Research On Machine Vision-base Detection Of The Of Sealing Rubber Rings

The sealing rubber ring needs to detect defect in the production process, andthe traditional detection methods mainly rely on artificial detection. It not onlyincreases the cost of production and worker’s labor intensity, and low detectionefficiency and large error, and it is difficult to ensure the inspection results. So it isneeded an automatic detection system which can be applied to the sealing rubberring to replace artificial detection. After year’s development of machine visiontechnology, it has been used in the detection of mass products. This paper launcheda new study on the detection system of the black type o rubber sealing ring basedon machine vision technology. The main research work is introduced as followings:Firstly, this paper analyzes the development of machine vision and rubber ringdetection at home and abroad, puts forward the overall design of the rubber sealring detection on the analysis of the problem of the presence.Secondly, sealing rubber ring’s image acquisition system is designedaccording to the general scheme of the detection system. This paper selects theappropriate collection equipment to build an experimental platform and collects therubber ring image. All works are based on requirements of the image to bemeasured, at the same time combined with the requirements of all components ofthe acquisition system.Thirdly, the image processing algorithms were investigated, including imagefiltering, threshold segmentation, regional extraction and edge extraction. On thebasis of experiment, we analyzed and compared the advantages and disadvantagesof various algorithms, and choose the suitable image processing algorithm for thesealing rubber ring.Fourthly, the paper selects an appropriate measure of the center of the circlealgorithm, contrary to the rubber ring size detection. The paper presented a newmethod combined the binary image pixel statistics method with the gray levelco-occurrence matrix analysis method to extract the rubber ring’s defectcharacteristics, and then gave the defect recognition algorithm flowchart.