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Determination of the optimal imaging parameters in industrial computed tomography for dimensional measurements on monomaterial workpieces

Authors :
Natalia Grozmani
Andrea Buratti
L V Sartori
Robert Schmitt
Christoph Voigtmann
Source :
Measurement Science and Technology. 29:115009
Publication Year :
2018
Publisher :
IOP Publishing, 2018.

Abstract

Industrial computed tomography (CT) plays a key role in 3D coordinate metrology as an alternative to conventional coordinate measuring machines. CT measurement uncertainty depends on the setup parameters with which CT scans are performed. Currently, there is no established model that can describe the relationship between CT setup parameters and measurement uncertainty, and thus determine the optimal settings for a given measurement task. In practice, CT users choose setup parameters intuitively causing high variability in the measurement results. In this study, we enhance and validate an analytical method for optimizing imaging parameters. The proposed method is based on the assumption that minimizing the contribution of imaging parameters to measurement uncertainty corresponds to (1) maximizing image contrast and signal, (2) minimizing geometric blurring, and (3) minimizing image noise and CT artifacts. It also requires information about the workpiece nominal geometry and material composition. The proposed method calculates the optimal photon energy for precise surface determination, given the workpiece position and orientation. Tube voltage and prefilter are determined so that the resulting x-ray spectrum has an effective energy equal to the optimal energy and beam hardening artifacts are minimized. Tube current is chosen to maximize image signal, while avoiding blurring and excessive generated tube power. Exposure time is chosen as the shortest time that fully exploits the detector dynamics. The proposed method was validated by analyzing the standard deviations of CT measurements on a test phantom. An analysis of variance on the uncertainty components showed that the predicted parameters were globally optimal.

Details

ISSN :
13616501 and 09570233
Volume :
29
Database :
OpenAIRE
Journal :
Measurement Science and Technology
Accession number :
edsair.doi...........e3e5449c1bb52bbdfead8bdd5e5a17cc