Diaci J.: Surface defect detection on power transmission belts using laser profilometry; accepted for publication

Quality control in production of the power transmission belts currently relies mostly on visual inspection by skilled workers. They primary inspect belt geometry for defects like small bumps, dents and unformed teeth. Despite the controller experience, the result depends on the person’s mood and general condition. To avoid subjective inspection, an experimental system for automated inspection of the belt geometry is developed. It operates on the basis of the laser triangulation system, capable of acquiring a cloud of points in 3D space representing a complete belt surface. By processing the acquired data cloud, most typical belt defects can be identified and assessed. We demonstrate two different methods of data processing. The first one imitates the established “manual ” procedure, where the individual tooth profile is compared to a template specified by a technical documentation. The second method uses a novel approach based on the deviation map. That enables automated analyses of the complete tooth surface (not only profile), identification of 4 typical surface defects and their pass/fail quality assessment. We found shape of the surface defects sufficiently recognizable in the acquired data cloud, which means that point measurement accuracy of the developed laser triangulation system is sufficient. We demonstrate identification of the typical surface defects. We found that further work is needed to develop pass/fail criteria of the quality assessment to comply with the requirements of the industry