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Evaluating the surface profile (roughness) of coated abrasives / Non-contact 3D shape measurement using a laser microscope


Application

A coated abrasive consists of abrasive grains, such as diamond fragments, bonded to the surface of synthetic fabric, craft paper, or non-woven cloth using synthetic resin. To precisely control the abrasive quality, the condition of the bonded abrasive grains needs to be carefully managed. Checking the condition of abrasives with a conventional laser microscope is difficult because the reflectivity of the areas with sharp abrasive grains is extremely low, while the reflectivity of flat areas is very high. Consequently, three-dimensional imaging of coated abrasives has been difficult for laser microscopes.

Olympus' solution

Olympus' LEXT 3D scanning laser microscope has dual confocal technology that enables users to evaluate the profile of abrasive surfaces that have heavy irregularities, observe the distribution of abrasive grains, and examine surface roughness quantitatively. With its dual confocal system, the LEXT can acquire a reliable 3D image even for surfaces made up of materials with different reflectivities so manufacturers can evaluate their abrasive materials. With the microscope’s stitching mode, users can combine multiple images to form a single wide-area observation in high resolution, making it easy to identify differences in roughness across a large surface.

#100    
#100_objective 20x_zoom 1x_3x3 stitching
3D_#100_objective 20x_zoom 1x_3x3 stitching
20X objective lens; 1X zoom; 3×3 stitching
#240
#240_objective 20x_zoom 1x_3x3 stitching
3D_#240_objective 20x_zoom 1x_3x3 stitching
20X objective lens; 1X zoom; 3×3 stitching

Olympus IMS

Verwendete Produkte

The LEXT™ OLS5100 laser scanning microscope combines exceptional accuracy and optical performance with smart tools that make the system easy to use. The tasks of precisely measuring shape and surface roughness at the submicron level are fast and efficient, simplifying your workflow and delivering high-quality data you can trust.

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