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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.
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.
Photon counting detectors (PCD) offer new possibilities for x-ray micro computed tomography (CT) in the field of non-destructive testing. For large and/or dense objects with high atomic numbers the problem of scattered radiation and beam hardening severely influences the image quality. This work shows that using an energy discriminating PCD based on CdTe allows to address these problems by intrinsically reducing both the influence of scattering and beam hardening.
Based on 2D-radiographic measurements it is shown that by energy thresholding the influence of scattered radiation can be reduced by up to in case of a PCD compared to a conventional energy-integrating detector (EID).
To demonstrate the capabilities of a PCD in reducing beam hardening, cupping artefacts are analyzed quantitatively. The PCD results show that the higher the energy threshold is set, the lower the cupping effect emerges. But since numerous beam hardening correction algorithms exist, the results of the PCD are compared to EID results corrected by common techniques. Nevertheless, the highest energy thresholds yield lower cupping artefacts than any of the applied correction algorithms.
As an example of a potential industrial CT application, a turbine blade is investigated by CT. The inner structure of the turbine blade allows for comparing the image quality between PCD and EID in terms of absolute contrast, as well as normalized signal-to-noise and contrast-to-noise ratio. Where the absolute contrast can be improved by raising the energy thresholds of the PCD, it is found that due to lower statistics the normalized contrast-to-noise-ratio could not be improved compared to the EID. These results might change to the contrary when discarding pre-filtering of the x-ray spectra and thus allowing more low-energy photons to reach the detectors.
Despite still being in the early phase in technological progress, PCDs already allow to improve CT image quality compared to conventional detectors in terms of scatter and beam hardening reduction.