Automated 3D Defect Detectionm based on Simulated Reference

Abstract

Bringing the Computed Tomography (CT) technology into production lines brings many advantages due to the complete and detailed 3D characterization and localization of defects. But compared to laboratory systems, Inline-CT systems must meet several challenges, the most significant one is certainly the limited available time for the measurement procedure and data evaluation. Visual inspection of 3D data sets of complex parts within the production rate is almost impossible, so automated image evaluation algorithms are mandatory for that task. Fast measurement procedures often mean short integration times and a lower number of projections which are two factors that increase quantum noise and thus decrease image quality significantly. In addition to that, scatter artifacts also have a negative influence on the image quality. All these conditions constitute challenges to the image evaluation algorithm. The Fraunhofer EZRT has developed a method for automated defect detection in cast parts by using reference (that means flawless) parts for comparison. The advantage of this method is that image artifacts are considered, since they appear in both data sets in the same way and have almost no negative influence on the reliability of the evaluation result. Most recent work took this method one step further by using not real flawless parts, but instead using simulations to generate reference data sets in a very convenient and quick way for any number of different parts.