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周晓虎, 高向东, 杜亮亮, 王春草. 基于FGT-FBP重构算法的焊接缺陷检测[J]. 焊接学报, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002
引用本文: 周晓虎, 高向东, 杜亮亮, 王春草. 基于FGT-FBP重构算法的焊接缺陷检测[J]. 焊接学报, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002
ZHOU Xiaohu, GAO Xiangdong, DU Liangliang, WANG Chuncao. Detection of weld defects based on FGT - FBP reconstruction algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002
Citation: ZHOU Xiaohu, GAO Xiangdong, DU Liangliang, WANG Chuncao. Detection of weld defects based on FGT - FBP reconstruction algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002

基于FGT-FBP重构算法的焊接缺陷检测

Detection of weld defects based on FGT - FBP reconstruction algorithm

  • 摘要: 针对焊接过程产生的缺陷,提出一种磁光成像传感的模糊灰度变换和滤波反投影(FGT-FBP)重构检测方法. 研究焊接缺陷的几何特征,通过分析裂纹和未熔合两种不同焊接缺陷在交变磁场励磁下的磁光成像特征,设计模糊规则,对磁光图像进行模糊灰度变换. 增强磁光图像对比度,使焊接缺陷形态趋势可视化,实现描述磁光成像焊接缺陷细节的无参考型图像评估方法. 对FGT处理的焊接缺陷磁光图进行旋转投影,并经过快速傅里叶变换和改进的滤波器进行滤波去噪,消除伪影后进行反投影变换实现焊接缺陷图像的重构. 利用滤波反投影重构算法进行去噪,可有效突出焊接缺陷特征. 最后结合阈值分割和边缘检测实现焊接缺陷检测. 结果表明,该方法能较准确检测裂纹和未熔合两种焊接缺陷.

     

    Abstract: An innovative detection method based upon fuzzy gray scale transformation and filter back-projection (FGT-FBP) reconstruction is proposed to study the geometrical characteristics of weld defects. By analyzing the characteristics of magneto-optical images with defects such as cracks and incomplete penetration under alternating magnetic field excitation, a fuzzy rule is designed to carry on fuzzy gray scale transformation of the magneto-optical image. The image contrast is improved to visualize the configuration and trend of weld defects. An image evaluation method without reference models that describes weld defect details of magneto-optical images is realized. The weld defect magneto-optical images processed by FGT are rotated and projected. Fast Fourier transform and improved filter are applied for denoising and filtering. Also, the back-projection transform is used to reconstruct weld defect images after eliminate artifacts. Then FGT-FBP is used to denoise by filtering, and extract defect features from the images. Finally, the proposed method is combined threshold segmentation with edge detection to achieve defect detection. Experiment results show that FGT-FBP reconstruction algorithm can detect weld defects such as cracks and incomplete penetration accurately.

     

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