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X-ray computed tomography (CT) is a volumetric (3D) Imaging diagnostic method, well established in the medical field, and in industrial NDE as well. Developments in industrial CT aim to extent the applicability to complex structures, which do not allow the access of all directions. This are e.g. limited view, data and angle CT applications. New reconstruction algorithms are required on one
side, and the accuracy has to be improved on the other side. Numerical Simulation can support such developments by providing well defined data sets for the testing of reconstruction algorithms. This approach of virtual CT is realized within the radiographic simulator aRTist, developed by BAM. The poster shows the possibilities of this tool to consider complex scan paths. Simulated data sets have been reconstructed by an versatile backprojection algorithm.
Correctly modeling the continuous photon spectrum of X-ray tubes requires detailed knowledge of the probability distribution of electron properties at the time of X-ray photon creation, in particular electron energy, depth within the target, and direction of movement. Semi-analytical X-ray spectrum models frequently assume a very simplified or even uniform distribution of electron direction. In the case of thick targets and small deviations from normal incidence this is a useful approximation. For thin targets or large deviations from normal incidence the correct distribution of electron directions becomes more important. As calculation speed is an important aspect of semi-analytical models compared to Monte Carlo simulations, fast evaluation of the distribution of electron properties is highly desirable. The approach presented here numerically evaluates the evolution of a discrete probability distribution of electron properties due to single electron scatter interactions within a plane target. This allows capturing the important aspects of the electron distribution while achieving runtimes of a few seconds up to a minute on a standard office PC.
Die radiografische Bildqualität in ihrer klassischen Definition hängt von Kontrast, Rauschen und Unschärfe ab. Diese Parameter werden normalerweise mit Bildgüteprüfkörpern (BPK) bestimmt. Die Streustrahlung reduziert im Allgemeinen immer die Bildqualität in der Radiografie. Verschiedene Einflussgrößen werden unter Berücksichtigung von Techniken, wie Film-Radiografie, Computer-Radiografie mit Speicherfolien und digitale Radiographie mit Matrixdetektoren, analysiert. In Lehrbüchern und Standards werden das Streuverhältnis k und verschiedene Kontraste definiert. Für digitale Medien werden zusätzliche Parameter wie das Signal-Rausch-Verhältnis SNR und das Kontrast-Rausch-Verhältnis CNR eingeführt. In diesem Zusammenhang wird der Einfluss der Streustrahlung aus dem Messobjekt und dem Detektor bestehend aus Kassette bzw. Gehäuse und sensitiver Detektorschicht auf die Bildqualität ermittelt. Die numerische Modellierung wird eingesetzt, um die Streustrahlung und die Primärstrahlung aus dem Objekt separat zu bestimmen. Die Streustrahlung aus dem Objekt und Detektor erzeugen eine Abbildung des Objektes, die dem Primärstrahlungsbild überlagert ist, wobei das Streubild eine höhere Unschärfe aufweist. Dieser Effekt hängt von der Fehlergröße, dem Abstand zwischen Detektor und Objekt und der Zwischenfilterung ab.
The new standard ISO 176362:2013 'NDT of welds: Radiographic testing - Part 2: X- and gamma ray techniques with digital detectors' describes a complex procedure for film replacement by phosphor imaging plates and digital detector arrays. RT modeling software should consider these detector types, X-ray film, and the standard requirements for image quality. Practitioners expect the same visibility of image quality indicators (IQI) in the simulated radiographs as in the experimental exposures. The proposed benchmark test is based on the comparison of experimental radiographs taken at BAM with modeled ones of participants. The experimental setup and the determination of the equivalent penetrameter sensitivity (EPS) as described in the procedure of ASTM E 746 are used for quantitative evaluation of the achievable contrast sensitivity for step hole IQIs as considered in Annex B of ISO 17636-2. System classification data for Computed Radiography (CR) and film systems will be provided by BAM according to ISO 116991 for selected film systems and according to ASTM E 2446 for selected CR systems. The classification of films and digital detectors is based on the measurement of the dose response function, the basic spatial resolution (SRb) of the image, and the measured image noise, which depends on the detector efficiency, the quantum statistics, and the detector fixed pattern noise.
Industrial Radiology
(2006)
The computer simulation of radiography is applicable for different purposes in NDT such as for the qualification of NDT systems, the optimization of system parameters, feasibility analysis, model-based data interpretation, education and training of NDT/NDE personnel, and others. Within the framework of the European project PICASSO simulators will be adapted to support reliability assessments of NDT tasks. The radiographic simulator aRTist developed by BAM is well suited for this task. It combines analytical modelling of the RT inspection process with the CAD-orientated object description applicable to various industrial sectors such as power generation, aerospace, railways and others. The analytic model includes the description of the radiation source, the interaction of Radiation
with the material of the part, and the detection process with special focus to DIR. To support reliability estimations the simulation tool is completed by a tool for probability of detection (POD) estimation. It consists of a user interface for planning automatic simulation runs with varying parameters, specifically defect variations.
Further, an automatic image analysis procedure is included to evaluate the defect visibility and calculate the POD therefrom.
Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability assessment of film and digital radiography. NDT of safety relevant components of aerospace industry requires the proof of probability of detection (POD) of the inspection. Modeling tools can reduce the expense of such extended, time consuming NDT trials, if the result of simulation fits to the experiment. Our analytic simulation tool consists of three modules for the description of the radiation source, the interaction of radiation with test pieces and flaws, and the detection process with special focus on film and digital industrial radiography. It features high processing speed with near–interactive frame rates and a high level of realism. A concept has been developed as well as a software extension for reliability investigations, completed by a user interface for planning automatic simulations with varying parameters and defects. Furthermore, an automatic image analysis procedure is included to evaluate the defect visibility. The radiographic modeling from 3D CAD of aero engine components and quality test samples are compared as a precondition for real trials. This enables the evaluation and optimization of film replacement for application of modern digital equipment for economical NDT and defined POD.
Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical
Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability
assessment of film and digital radiography. A simulation supported probability of detection (POD) methodology
has been developed and the validity of the approach has been studied using an application from the aeronautics
industry. An experimental POD has been determined with the help of a specialized software tool, developed to
aid with the collection of large series of POD data. The resulting POD is compared to simulations of the same
setting using aRTist and the newly available module for simulation supported POD. A quantitative agreement
within a few percent is achieved between the experimental and the simulation supported POD.