dc.description.abstract | This study develops an automatic optical detection system for cast metal surface flaws and investigates surface defects on the cast metal golf club head. Surface defects include reaction pores, air entrainment pores, peeling, shrinkage holes, lumps, and so on. Five main flaws. First, the club head′s surface is separated into 21 parts based on different curvature angles, the best imaging angles for each area are determined, and an image shooting technique is developed. Our image-capturing approach incorporates unilateral light sources on the left and right sides. Illumination, combined with the adjustment of the rotation angle of the rotating platform and the up and down movement of the lifting platform, allows the CCD to adapt to the curvature of the surface in different areas and capture images with the most obvious defect features as well as the smallest defect above 6 pixels. Next, use LabVIEW as a tool for image processing to find defects using a four-step procedure. The first phase involves using open operations to eliminate the noise and dark spots on the metal in the image. The second stage employs the grayscale standard deviation correction approach to successfully overcome the uneven brightness problem in the image produced by contrast variations that accentuate fault features, decreasing the original image with a grayscale standard deviation of over 45 to between 22 and 23. The third step involves using the Laplacian filter to reduce background noise and sharpen fault details. The fourth phase employs binary segmentation technology to successfully distinguish faults from the background, followed by the closure operation in morphology to fix and enhance the image′s defect features. At the same time, particle filters are utilized to minimize the screening frequency. decreased from 2.74% to 1.8%. Finally, the Matlab application is used to combine photos from several shooting regions and identify the location of the defect on a plane coordinate system, resulting in a more intelligible visual position.
This investigation obtained 21 pictures for each club head sample. There were 5 sample club heads in all, therefore 105 pictures were obtained. The automatic optical defect detection system identified 944 faults. The identification findings were compared to human eye detection results. After comparison, the number of faults overlooked by the screen was zero, indicating that our defect detection method correctly identified all errors seen by the human eye. There were 17 faults examined, with a 1.8% screening rate and a 98.2% detection success rate. It has been confirmed that our automatic optical inspection system can successfully detect faults on the surface of cast metal. | en_US |