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In situ crack detection in the mushy zone and the solid weld of a gas tungsten arc (GTA) weld using X-ray imaging during welding is a new research area for NDT inspection. Usually, NDT flaw detection is done after the complete solidification of the weld seam. In this paper, we present the use of real-time radiography with a minifocus X-ray source (YXLON X-ray tube Y.TU 225-D04) and a 75μm pixel size digital detector array (Dexela 1512) for the acquisition of 2D radiographic images by a sequence of exposures with time intervals of 80 ms for hot crack detection during single pass bead-on-plate GTA welding of 3 mm thick plates of aluminium alloy AlMgSi (6060). An analysis of the crack distribution in the weld sample is conducted from the acquired 2D radiographs and its corresponding 3D volumetric reconstruction achieved by linear coplanar digital laminography.
This in situ approach opens new possibilities in the field of hot crack research by having the direct information of both the crack initiation and growth and its correlation to the welding parameters.
Generating 2D noise with local, space-varying spectral characteristics is vital where random noise fields with spatially heterogeneous statistical properties are observed and need to be simulated. A realistic, non-stationary noise generator relying on experimental data is presented. That generator is desired in areas such as photography and radiography. For example, before performing actual X-ray imaging in practice, output images are simulated to assess and improve setups. For that purpose, realistic film noise modelling is crucial because noise downgrades the detectability of visual signals. The presented film noise synthesiser improves the realism and value of radiographic simulations significantly, allowing more realistic assessments of radiographic test setups. The method respects space-varying spectral characteristics and probability distributions, locally simulating noise with realistic granularity and contrast. The benefits of this approach are to respect the correlation between noise and image as well as internal correlation, the fast generation of any number of unique noise samples, the exploitation of real experimental data, and its statistical non-stationarity. The combination of these benefits is not available in existing work. Validation of the new technique was undertaken in the field of industrial radiography. While applied to that field here, the technique is general and can also be utilised in any other field where the generation of 2D noise with local, space-varying statistical properties is necessary.
Extracting statistical characteristics from radiographic films is vital for film system classification and contrast sensitivity evaluation and serves as a basis for film noise simulation. A new method for digitising radiographic films in order to extract these characteristics is presented. The method consists of a camera-based setup and image processing procedure to digitise films. Correct optical density values and granularity can be extracted from the digitised images, which are equal to results obtained by standardised measurement procedures. Specific statistical characteristics of film noise are theoretically derived and subsequently verified by the obtained data, including characteristics such as Gaussianity and spatial spectral characteristics of the optical density fluctuations. It is shown that the presented method correctly measures the granularity of film noise and can therefore replace time-consuming microdensitometer measurements traditionally required for film system classifications. Additionally, the inherent unsharpness of film systems was investigated and compared with literature data. This comparison serves as another validation approach of the presented method.
The presently active standards on Computed Radiography (CR) need a major revision. It was observed by many users that the image quality for class B of EN 14784-2 is not achievable under the same exposure conditions as used for film exposure. A mathematical model was developed and tested, which allows the calculation of the image quality, proven by image quality indicators (IQI), depending on the fixed pattern noise and the efficiency of the used imaging plate (IP) scanner system. All tested IP scanner systems provide a fixed correlation between the measured signal/noise ratio (SNR) and the grey values in the digital images. The maximum achievable SNRmax depends on the fixed pattern noise of the plate (high dose limit). Depending on the exposure dose an optimum visibility of IQIs can be predicted by calculation and measured considering the attenuation coefficient for calculation of the contrast/noise ratio (CNR). The diameter of the just visible wire is proportional to 1/sqrt(CNR). The optimum tube voltage for best visibility of IQIs and maximum CNR depend on the exposure dose. The optimum tube voltage for best visibility is achieved only at exposures with high dose. A dose dependant optimal tube voltage was not observed for film radiography.
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.
This work presents an investigation of the accuracy of a radiographic simulation model applied to subsea pipeline inspections. Experimental measurements of a sample in a water tank are used to develop a set of calibrated simulation parameters for the modelling software aRTist. Image quality parameters such as signal-tonoise ratio, contrast and basic spatial resolution are compared with the aim of matching simulated values to experimental results. With this method signal-to-noise ratio was successfully matched while differences were still found in contrast-to-noise ratio comparisons. This means that measurements depending on absolute intensity are not accurate enough, however wall thickness measurements in tangential images, which are not based on absolute intensity, were found to produce similar results in simulated and experimental cases. The differences in contrast and intensity are thought to be due to detector backscatter and additional scatter from out-of-setup objects within the exposure bay, due to a lack of source collimation. These would affect the experimental results but were not included in the simulated setup. This was investigated by including different proportions of peripheral water and other objects in the modelled setup and examining the effect on Image quality parameters. Results show that this additional scatter has a significant impact on the radiograph, particularly on image contrast, and is therefore the likely cause of differences between experimental and simulated images. This implies that it will be very difficult to completely match simulated to experimental results, as including all possible scattering objects in the model would be very complex. An improvement could be made by using real subsea data to estimate this additional scattering, which could then be used to calibrate the model. However there would still be significant uncertainty in the ability of the model to accurately produce realistic intensity and contrast.
Radiological inspections, in general, are the nondestructive testing (NDT) methods to detect the bulk of explosives in large objects. In contrast to personal luggage, cargo or building components constitute a complexity that may significantly hinder the detection of a threat by conventional X-ray transmission radiography. In this article, a novel X-ray backscatter technique is presented for detecting suspicious objects in a densely packed large object with only a single sided access. It consists of an X-ray backscatter camera with a special twisted slit collimator for imaging backscattering objects. The new X-ray backscatter camera is not only imaging the objects based on their densities but also by including the influences of surrounding objects. This unique feature of the X-ray backscatter camera provides new insights in identifying the internal features of the inspected object. Experimental mock-ups were designed imitating containers with threats among a complex packing as they may be encountered in reality. We investigated the dependence of the quality of the X-ray backscatter image on (a) the exposure time, (b) multiple exposures, (c) the distance between object and slit camera, and (d) the width of the slit. At the end, the significant advantages of the presented X-ray backscatter camera in the context of aviation and port security are discussed.
This paper presents a new X-ray backscatter technique (XBT) for non-destructive imaging of aerospace materials with only a single-sided access. It uses a special twisted slit collimator to inspect the whole object by changing the viewing direction of the X-ray backscatter camera. For the first time, the X-ray backscatter measurements were conducted using high-energy (>500 keV) X-ray sources. Experiments were performed on thick complex structured aluminium components, stringers and honeycomb structures to validate the applicability of the present technique to image small changes in the material properties and also to detect low-density material inclusions. In order to reduce the inspection time from hours to several seconds and to improve the image quality of the X-ray backscatter image, the backscattered signals were measured using a digital detector array with high spatial resolution (200 µm). The influence of the energy of the X-ray source and the slit width of the camera on the X-ray backscatter image were also investigated. In the proposed technique, the whole object is irradiated by an un-collimated X-ray beam resulting in a low image acquisition time of 3 min that facilitates the use of XBT for the real time NDT&E of aerospace materials.
In this paper, we present a new dataset consisting of 19,407 X-ray images. The images are organized in a public database called GDXray that can be used free of charge, but for research and educational purposes only. The database includes five groups of X-ray images: castings, welds, baggage, natural objects and settings. Each group has several series, and each series several X-ray images. Most of the series are annotated or labeled. In such cases, the coordinates of the bounding boxes of the objects of interest or the labels of the images are available in standard text files. The size of GDXray is 3.5 GB and it can be downloaded from our website. We believe that GDXray represents a relevant contribution to the X-ray testing community. On the one hand, students, researchers and engineers can use these X-ray images to develop, test and evaluate image analysis and computer vision algorithms without purchasing expensive X-ray equipment. On the other hand, these images can be used as a benchmark in order to test and compare the performance of different approaches on the same data. Moreover, the database can be used in the training programs of human inspectors.
An algorithm has been developed to remove reliably dotted interferences impairing the perceptibility of objects within a radiographic image. This particularly is a major challenge encountered with neutron radiographs collected at the NECTAR facility, Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II): the resulting images are dominated by features resembling a snow flurry. These artefacts are caused by scattered neutrons, gamma radiation, cosmic radiation, etc. all hitting the detector CCD directly in spite of a sophisticated shielding. This makes such images rather useless for further direct evaluations.
One approach to resolve this problem of these random effects would be to collect a vast number of single images, to combine them appropriately and to process them with common image filtering procedures. However, it has been shown that, e.g. median filtering, depending on the kernel size in the plane and/or the number of single shots to be combined, is either insufficient or tends to blur sharp lined structures. This inevitably makes a visually controlled processing image by image unavoidable. Particularly in tomographic studies, it would be by far too tedious to treat each single projection by this way. Alternatively, it would be not only more comfortable but also in many cases the only reasonable approach to filter a stack of images in a batch procedure to get rid of the disturbing interferences.
The algorithm presented here meets all these requirements. It reliably frees the images from the snowy pattern described above without the loss of fine structures and without a general blurring of the image. It consists of an iterative, within a batch procedure parameter free filtering algorithm aiming to eliminate the often complex interfering artefacts while leaving the original information untouched as far as possible.