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The progress in X-ray detector electronics (sensitivity and speed) allows meanwhile fast single photon detection by a matrix detector. Combined photon counting and energy discrimination is implemented in the electronic circuit of each detector pixel. The company XCounter developed detectors based on CdTe single crystals, which can be tiled to larger areas and have a pixel size of 100ìm. The largest area available in beginning of 2014 is 50x75 mm². These detectors have very promising properties, which make them very suitable for NDT applications:
1. A CdTe attenuation layer of 750 µm thickness allows efficient X-ray detection up to ca. 300 keV. In counting mode only photon noise is important; no other detector noise sources need to be considered. There is no Offset signal without radiation.
2. Each of the detector pixels has two energy thresholds. These can be used for dual energy imaging for materials separation. Also the suppression of scattered radiation by energy thresholding will improve the image contrast sensitivity. First experiments will be presented which demonstrate the advantages of this new detector technology over the conventional charge integrating detectors.
A challenge is the development of a modified detector calibration procedure, which becomes critical at longer exposure times.
Carbon fiber reinforced polymer ropes are gaining in significance in the fields of civil engineering and hoisting applications. Thus, methods of non-destructive testing (NDT) need to be developed and evaluated with respect to new challenges and types of defects. Particularly important is the development of in-service testing solutions which allow the integration in global online monitoring systems. Conventional methods like electrical resistivity or strain measurements using optical fibers are already in use. This study investigates the possibility of using various X-ray techniques to increase the reliability and significance of NDT and their applicability to in-service testing. Conventional film radiography is the most common technique; however, even after image enhancement of the digitized film, this technique lacks contrast sensitivity and dynamic range compared to digital detector array (DDA) radiography. The DDA radiography is a highly sensitive method; yet, the limitation is that it delivers 2D images of 3D objects. By the use of co-planar translational laminography the detectability of planar defects is superior to 2D methods due to multiple projection angles. Apart from this, it can be used on-site due to a rather simple setup and robust equipment. In this work two photon counting detectors (PCD) with different sensor materials (Si and CdTe) were used. The results show that the resolution and defect recognition is lower in case of DDA radiography and laminography using PCDs compared to high-resolution computed tomography. However, the DDA radiography and laminography are sensitive enough to both fiber breakage and delaminations and can be significantly advantageous in terms of measurement time and adaptability for on-site monitoring.
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.
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.
Defect recognition in CFRP components using various NDT methods within a smart manufacturing process
(2018)
The manufacturing process of carbon fiber reinforced polymer (CFRP) components is gaining a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing process are e.g. porosity and voids which may lead to delaminations during operation and under load. To find irregularities and classify them as possible defects in an early stage of the manufacturing process is of high importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we compare various NDT methods which were applied to similar CFRP laminate samples in order to detect and characterize regions of defective volume. Besides ultrasound, thermography and eddy current, different X-ray methods like radiography, laminography and computed tomography are used to investigate the samples. These methods are compared with the intention to evaluate their capability to reliably detect and characterize defective volume. Beyond the detection and evaluation of defects, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method shall be applied is inherent within the process. Is it possible to design an in-line or at-line testing process which can recognize defects reliably and reduce testing time and costs? This study aims to show up opportunities of designing a smart NDT process synchronized to the production based on the concepts of smart production (Industry 4.0). A set of defective CFRP laminate samples and different NDT methods were used to demonstrate how effective defects are recognized and how communication between interconnected NDT sensors and the manufacturing process could be organized.
3D structural investigations are described by X-ray laminography studies of sandwich shell segments, made of a PVC foam core, covered by non-crimp fabric glass fibre composite lay-ups processed by vacuum assisted resin infusion of epoxy. The specific scope of this study is to image transversal flaws within the foam core (joints) and of single ply overlaps. Test flaws were purposely implemented in order to simulate typical failure under cyclic load. In a dedicated test rig for shell structures, the flaw evolution/propagation is monitored by thermography and optical 3D inspection of deformation. Due to the unfavourable preconditions for classical computed tomography as of large aspect ratio, the samples were investigated by coplanar translational laminography. Its limited range of observation angles of ± 45°, results in anisotropic artefacts about the normal to the sample surface, but the typical flaws are well visualized in the as-prepared state, in a state of early damage, and in the repaired state.
Laminography is a widely used NDT technique for large flat object which cannot be investigated by traditional computed tomography. However, due to the limited scanning angle of laminography, the reconstructed image has more artifact interference, which seriously affects the reconstructed image quality. Reducing artifacts of the laminography image and enhancing the images have become important research effort. In this paper, we present dual-energy materials characterization methods based on photon counting detectors to reduce artifacts and enhance image for laminography. The photon counting detector used in this study allows the setting of two independent energy thresholds in order to acquire dual-energy images for laminography from a single scan. The dual energy imaging methods of basis material decomposition (BMD) and weighted logarithmic subtraction (WLS) were studied in the paper with respect to laminography image enhancement. A fast decomposition algorithm on laminographic projection domain with approximating the inverse dual-energy equations to calculate the thickness of basic materials was used in the BMD dual-energy imaging methods. The experimental results show that the BMD method can characterize materials and enhance features of the basic material within the laminographic dataset. In the WLS method, a linear operation was applied on dual-energy images reconstruction directly, which can eliminate the attenuation of one specific material in the resultant image by setting an appropriate weighting factor. In our experiments. WLS method was used successfully to eliminate the strong artifacts generated by the special material and enhance the images. Dual-energy materials characterization methods based on photon counting detectors show potential applications in laminography.
A composite material is a combination of two or more materials with very different mechanical, thermal and electrical properties. The various forms of composite materials, due to their high material properties, are widely used as structural materials in the aviation, space, marine, automobile, and sports industries. However, some defects like voids, delamination, or inhomogeneous fiber distribution that form during the fabricating processes of composites can seriously affect the mechanical properties of the composite material. In this study, several imaging NDE techniques such as: thermography, high frequency eddy current, ultrasonic, x-ray radiography, x-ray laminography, and high resolution x-ray CT were conducted to characterize the microstructure of carbon fiber composites. Then, a 3D analysis was implemented by the destructive technique of serial sectioning for the same sample tested by the NDE methods. To better analyze the results of this work and extract a clear volume image for all features and defects contained in the composite material, an intensive comparison was conducted among hundreds of 3D-NDE and multi serial sections’ scan images showing the microstructure variation.
Carbon fiber composites have been increasingly used in aerospace, military, sports, automotive and other fields due to their excellent properties, including high specific strength, high specific modulus, corrosion resistance, fatigue resistance, and low thermal expansion coefficient. Interlaminar fracture is a serious failure mode leading to a loss in composite stiffness and strength. Iscontinuities formed during manufacturing process degrade the fatigue life and interlaminar fracture resistance of the composite. In his study, three approaches were implemented and their results were correlated to quantify discontinuities effecting static and fatigue interlaminar fracture behavior of carbon fiber composites.
Samples were fabricated by hand layup vacuum bagging manufacturing process under three different vacuum levels, indicated High (-686 mmHg), Moderate (-330 mmHg) and Poor (0 mmHg). Discontinuity content was quantified throughthickness by destructive and nondestructive techniques. Eight different NDE methods were conducted including imaging NDE methods: X-Ray laminography, ultrasonic, high frequency eddy current, pulse thermography, pulse phase thermography and lock-in-thermography, and averaging NDE techniques: X-Ray refraction and thermal conductivity measurements. Samples were subsequently destructively serial sectioned through-thickness into several layers. Both static and fatigue interlaminar fracture behavior under Mode I were conducted. The results of several imaging NDE methods revealed the trend in percentages of discontinuity. However, the results of averaging NDE methods showed a clear correlation since they gave specific values of discontinuity through-thickness. Serial sectioning exposed the composite’s internal structure and provided a very clear idea about the type, shape, size, distribution and location of most discontinuities included. The results of mechanical testing showed that discontinuities lead to a decrease in Mode I static interlaminar fracture toughness and a decrease in Mode I cyclic strain energy release rates fatigue life. Finally, all approaches were correlated: the resulted NDE percentages and parameters were correlated with the features revealed by the destructive test of serial sectioning and static and fatigue values in order to quantify discontinuities such as delamination and voids.
Defect recognition in CFRP components using various NDT methods within a smart manufacturing process
(2017)
The manufacturing process of carbon fiber reinforced polymer (CFRP) components is playing a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing are e.g. porosity and voids which may lead to delaminations during operation and under load. To find those defects in an early stage of the manufacturing process is of huge importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we present various NDT methods which are applied to similar CFRP laminate samples in order to detect and characterize defective volume. Besides ultrasound, thermography and eddy current, different x-ray methods like radiography, laminography and computed tomography are used to investigate the samples. These methods are compared with the intention to evaluate their capability to reliably detect and characterize defective volume. Beyond the detection of flaws, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method to apply is made by the process itself. Is it possible to design an in-line or at-line testing process which can recognize defects reliably and reduce testing time and costs? This study aims to show up opportunities of designing a smart NDT process synchronized to the production based on the ideas of smart production (Industry 4.0). A set of defective CFRP laminate samples and different NDT methods were used to demonstrate how effective defects are recognized and how communication between interconnected NDT sensors and the manufacturing process could be organized.