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Modern wind turbine rotor blades consist of sandwich shell segments made from glass fiber reinforced polymers. During manufacturing, defects can arise which could lead to failure of the whole component under dynamic mechanical and thermal loads. Hence during operation defects can arise which, if detected, can be repaired locally and in-situ by applying repair patches instead of taking the whole rotor blade down and repair it remotely. This method is much more time and cost effective, since the shut-down time of the energy converter is limited to a minimum. These repair patches can, however, also lead to new defects if not applied optimally. Therefore, it is necessary to control the quality of the repair patches to ensure the best possible restoration of structural integrity of the component. As a rotor blade is an object with a large aspect ratio, X-ray laminography is predestined to provide 3D information of the objective volume. To enhance the amount of information gained from laminographic reconstruction, we use in this study a photon counting and energy discriminating X-ray detector and apply a material decomposition algorithm to the data. By inherently separating the incident spectra within the detection process into two distinct energy bins, the basis material decomposition can provide material resolved images. Choosing glass and epoxy resin as basis materials and numerically solving the inverse dual-energy equation system, the reconstructed laminographic datasets contain highly valuable information about the distribution of the basis materials within the structure. Furthermore, cross- artifacts arising from the limited angle of the projection data can be reduced by this method which allows to investigate structures that were hidden underneath the artefacts.
Classical film radiography is a well-established NDT technique and it is most commonly used for testing weld seams and corroded pipes e.g. in oil and gas industry or in nuclear power plants. In the course of digitization, digital detector arrays (DDA) are finding their way into industrial applications and are replacing film radiography step by step. This study deals with the latest generation of DDAs, the photon counting and energy resolving detectors (PCD), and their characteristics compared to charge integrating detectors (CID). No matter which technology to use, radiography still lacks a general issue: A three-dimensional object is projected onto a two dimensional image. Of course, advanced computed tomography (CT) algorithms exist since many years, but if the object to investigate is too large to fit into the manipulation system or its shape is not appropriate, CT is not feasible or sensible to be applied. To overcome this limitation, numerous laminographic algorithms have been developed in the past. In this study, photon counting detectors are used in combination with co-planar translational laminography to gain reconstructed three-dimensional volumes. Both laminographic testing and PCDs require a serious knowledge of many parameters that can influence the image quality in the resulting datasets. These are e.g. the detector efficiency and calibration procedure, setting of energy thresholds, exposure data, number of projections, beam length correction and spatial resolution. The use of PCDs yields more variables to be considered compared to CIDs. The most important parameters in laminographic testing and in the use of PCDs are described in this study and limits are discussed.
This work presents the use of limited experimental measurements to develop a set of calibrated Simulation parameters that can then be used for reliable simulation of subsea pipeline inspections. The modelling software aRTist is used as the simulation tool, and the calibration is through comparison with experimental images of a well characterised sample in a water tank. Image Quality parameters such as signal-to-noise ratio, contrast and basic spatial resolution are compared with the aim of matching simulated values to experimental results. Currently the model is partially calibrated, with signal-to-noise ratio successfully matched while differences are still found in contrast-to-noise ratio comparisons. This means that measurements depending on absolute intensity are not accurate enough in the simulation at this stage. However, the simulation is found to be accurate for wall thickness measurements in tangential images, which are not based on absolute intensity, with simulated and experimental cases producing similar results.
Since a few years the direct detection of X-ray photons into electrical signals is possible by usage of highly absorbing photo conducting materials (e.g. CdTe) as detection layer of an underlying CMOS semiconductor X-ray detector. Even NDT energies up to 400 keV are possible today, as well. The image sharpness and absorption efficiency is improved by the replacement of the unsharp scintillation layer (as used at indirect detecting detectors) by a photo conducting layer of much higher thickness. If the read-out speed is high enough (ca. 50 – 100 ns dead time) single X-ray photons can be counted and their energy measured. Read-out noise and dark image correction can be avoided. By setting energy thresholds selected energy ranges of the X-ray spectrum can be detected or suppressed. This allows material discrimination by dual-energy techniques or the reduction of image contributions of scattered radiation, which results in an enhanced contrast sensitivity. To use these advantages in an effective way, a special calibration procedure has to be developed, which considers also time dependent processes in the detection layer. This contribution presents some of these new properties of direct detecting digital detector arrays (DDAs) and shows first results on testing fiber reinforced composites as well as first approaches to dual energy imaging.