1 Engineering Research Center for Machining of Brittle Materials of Ministry of Education, Huaqiao University, Xiamen 361021; 2 Institute of Manufacturing Engineering, Huaqiao University, Xiamen 361021
Abstract: Computer vision detection technology was adopted to extract the defect feature quantity of the surface, and further completed the detection of surface crack defects in polycrystalline diamond compact. First, according to the features of polycrystalline diamond compact, the appropriate light source lighting system was studied. Then, a local boundary extraction method based on the histogram projection gradient extremum was proposed, and the region of interest (ROI) was extracted. On this basis, the method of image filtering and threshold segmentation were used to realize the accurate extraction of the crack. Finally, the crack was identified by calculating the circularity factor and aspect ratio of the cracked domain. Experimental results showed that this method can effectively detect the surface crack defects of polycrystalline diamond compact.
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2017, Vol. 31 
