Application of subpixel edge detection in quality control of double-column metal parts

Abstract

At present, most of the parts of mechanical equipment are made of metal, so the accurate detection and extraction of important characteristic parameters of metal parts is the key to determine the quality of mechanical equipment. In order to accurately extract and measure the feature size of metal parts, this research first carried out image preprocessing. Threshold segmentation is performed, and the target traits are extracted from the image to obtain the ROI. Finally, the preprocessed image is extracted from the image by the sub-pixel edge extraction technology to extract the feature size of the circle to be measured. The difference between the measured value of the characteristic dimension of the spring bearing seat and the gasket and the real value measured by the research method is within the range of 5 and 4 μm, respectively, and both of them meet the requirements of the characteristic dimension accuracy. When the feature size of the two is repeatedly measured, the variation range of the detection results of the spring bearing seat and the gasket is within 9 and 7 μm respectively, and the detection value is much smaller than the feature size tolerance. The detection accuracy of the method can reach 95.394%. The $F_1$ score was 96.029 and the AUC value was 0.93, both higher than other methods. The results show that the use of sub-pixels on metal parts The edge extraction method is extremely accurate. The research method can effectively improve the detection accuracy of the feature size of metal parts, which is of great significance to the development of the entire metal parts processing industry.