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高向东,谢溢龙,陈子琴,游德勇. 高强钢焊接缺陷磁光成像分形特征检测[J]. 焊接学报, 2017, 38(7): 1-4. DOI: 10.12073/j.hjxb.20150803001
引用本文: 高向东,谢溢龙,陈子琴,游德勇. 高强钢焊接缺陷磁光成像分形特征检测[J]. 焊接学报, 2017, 38(7): 1-4. DOI: 10.12073/j.hjxb.20150803001
GAO Xiangdong, XIE Yilong, CHEN Ziqin, YOU Deyong. Fractal feature detection of high-strength steel weld defects by magnetooptical imaging[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(7): 1-4. DOI: 10.12073/j.hjxb.20150803001
Citation: GAO Xiangdong, XIE Yilong, CHEN Ziqin, YOU Deyong. Fractal feature detection of high-strength steel weld defects by magnetooptical imaging[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(7): 1-4. DOI: 10.12073/j.hjxb.20150803001

高强钢焊接缺陷磁光成像分形特征检测

Fractal feature detection of high-strength steel weld defects by magnetooptical imaging

  • 摘要: 研究一种基于磁光成像原理的焊接缺陷无损检测新方法.以高强钢表面微小焊接缺陷为例,采用分形维数对焊缝磁光图像进行特征识别并估计最优尺度,根据Adabost分类算法对提取的焊接缺陷特征进行分析和训练,构建焊接缺陷特征量并对高强钢表面缺陷磁光图像进行自动识别.结果表明,运用磁光成像方法可以获取高强钢焊接缺陷特征,并通过图像分形维数分析可识别焊缝缺陷的位置、形状和类别.

     

    Abstract: A new nondestructive testing method based on the principle of magnetic-optical imaging was investigated in this paper. Fractal dimension detection was applied to extract features and estimate the optimal scale on the magnetic-optical images of high strength steel that has micro weld defects on the surface. The extracted features of weld defects were trained and tested by using classification algorithm Adabost to build weld defect characteristics and realize automatic identification of magnetic optical images for high strength steel surface defects. The experimental results show that the characteristics of high strength steel weld defects can be detected by using magnetic-optical imaging. Furthermore, the position, shape and category of weld defects can be identified by fractal dimension analysis based on the magnetic-optical images.

     

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