To solve the problems of low efficiency and high subjectivity of existing sandpaper morphology parameter detection methods, machine vision methods are used to detect the surface morphology characteristics of sandpaper. A weighted decision matrix is established to select the important parameters that can reflect the topography of the sandpaper surface; Zeiss Smartproof5 fast turntable confocal microscope equipment is used to obtain the true-color view of different sandpaper samples, the pseudo-color view based on the height, and the XYZ three-dimensional point cloud of the sandpaper surface; the image is preprocessed by the methods of threshold segmentation and morphology processing, and then segmented by watershed segmentation; and the key topographic parameters of different sandpaper samples are calculated and compared. The key morphological parameters of different sandpaper samples were calculated and compared. The results show that the number of abrasive grains, abrasive grain size and other parameters increase with the increase of mesh size, while the uniformity of sandpaper distribution decreases with the increase of mesh size. The results of this study can provide a theoretical reference for the realization of automated inspection of sandpaper surface topography.
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Zheng et al. (2024) studied this question.
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