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Detection model of invisible weld defects using magneto-optical imaging induced by rotating magnetic field

机译:旋转磁场磁光成像的检测模型

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Magneto-optical (MO) imaging non-destructive testing (NDT) system excited by rotating magnetic field is proposed for feature extraction and detection classification of invisible arbitrary-angle weld defects. Based on Faraday rotation effect, the relationship between the imaging characteristics of weld defect MO image and the leakage magnetic field intensity is analyzed. The gray-level co-occurrence matrix (GLCM) method is used to extract texture features of the weld defect MO images, and the texture features of the images can reflect the leakage magnetic field characteristics of the defects. These texture features of the weld defect MO images are used as the input vector of the defect classification model based on support vector machine (SVM). The effectiveness and feasibility of the classification model are verified by the weld defect detection experiment. Experimental results show that the established recognition model can accurately classify invisible arbitrary-angle weld defects.
机译:通过旋转磁场激发的磁光(Mo)成像(NDT)系统,用于特征提取和无形任意角焊缝缺陷的特征提取和检测分类。基于法拉第旋转效果,分析了焊接缺陷Mo图像的成像特性与漏磁场强度之间的关系。灰度共发生矩阵(GLCM)方法用于提取焊接缺陷MO图像的纹理特征,图像的纹理特征可以反映缺陷的漏磁场特性。焊接缺陷Mo图像的这些纹理特征用作基于支持向量机(SVM)的缺陷分类模型的输入向量。通过焊接缺陷检测实验验证了分类模型的有效性和可行性。实验结果表明,建立的识别模型可以准确地分类无形的任意角焊缝缺陷。

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