Design of a quality inspection system for heated cigarette ends based on machine vision
A heated cigarette end quality inspection system based on machine vision detection technology was designed to address the difficulty of online detection of common quality defects such as cigarette deformation,hollowing,and looseness at the end of heated cigarettes. The system utilized hardware such as high-speed counting cards,industrial cameras,and flash controllers to complete image acquisition,and the Canny algorithm was used for cigarette contour detection and recognition in the industrial computer. Then,cigarette deformation was determined based on the mean and standard deviation of the contour radius,cigarette hollow was identified based on global threshold binarization,and cigarette looseness was identified based on local adaptive binarization. Based on the recognition results,the end defects of cigarette deformation,hollowing,and looseness were eliminated online. The performance of the binary algorithm used in the system and its practical application in production were validated. The results showed that compared with OTSU,Bernsen,Niblack and other methods,global threshold binarization had the highest accuracy (99.8％) in hollow detection,and adaptive binarization had the highest accuracy (99.0％) in looseness detection. The system had a detection accuracy of ≥99％ for defects such as deformation,hollowing,and looseness of heated cigarette ends,and had significant advantages in calculation time. It was suitable for high-speed operation requirements of production lines and could provide support for improving the quality of heated cigarette ends and production process control.
heated cigarettemachine visioncigarette end qualityCanny algorithmbinary algorithm
万方数据
维普
