Michael Schrapp

Artifact reduction in non-destructive testing by means of complementary data fusion of x-ray computed tomography and ultrasonic pulse-echo testing

In industrial non-destructive testing, x-ray computed tomography (CT) and ultrasonic pulse-echo testing play an important role in the investigation of large-scale samples. One major artifact arises in CT, when the x-ray absorption in specific directions is too intense, so that the material cannot be fully penetrated. Due to different physical interaction principles, ultrasonic imaging is able to show features which are not visible in the CT image. In this contribution, we present a novel fusion method for the complementary data provided by x-ray CT and ultrasonic testing. The ultrasonic data are obtained by an adapted synthetic aperture focusing technique (SAFT) and complement the missing edge information in the CT image. Subsequently, the full edge map is incorporated as a priori information in a modified simultaneous iterative reconstruction method (SIRT) and allows a significant reduction of artifacts in the CT image.

Object Specific Trajectory Optimization for Industrial X-ray Computed Tomography.

In industrial settings, X-ray computed tomography scans are a common tool for inspection of objects. Often the object can not be imaged using standard circular or helical trajectories because of constraints in space or time. Compared to medical applications the variance in size and materials is much larger. Adapting the acquisition trajectory to the object is beneficial and sometimes inevitable. There are currently no sophisticated methods for this adoption. Typically the operator places the object according to his best knowledge. We propose a detectability index based optimization algorithm which determines the scan trajectory on the basis of a CAD-model of the object. The detectability index is computed solely from simulated projections for multiple user defined features. By adapting the features the algorithm is adapted to different imaging tasks. Performance of simulated and measured data was qualitatively and quantitatively assessed.The results illustrate that our algorithm not only allows more accurate detection of features, but also delivers images with high overall quality in comparison to standard trajectory reconstructions. This work enables to reduce the number of projections and in consequence scan time by introducing an optimization algorithm to compose an object specific trajectory.

Data fusion in neutron and X-ray computed tomography

We present a fusion methodology between neutron and X-ray computed tomography (CT). On the one hand, the inspection by X-ray CT of a wide class of multimaterials in non-destructive testing applications suffers from limited information of object features. On the other hand, neutron imaging can provide complementary data in such a way that the combination of both data sets fully characterizes the object. In this contribution, a novel data fusion procedure, called Fusion Regularized Simultaneous Algebraic Reconstruction Technique, is developed where the X-ray reconstruction is modified to fulfill the available data from the imaging with neutrons. The experiments, which were obtained from an aluminum profile containing a steel screw, and attached carbon fiber plates demonstrate that the image quality in CT can be significantly improved when the proposed fusion method is used.

Ultrasonic imaging of complex specimens by processing multiple incident angles in full-angle synthetic aperture focusing technique

In the evaluation of large-scale metallic specimens, X-ray CT suffers from limited penetration, which results in artifacts in the reconstructed image. Data fusion of information obtained by different modalities allows correction of those artifacts. In this contribution, an approach is presented to provide complementary data of the inner pattern of the specimen by ultrasonic testing in immersion mode. To process an ultrasonic imaging full-angle synthetic aperture focusing technique, data are acquired along the a priori known contour of the specimen. Substantial discrepancies in speed of sound between the couplant and the material of the specimen lead to refraction effects which are corrected by a virtual source element method. Furthermore, several incident angles at each virtual source are utilized to achieve an enhanced detectability of inner structural edges. However, arising reverberations limit image quality and must be suppressed by predictive deconvolution. Additionally, a subspace analysis and projection method is utilized to remove echoes of the a priori known surface in the reconstructed image which potentially mask information of near-surface structures. In comparison with exclusively perpendicular insonification, resulting images show a significant enhanced possibility of detection for inner structural edges even in adverse orientations for ultrasonic imaging. Furthermore, surface echoes and reverberations are suppressed by the proposed filter methods in a reliable way.

Artifact reduction in industrial computed tomography via data fusion

As the most stressed part of a gas turbine the first row of turbine blades is not only a challenge for the materials used. Also the testing of these parts have to meet the highest standards. Computed tomography (CT) as the technique which could reveal the most details also provides the biggest challenges [1]: A full penetration of large sized turbine blades is often only possible at high X-ray voltages causing disproportional high costs. A reduction of the X-ray voltage is able to reduce these arising costs but yields non penetration artifacts in the reconstructed CT image. In most instances, these artifacts manifests itself as blurred and smeared regions at concave edges due to a reduced signal to noise ratio. In order to complement the missing information and to increase the overall image quality of our reconstruction, we use further imaging modalities such as a 3-D Scanner and ultrasonic imaging. A 3-D scanner is easy and cost effective to implement and is able to acquire all relevant data simultaneous...