Simulation of Radiographic Techniques

Nondestructive evaluation (NDE) contributes to the integrity and safe operation of engineered components and structures, providing information on the presence of defects and the actual conditions during production and operation, as well. The use of appropriate models for NDE techniques, which are capable to predict the output of an NDE system quantitatively, have an important impact on the reliability and efficiency of modern NDE methods. During the last years there has been remarkable progress made in the development and the use of models to describe the total transfer chain of NDE systems. Actually there are available a number of CAD-based NDE simulation tools for several standard NDE techniques such as ultrasonics, eddy currents, and radiography. It turns out that the following areas are of major interest for the application of NDE simulators: — the use of models during the design process to ensure the inspectability of the engineered components at the earliest possible stage — the use of models for feasibility analysis, e.g. for damage analysis to investigate whether the producer or the user of the component have considered all state-of-the-art NDE techniques to ensure the safe operation of the component while avoiding its damage, or to investigate the applicability of standard techniques for specialized testing problems — the use of models to develop new NDE techniques, extend their measurement capabilities including model-based data interpretation and 3-dimensional reconstruction of material properties, or to optimize standard techniques for special applications — the use of models for reliability investigations and validation tasks in terms of the prediction of probability of detection (POD) to describe the potential capability of the NDE method excluding human factor, the definition of parameters essentially influencing the response of the NDE system including their accessible ranges, or the application of models as a part of a modular validation procedure — the use of models for education and training purposes where interactive training tools will improve the learning experience, and reduces the time on task for students and the material costs as well</p

Simulation of Radiographic Techniques

Nondestructive evaluation (NDE) contributes to the integrity and safe operation of engineered components and structures, providing information on the presence of defects and the actual conditions during production and operation, as well. The use of appropriate models for NDE techniques, which are capable to predict the output of an NDE system quantitatively, have an important impact on the reliability and efficiency of modern NDE methods. During the last years there has been remarkable progress made in the development and the use of models to describe the total transfer chain of NDE systems. Actually there are available a number of CAD-based NDE simulation tools for several standard NDE techniques such as ultrasonics, eddy currents, and radiography. It turns out that the following areas are of major interest for the application of NDE simulators: — the use of models during the design process to ensure the inspectability of the engineered components at the earliest possible stage — the use of models for feasibility analysis, e.g. for damage analysis to investigate whether the producer or the user of the component have considered all state-of-the-art NDE techniques to ensure the safe operation of the component while avoiding its damage, or to investigate the applicability of standard techniques for specialized testing problems — the use of models to develop new NDE techniques, extend their measurement capabilities including model-based data interpretation and 3-dimensional reconstruction of material properties, or to optimize standard techniques for special applications — the use of models for reliability investigations and validation tasks in terms of the prediction of probability of detection (POD) to describe the potential capability of the NDE method excluding human factor, the definition of parameters essentially influencing the response of the NDE system including their accessible ranges, or the application of models as a part of a modular validation procedure — the use of models for education and training purposes where interactive training tools will improve the learning experience, and reduces the time on task for students and the material costs as wel

The Effect of Scattered Radiation in X-Ray Techniques—Experiments and Theoretical Considerations

Scattered radiation generated inside a specimen may significantly influence the flaw sensitivity by reducing the relative contrast of the flaw indication [1]. This statement holds if the scattered radiation produces a uniform intensity distribution in the film or detector plane, i.e. it is non-image forming while contributing to the radiographie projection. The introduction of built-up factors yields an appropriate description of the corresponding relative contrast reduction in the radiographie image [2]. In general, the underlying physical process can be treated as an X-ray or photon transport problem [3–6] based on a Boltzmann type equation. This approximation does not need the assumption of a uniform distributed field of scattered radiation. There are several attempts known to solve this problem for NDE applications in terms of Monte Carlo simulation [5, 7–8]. But this technique is only in a qualified sense applicable to practical testing problems with a large variety of factors like 3D object description, finite focal spot, energy dependence of source and interaction mechanisms, and others to be considered requiring a huge number of realizations to receive statistically significant results. Other techniques based on the solution of the corresponding integral transport equation [9–10] employing two stage algorithms. The first stage is known as transport stage where the photon flow resulting from the angular photon sources are computed. The second stage is known as the source computing stage where the scattering sources resulting from the Compton or coherent scattering are computed. Results from these calculations show, that for some cases the scattered radiation does not only decrease the contrast in a radiograph but shows a geometrical dependence which overlays the image from the direct radiation. Finally, an analytical simulation procedure to describe the scattered photon flux was developed which is based on the theory of Markovian processes with random structure [11–12].</p

3D X-Ray Reconstruction from Strongly Incomplete Noisy Data

Recently we reported [1–3] on the theory and the technique of reconstructing three- dimensional images of flaws and inclusions from an extremely limited number of cone- beam X-ray projections. The number of projections is chosen between two and seven and they are achieved in an observation angle smaller than 180 degrees. We introduced an approach using the Bayesian reconstruction (BR) with Gibbs prior in the form of mechanical models like noncausal Markov fields. As it was pointed out the convergence of the iteration reconstruction procedure depends on the chosen prior functional within a compact set of solutions. We investigated the capabilities of three types of a priori functional, which are represented by Gibbs energies. Corresponding to the supported structures, they were named (i) cluster support, (ii) plane support and (iii) phase support. While examining the phase support we made an effort to estimate the influence of Gaussian white noise on the quality of restoration. The noise was generated artificially and superimposed to the two dimensional x-ray images. It was shown that the algorithm was stable despite the disturbance of the noise. On the other hand it was observed that an increasing noise level leads to a noticeable deterioration of the quality of the restored image. The restoration of images from extremely incomplete and noisy data is a strict practical demand in many cases. This explains the effort to investigate the influence of noise to the reconstruction results.</p

3D X-Ray Reconstruction from Strongly Incomplete Noisy Data

Recently we reported [1–3] on the theory and the technique of reconstructing three- dimensional images of flaws and inclusions from an extremely limited number of cone- beam X-ray projections. The number of projections is chosen between two and seven and they are achieved in an observation angle smaller than 180 degrees. We introduced an approach using the Bayesian reconstruction (BR) with Gibbs prior in the form of mechanical models like noncausal Markov fields. As it was pointed out the convergence of the iteration reconstruction procedure depends on the chosen prior functional within a compact set of solutions. We investigated the capabilities of three types of a priori functional, which are represented by Gibbs energies. Corresponding to the supported structures, they were named (i) cluster support, (ii) plane support and (iii) phase support. While examining the phase support we made an effort to estimate the influence of Gaussian white noise on the quality of restoration. The noise was generated artificially and superimposed to the two dimensional x-ray images. It was shown that the algorithm was stable despite the disturbance of the noise. On the other hand it was observed that an increasing noise level leads to a noticeable deterioration of the quality of the restored image. The restoration of images from extremely incomplete and noisy data is a strict practical demand in many cases. This explains the effort to investigate the influence of noise to the reconstruction results