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Detection of Piston Surface Defects Based on Machine Vision

With the development of science and technology, enterprises and users have higher and higher requirements for the quality of engine pistons. At present, the piston detection methods of many manufacturers are mainly contact detection and manual detection. However, the size of piston surface defects is usually small and irregular, and the surface reflectance is strong, it is difficult to detect defects. Therefore, taking the piston as the research object, a piston surface defect detection system is developed based on machine vision to detect and identify the piston surface defects. Aiming at the image processing of piston surface defects, a set of image processing flow based on HALCON is designed. It mainly includes image preprocessing, binarization, morphological processing, and threshold segmentation. The research shows that the system has certain reliability, detection efficiency, and accuracy, so that the detection system can be applied to practical production.