Detection of weld defects based on FGT - FBP reconstruction algorithm

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.