Performance improvement of a 3D inspection process

摘要

The performance of a 3-D inspection process as measured in terms of accuracy and repeatability of point cloud data obtained through the process is of great importance for proper utilization of data. This paper attempts to characterize effect of different operating conditions on system performance and to estimate a set of best operating conditions for the Capture Geometry Inside system CSS-1000. The system consists of a milling machine to cut the part one layer at a time and a vision system made up of a line-scan camera and associated software to capture images of the cut surfaces. These images are stacked to construct a 3-D point cloud data of the part. The mill-head rotation speed, milling feed rate and part orientation are some of the operating conditions studied. Accuracy is measured by comparing measured dimensions of the part with dimensions obtained from the process while spread of point cloud data from the best-fit plane on a surface provides a measure of repeatability. Tests were done on parts made up of two different materials: Aluminum and Delrin? under two different sets of operating conditions. The results show improvement in accuracy under the new set of operating conditions for aluminum parts while repeatability improves for Delrin parts.