The part is compared to the golden image at each region of interest and for each inspection type and level. Differences are extracted and accept or reject is based on the extraction results. Data is forwarded to a statistical database. Flawed parts are identified, and the ADR system signals pass or fail to the inspection system. Common defects such as cavity, gas, inclusion, and sponge are detected.
Manufacturers are able to define various levels of defects.
Defect type and severity are then automatically classified according to these manufacturers-defined criteria. Quantitative measurements of defect size and density provide process feedback. The Artificial Intelligence ADR system is designed on the basis of a qualitative image model. Edges are not sharp structures in X-ray imagery because of the penetration and divergent rays of the central projection. In the edge regions the noise level is high.