Development of a virtual metrological CT for numerical measurement uncertainty determination using aRTist 2

Abstract

The development of a virtual metrological CT for numerical measurement uncertainty determination at the Institute of Manufacturing Metrology (Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Germany) using the software aRTist 2 by the BAM German Federal Institute for Materials Research and Testing is described. The virtual metrological CT uses a Monte-Carlo approach for numerical measurement uncertainty determination. Results demonstrating that numerical uncertainty determination according to GUM Supplement 1 and in accordance with uncertainty determination according to guideline VDI/VDE 2630 Part 2.1 is possible for selected measurement tasks are presented.

Methodologies for model parameterization of virtual CTs for measurement uncertainty estimation

“…Thus, geometrical deviations can be characterised as a set of unknown time and system dependent functions. In previous attempts, a drift-based deviation model was proposed to integrate a cumulated set of deviations into the aRTist simulation [15]. Even though the proposed model was able to reconstruct the task specific uncertainties of a reference measurement, the approach needed adjusted uncertainty intervals, which had to be provided by an experienced system operator.…”

Convergence Behaviour of Numerical Measurement Uncertainty Evaluation using a Virtual Metrological Computed Tomography System

“…The digital twin and Monte Carlo framework used in this study is adapted to the Werth Messtechnik GmbH (Gießen, Germany) TomoCheck 200 3D as described in [19]. The digital twin was developed using the software aRTist 2.8.3 (BAM Federal Institute of Materials Research and Science (Berlin, Germany) [1]).…”

“…An example for the use of aRTist 2 for numerical measurement uncertainty evaluation can be found in [8]. The methodological description of this digital twin can be found in [19]. In this contribution, we want to address the necessary number of Monte Carlo trials for the convergence of the numerically evaluated measurement uncertainties.…”

“…Prior work at the Institute of Manufacturing Metrology showed the potential to numerically evaluate task-specific measurement uncertainties in good agreement with values determined experimentally in accordance with the VDI/VDE standard 2630 Part 2.1 [18] for an unproblematic measurement task (see [8]). Details on the digital twin and the Monte Carlo method used can be found in [19]. In this prior work, the number of simulations for the Monte Carlo trials was chosen based on computational feasibility and expert knowledge.…”

Implementation of Parameterized Work Piece Deviations and Measurement Uncertainties into Performant Meta-models for an Improved Tolerance Specification

“…For CT, the visual evaluation of the locally varying uncertainties directly gives insight into the underlying X-ray penetration lengths (because they directly affect the single point noise due to the impaired signal to noise properties of the recorded projections). The method was successfully used to correct systematic measurement errors in CT measurements by determining the systematic measurement error (here represented by the mean value of k d ) of a simulated measurement series using the virtual CT system from (Wohlgemuth et al, 2018) and subsequently correcting the faulty contributions . It was shown in that the weighted data fusion of surface data sets using locally defined quality parameters could lead to a better measurement result.…”