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GMR-based eddy current probe for weld seam inspection and its non-scanning detection study

机译：基于GMR的涡流检查的基于GMR的涡流探头及其非扫描检测研究

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摘要

Eddy current testing is one of the most important non-destructive testing methods for welding defects detection. This paper presents the use of a probe consisting of 4 giant magneto-resistive (GMR) sensors to detect weld defects. Information from four measuring points above and on both sides of the weld seam is collected at the same time. By setting the GMR sensors' sensing axes perpendicular to the direction of the excitation magnetic field, the information collected mainly reflects the change in the eddy current which is caused by defects. Digital demodulation technology is applied to extract the real part and imaginary part of the GMR sensors' output signals. The variables containing directional information of the magnetic field are introduced. Based on the data from the four GMR (4-GMR) sensors' output signals, four values, Ran, Mean, Var and k are selected as the feature quantities for defect recognition. Experiments are carried out on weld seams with and without defects, and the detection outputs are given in this paper. The 4-GMR probe is also employed to investigate non-scanning weld defect detection and the four feature quantities (Ran, Mean, Var and k) are studied to evaluate weld quality. The non-scanning weld defect detection is presented. A support vector machine is used to classify and discriminate welds with and without defects. Experiments carried out show that through the method in this paper, the recognition rate is 92% for welds without defects and 90% for welds with defects, with an overall recognition rate of 90.9%, indicating that this method could effectively detect weld defects.
机译：涡流测试是焊接缺陷检测最重要的非破坏性测试方法之一。本文介绍了由4个巨型磁电阻（GMR）传感器组成的探头来检测焊接缺陷。来自焊缝上方和两侧的四个测量点的信息同时收集。通过将垂直于激励磁场的方向的GMR传感器的感测轴设置，收集的信息主要反映由缺陷引起的涡流的变化。应用数字解调技术以提取GMR传感器输出信号的实数和虚部。介绍了包含磁场的方向信息的变量。基于来自四个GMR（4-GMR）传感器的输出信号的数据，选择四个值，ran，平均值，v和k作为缺陷识别的特征量。实验在具有缺陷的焊缝上进行，并在本文中给出了检测输出。 4-GMR探针还用于研究非扫描焊接缺陷检测，并研究四个特征量（RAN，平均值，var和k）以评估焊接质量。提出了非扫描焊接缺陷检测。支持向量机用于分类和区分焊缝，无缺陷。进行的实验表明，通过本文的方法，焊缝的识别率为92％，对于缺陷的焊缝，缺陷的焊缝90％，总识别率为90.9％，表明该方法可以有效地检测焊接缺陷。

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