型探针测试了带有嵌入缺陷的铝样品。可以看出,所提出的利用空间和频域特征的方案能够定量表征地下缺陷。

更新日期:2020-05-30
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