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Organisationseinheit der BAM
The lack of traceability to meter of X-ray Computed Tomography (CT) measurements still hinders a more extensive acceptance of CT in coordinate metrology and industry. To ensure traceable, reliable, and accurate measurements, the determination of the task-specific measurement uncertainty is necessary. The German guideline VDI/VDE 2630 part 2.1 describes a procedure to determine the measurement uncertainty for CT experimentally by conducting several repeated measurements with a calibrated test specimen. However, this experimental procedure is cost and effort intensive. Therefore, the simulation of dimensional measurement tasks conducted with X-ray computed tomography can close these drawbacks. Additionally, recent developments towards a resource and cost-efficient production (“smart factory”) motivate the need for a corresponding numerical model of a CT system (“digital twin”) as well. As there is no standardized procedure to determine the measurement uncertainty of a CT system by simulation at the moment, the project series CTSimU was initiated, aiming at this gap. Concretely, the goal is the development of a procedure to determine the measurement uncertainty numerically by radiographic simulation. The first project (2019-2022), "Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU" developed a framework to qualify a radiographic simulation software concerning the correct simulation of physical laws and functionalities. The most important outcome was a draft for a new guideline VDI/VDE 2630 part 2.2, which is currently under discussion in the VDI/VDE committee. The follow-up project CTSimU2 "Realistic Simulation of real CT systems with a basic-qualified Simulation Software" will deal with building and characterizing a digital replica of a specific real-world CT system. The two main targets of this project will be a toolbox including methods and procedures to configure a realistic CT system simulation and to develop tests to check if this replica is sufficient enough. The result will be a draft for a follow-up VDI/VDE guideline proposing standardized procedures to determine a CT system's corresponding characteristics and test the simulation (copy) of a real-world CT system which we call a "digital twin".
Various software products for the simulation of industrial X-ray radiography have been developed in recent years (e.g., aRTist 2, CIVA CT, Scorpius XLab, SimCT, Wilcore) and their application potential has been shown in numerous works. However, full systematic approaches to characterise a specific CT system for these simulation software products to obtain a truthful digital twin are still missing. In this contribution, we want to present two approaches to obtain realistic grey values in X-ray projections in aRTist 2 simulations based on measured projections. In aRTist 2, the displayed grey value of a pixel is based on the energy density incident on that pixel.
The energy density is calculated based on the X-ray tube spectrum, the attenuation between source and detector as well as an energy-dependent sensitivity curve of the detector. The first approach presented in this contribution uses the sensitivity curve as a free modelling parameter. We measured the signal response at different thicknesses of Al EN-AW6082 at different tube voltages (i.e., different tube spectra). We then regarded the grey values displayed by these projections as a data regression respectively an optimisation problem and obtained the sensitivity curve that is best able to reproduce the measured behaviour in aRTist 2. The resulting sensitivity curve does not necessarily hold physical meaning but is able to simulate the real system behaviour in the simulation software.
The second approach presented in this contribution is to estimate the sensitivity curve based on assumptions about the characteristics of the scintillation detector (e.g., scintillator material, scintillator thickness and signal processing characteristics). For this approach, a linear response function (linear relationship between the deposited energy per pixel and the resulting grey value) is assumed. If the detector characteristics, which affect the simulated deposited energy, are properly modelled, the slope and offset of the response function to match the measured grey values should be the same for different tube spectra. As the offset is constant and given by the grey values measured at no incident radiation, the slope is the remaining parameter to evaluate the success of the detector modelling. We therefore adapted the detector characteristics by changing the detector setup until the slope was nearly the same for all measured tube spectra. We are aware that the resulting parameters of the scintillator material and thickness might not be the real ones, but with those modelling parameters we are able to simulate realistic grey values in aRTist 2. Both of those approaches could potentially be a step forward to a full systematic approach for a digital twin of a real CT system in aRTist 2.
Die industrielle Röntgen-Computertomografie (CT) etabliert sich für die Anwendung in der dimensionellen Messtechnik. Sie bietet als zerstörungsfreies Messverfahren das Potential, sowohl innen- als auch außenliegende Merkmale holistisch zu erfassen. Für die Bestimmung der Güte eines Messwerts muss die dem Messwert zugeordnete Messunsicherheit ermittelt werden. Dabei kann, nach derzeitigem Stand der Technik und Normung, die aufgabenspezifische Messunsicherheit nach VDI/VDE 2630 Blatt 2.1 nur unter hohem Aufwand mit einer Vielzahl an experimentellen Wiederholmessungen ermittelt werden. Ziel diverser Forschungs-projekte zu diesem Thema ist es daher, eine numerische Messunsicherheitsbestimmung zu erreichen. Dafür ist es notwendig, alle signifikanten Einflussgrößen zu erfassen, deren Unsicherheitsbeiträge zu bestimmen und zu bewerten. In diesem Beitrag wird der Einfluss des Bildrauschens auf verschiedene dimensionelle Messgrößen simulativ untersucht. Mithilfe eines prismatischen Prüfkörpers, der eine Vielzahl an Geometrieelementen aufweist, werden verschiedene Messgrößen unterschiedlicher Komplexität betrachtet. Ziel ist es, für diese Messgrößen zu testen, wie diese auf das Bildrauschen reagieren. Dieses wird dabei durch das Signal-Rausch-Verhältnis (SNR) der Projektionsgrauwerte beschrieben und variiert. Es werden Wiederholsimulationen durchgeführt, damit eine statistische Aussage über die Verteilung der Messwerte möglich ist und der Einfluss des Rauschens auf verschiedene Messgrößen individuell beurteilt werden kann. Das Simulationsszenario wird so gestaltet, dass lediglich das Bildrauschen Einfluss auf die Messung hat. Die berechneten Verteilungsbreiten lassen mit sinkendem SNR eine deutliche Zunahme erkennen, insbesondere bei der Bestimmung von Formabweichungen. Simuliert wird mit der Software aRTist 2.10 (BAM).
A software toolbox is introduced that addresses several needs common to computed tomography (CT). Built for the WIPANO CTSimU project to serve as the reference implementation for its image processing and evaluation tasks, it provides a Python 3 interface that is adaptable to many conceivable applications. Foremost, the toolbox features a pipeline architecture for sequential 2D image processing tasks, such as flat field corrections and image binning, and enables the user to create their own processing modules. Beyond that, it provides means to measure line profiles and image quality assessment algorithms to calculate modulation transfer functions (MTF) or to determine the interpolated basic spatial resolution (iSRb) using a duplex wire image. It can also be used to calculate projection matrices for the reconstruction of scans with arbitrary industrial CT geometries and trajectories. The CTSimU project defined a framework of projection- and volume-based test scenarios for the qualification of radiographic simulation software towards its use in dimensional metrology. The toolbox implements the necessary evaluation routines and generates reports for all projection-based tests.
The ability of industrial X-ray computed tomography (CT) to scan an object with several internal and external features at once causes increasing adoption in dimensional metrology. In order to evaluate the quality of a measurement value, the task-specific measurement uncertainty has to be determined. Currently, VDI/VDE 2630 part 2.1 gives a guideline to determine the uncertainty of CT measurements experimentally by conducting repeated measurements. This is costly and time-consuming. Thus, the aim is to determine the task-specific measurement uncertainty numerically by simulations (e. g. according to the guide to expression of uncertainty in measurement (GUM) Supplement 1). To achieve that, a digital twin is necessary. This contribution presents a simple first approach how a digital twin can be built. In order to evaluate this approach, a study comparing measurements and simulations of different real CT systems was carried out by determining the differences between the measurement results of the digital twin and of the measurement results of the real-world CT systems. The results have shown a moderate agreement between real and simulated data. To improve on this aspect, a standardized method to characterize CT systems and methods to implement CT parameters into the simulation with sufficient accuracy will be developed.
An important focus of research in Industrial X-ray Computed Tomography (CT) is to determine the task-specific measurement uncertainty of CT measurements numerically by using simulations. For this, all relevant influence factors need to be identified and quantified. It is known, for example, that geometrical misalignments of the detector lead to measurement deviations if the reconstruction does not consider these misalignments. This contribution uses computer simulation of CT data to investigate the influence of geometrical misalignments of the detector on several measurands found in typical measurements tasks in the industry. A newly developed test specimen with a broad variety of features is used for this study. Angular and positional detector deviations are systematically introduced into the simulations and deliberately left uncompensated during the CT reconstruction. The resulting measurement deviations are shown and discussed.
This contribution presents a set of largely novel reference standards specially designed for testing different important physical effects and functionalities of radiography-based computed tomography (CT) simulation software. These standards were developed within the scope of the German cooperation project “CTSimU – Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation” [1] and serve as tools for the basic qualification of the sufficient physical correctness and required features of simulation software of CT-based coordinate measurement systems (CMSs) via the analyses either of 2D projection images only or of full CT scans. The results serve as input to the German standardisation committee for the development of a new national VDI/VDE guideline in the series VDI/VDE 2630 dealing with the basic qualification aspect of CT simulation software and shall lay ground for the measurement uncertainty determination of dimensional measurements using CT.
Radiografische Simulationswerkzeuge wie aRTist, ScorpiusXLab, SimCT oder CIVA CT verwenden analytische Methoden und physikalische Monte-Carlo-Teilchentransportsimulationen, um die Interaktionsprozesse zwischen Röntgenstrahlung und Materie zu simulieren. Die berechneten Projektionen bilden anschließend unter Berücksichtigung einer definierten Scan-Trajektorie die Basis der Simulation einer röntgencomputertomografischen Untersuchung.
Für den erfolgreichen Einsatz der Computertomografie, sei es als zerstörungsfreie Prüfmethode oder beim dimensionellen Messen, ist es generell notwendig, bekannte Fehler- bzw. Abweichungsquellen des Messverfahrens auszuschließen oder zu reduzieren. Dabei hat sich gezeigt, dass die Auswahl der Messparameter und die Erfahrung des Anwenders direkten Einfluss auf das erzielbare Messergebnis einer computertomografischen Untersuchung nehmen. Es ist daher sinnvoll, die Parameterauswahl in einem virtuellen Simulationsaufbau vorher zu erproben und an die Messaufgabe anzupassen.
Neben der Optimierung von Messparametern finden radiografische Simulationswerkzeuge auch Anwendung für Machbarkeitsstudien und werden zur Schulung von Anwendern im Bereich der Röntgen-Computertomografie verwendet.
Radiografische Simulationswerkzeuge befinden sich in einem stetigen Wandel, beispielsweise durch die Entwicklung neuer Rekonstruktionsmethoden, durch Erweiterung von analytischen Modellen, durch Integration komplexer Trajektorien oder durch Berücksichtigung von prozessbedingten geometrischen Abweichungen. Im laufenden EMPIR-Projekt „AdvanCT“ entsteht deshalb ein „Good Practice Guide“ für die Simulationsumgebung aRTist. Ziel dieses Guides ist es, die mit steigender Komplexität verbundenen Einstiegshürden für Anwender von aRTist zu reduzieren, um damit einen praxisnahen Zugang zur virtuellen Computertomografie zu ermöglichen. Dabei werden anhand von praktisch nachvollziehbaren Beispielen die grundlegenden Mechanismen der Simulationsumgebung erklärt und ein strukturierter Leitfaden zur Simulation röntgencomputertomografischer Untersuchungen mit aRTist vermittelt.
In diesem Beitrag werden erste Auszüge des Guides sowie eine Übersicht der weiteren geplanten Themen für die anschließende Diskussion vorgestellt.
Numerical measurement uncertainty determination for dimensional measurements of microparts with CT
(2016)
Up to now, the only standardized method to determine the measurement uncertainty for computed tomography (CT) is to use calibrated workpieces as specified in the Guideline VDI/VDE 2630 Part 2.1. This paper discusses a promising numerical method for uncertainty determination with help of a virtual metrological CT (VMCT). It gives an explanation of the adjustments, the input parameters and the execution of the simulation. Furthermore, it discusses the first results of uncertainty determination compared to the method of using calibrated workpieces with the aid of two example cases.
Methodologies for model parameterization of virtual CTs for measurement uncertainty estimation
(2022)
X-ray computed tomography (XCT) is a fast-growing technology for dimensional measurements in industrial applications. However, traceable and efficient methods to determine measurement uncertainties are not available. Guidelines like the VDI/VDE 2630 Part 2.1 suggest at least 20 repetitions of a specific measurement task, which is not feasible for industrial standards. Simulation-based approaches to determine task specific measurement uncertainties are promising, but require closely adjusted model parameters and an integration of error sources like geometrical deviations during a measurement. Unfortunately, the development of an automated process to parameterize and integrate geometrical deviations into XCT models is still an open issue. In this work, the whole processing chain of dimensional XCT measurements is taken into account with focus on the issues and requirements to determine suitable parameters of geometrical deviations. Starting off with baseline simulations of different XCT systems, two approaches are investigated to determine and integrate geometrical deviations of reference measurements. The first approach tries to iteratively estimate geometric deviation parameter values to match the characteristics of the missing error sources. The second approach estimates those values based on radiographs of a known calibrated reference object. In contrast to prior work both approaches only use a condensed set of parameters to map geometric deviations. In case of the iterative approach, some major issues regarding unhandled directional dependencies have been identified and discussed. Whereas the radiographic method resulted in task specific expanded measurements uncertainties below one micrometre even for bi-directional features, which is a step closer towards a true digital twin for uncertainty estimations in dimensional XCT.