Abstract

X-ray computed tomography (CT) imaging for industrial applications is limited to certain physical conditions to be fulfilled. The size of the measuring object and the accumulated wall thickness are two fundamental conditions. An omission of these conditions by not capturing object attenuation information by the x-ray detector leads to missing data in the 3D reconstruction process and results as a consequence in image degradation and artifacts. Conventional industrial x-ray CT is based on cone-beam projections and circular or helical scanning trajectories using linear axis and a rotary (lift) table. For many inspection tasks on big-sized or unusually shaped objects the physical limits for obtaining a sufficient high image quality are reached very quickly when using conventional CT systems. Industrial six-axis robots offer much more flexibility with respect to the conditions mentioned earlier and can overcome the limitations of conventional scanners. In the present work we characterized an industrial six-axis robot in its working space following ISO 9283 in terms of pose accuracy and pose repeatability. These results are then used to simulate faulty scanning trajectories in terms of pose deviations where a single robot is used as an object manipulator to rotate virtual specimens on a circular trajectory resulting in different (faulty) reconstruction datasets. These datasets are evaluated visually and by using performance parameters and geometrical features in order to determine the reproduction fidelity (performance) of a one arm robot-based CT system depending on different pose errors. With the results obtained it was shown that a robot-based CT system of type B (in our classification scheme) using one robot as object manipulator should be able to reach a spatial resolution power in the range of the voxel size (in our case 200 µm) and smaller (neglecting effects from focal spot size, detector unsharpness from x-ray to light conversation and scatter radiation) if systematic pose errors are compensated using appropriate calibration methods.

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