Optimization of parameter settings by projection based quality parameters in industrial computed tomography

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New technologies in manufacturing (such as additive manufacturing) enable the production of parts with high requirements towards accuracy as well as a high functional integration. These parts often contain inner structures and hidden features that cannot be accessed with conventional tactile coordinate metrology. Computed tomography (CT) thus is getting more and more important, because it is the only method that can measure inner structures non-destructively. Computed tomography offers a high density of measurement points spread over the whole inner and outer surface geometry of the part, making a three-dimensional volumetric model of the measured component possible. Computed tomography for dimensional metrology is a complex and indirect measurement procedure, whose results depend on a variety of influencing factors. Starting from the single projection towards data processing of the measured data, for each measuring task an individual set of parameters has to be chosen accordingly. The quality and reliability of the measurement, expressed in measurement uncertainty, depends on hard- and software as well as user-set scan parameters. Scan parameters, such as current, tube voltage or exposure time, can influence the measurement results. Especially in micro computed tomography this influence is significant. However, in most cases the selection of scan parameters is still based on the experience of the CT user, while due to the complex measurement process the influence of the parameter choice on the measurement result cannot be quantified. Thus, in the proposed project, a methodology regarding an automated setting of scan parameters is developed, which aims at a reduced task-specific measurement uncertainty. First, the influence of image quality parameters of the individual projections on the reconstructed volume and respectively on the measurement deviation is evaluated and quantitatively described in a model. For the measurements, test bodies that show similarity to real industrial components are used. Of special interest hereby is the difference between measurement error regarding dimensions and form of geometric features. Based on the model, the required image quality of the projection then can be derived from the model and an individual set of optimal image quality parameters for each measuring tasks can be determined. The aim is to develop and validate a methodology for the automated optimization of scan parameters.