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Eingeladener Vortrag
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Stochastic artefacts are frequently encountered in digital radiography and tomography with neutrons. Most obviously, they are caused by ubiquitous scattered radiation hitting the CCD-sensor. They appear as scattered dots and, at higher frequency of occurrence, they may obscure the image. Some of these dotted interferences vary with time, however, a large portion of them remains persistent so the problem cannot be resolved by collecting stacks of images and to merge them to a median image. The situation becomes even worse in computed tomography (CT) where each artefact causes a circular pattern in the reconstructed plane. Therefore, these stochastic artefacts have to be removed completely and automatically while leaving the original image content untouched. A simplified image acquisition and artefact removal tool was developed at BAM and is available to interested users. Furthermore, an algorithm complying with all the requirements mentioned above was developed that reliably removes artefacts that could even exceed the size of a single pixel without affecting other parts of the image. It consists of an iterative two-step algorithm adjusting pixel values within a 3 × 3 matrix inside of a 5 × 5 kernel and the centre pixel only within a 3 × 3 kernel, resp. It has been applied to thousands of images obtained from the NECTAR facility at the FRM II in Garching, Germany, without any need of a visual control. In essence, the procedure consists of identifying and tackling asymmetric intensity distributions locally with recording each treatment of a pixel. Searching for the local asymmetry with subsequent correction rather than replacing individually identified pixels constitutes the basic idea of the algorithm. The efficiency of the proposed algorithm is demonstrated with a severely spoiled example of neutron radiography and tomography as compared with median filtering, the most convenient alternative approach by visual check, histogram and power spectra analysis.
Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability assessment of film and digital radiography. NDT of safety relevant components of aerospace industry requires the proof of probability of detection (POD) of the inspection. Modeling tools can reduce the expense of such extended, time consuming NDT trials, if the result of simulation fits to the experiment. Our analytic simulation tool consists of three modules for the description of the radiation source, the interaction of radiation with test pieces and flaws, and the detection process with special focus on film and digital industrial radiography. It features high processing speed with near–interactive frame rates and a high level of realism. A concept has been developed as well as a software extension for reliability investigations, completed by a user interface for planning automatic simulations with varying parameters and defects. Furthermore, an automatic image analysis procedure is included to evaluate the defect visibility. The radiographic modeling from 3D CAD of aero engine components and quality test samples are compared as a precondition for real trials. This enables the evaluation and optimization of film replacement for application of modern digital equipment for economical NDT and defined POD.
Concepts for digital image evaluation are presented for Computed Radiography (CR) and Digital Detector Arrays (DDAs) used for weld inspection. The precise DDA calibration yields an extra ordinary increase of contrast sensitivity up to 10 times in relation to film radiography. Restrictions in spatial resolution caused by pixel size of the DDA are compensated by increased contrast sensitivity. First CR standards were published in 2005 to support the application of phosphor imaging plates in lieu of X-ray film, but they need already a revision based on experiences reported by many users. One of the key concepts is the usage of signal-to-noise (SNR) measurements as equivalent to the optical density of film and film system class. The contrast sensitivity, measured by IQI visibility, depends on three essential parameters: The basic spatial resolution (SRb) of the radiographic image, the achieved signal-to-noise ratio (SNR) and the specific contrast (µeff - effective attenuation coefficient). Knowing these 3 parameters for the given exposure condition, inspected material and monitor viewing condition permits the calculation of the just visible IQI element. Furthermore, this enables the optimization of exposure conditions. The new ISO/FDIS 17636-2 describes the practice for digital radiography with CR and DDAs. It considers the first time compensation principles, derived from the three essential parameters. The consequences are described.
Best energy selection for different applications with digital detector arrays from 20 to 600 keV
(2012)
Mobile Tomographic Computer Aided Radiometry (TomoCAR) is based on the mechanical position control of an X-ray tube in front of an object and the application of a Digital Detector Array (DDA) behind it. Several hundred radiometric projections in small angle steps are acquired during the controlled movement of the X-ray tube along a preselected way. The tomographic or laminographic reconstruction allows the three-dimensional (3D) representation of flaws. A specially designed radiometric detector array with small internal unsharpness and high image contrast was used for visualization and sizing of planar and volumetric defects in austenitic welds in nuclear power plants. A German pilot study was successfully performed on the basis of the European network of inspection and qualification (ENIQ) guidelines. This was the precondition for several applications of TomoCAR in nuclear power stations in Germany and Switzerland.
A versatile computed tomography (CT) system was developed on basis of the TomoCAR design for in situ inspection of large aircraft components under production conditions. A gate based planar computed tomograph was constructed and tested for inspection of the integrity of CFRP stringers, embedded in aircraft fibre composite shells. A probability of crack visibility >90% could be determined.
New methodologies for evaluating the reliability of NDE systems are discussed in accordance with the specific
requirements of industrial application. After a review of the substantive issues from the previous decades, the go
forward guidance is concluded.
For high safety demands a quantitative probability of detection (POD) created from hit miss
experiments or signal response analysis and ROC (Receiver Operating Characteristics) are typically created. The
modular model distinguishes between the influence of pure physics and technique, industrial application factors
and the human factor and helps to learn what factors are covered by modelling, open or blind trials. A new
paradigm is offered to consider the POD or reliability of the system as a function of the configuration of input
variables and use it for optimisation rather than for a final judgement. New approaches are considered dealing
with real defects in a realistic environment, affordable but precisely like the Bayesian approach or model assisted
methods.
Among the influencing parameters, the human factor is of high importance. A systematic psychological
approach helps to find out where the bottlenecks are and shows possibilities for improvement.
When pushed to the limits of their detection capability, NDE systems do not produce consistent hit/miss
indications. Their capability of detecting small defects is therefore expressed in terms of POD. An adequate
NDE system is required to ensure the structural integrity. In conventional signal response analysis, the POD is
expressed as a function of the defect size, and its adequacy for the inspection task is tested against the maximum
allowable defect size which will not undermine the structural integrity. Analyses of modern structures show that
other parameters, beside the defect size, can both significantly influence the POD and determine the severity of
the defect for the structure. Within the multi-parameter reliability analysis, the POD is expressed as a function of
those influencing parameters. When determining the adequacy of the NDE system, the capability of detecting a
defect has to be expressed and tested against the critical value of exactly that parameter that determines defects
severity for the structure. Failing to do so can lead to a rejection of the healthy, or acceptance of the bad part.
The principle is demonstrated on the example of the Transmit-Receive Longitudinal (TRL) ultrasonic inspection
of the iron cast component for semi-elliptical surface defects.
The Probability of Detection (POD) is used to evaluate the detectability of non-destructive testing (NDT) systems. The POD is highly dependent on the amount of available data. The Bayesian approach provides a solution to compute POD-curves in case of a small amount of real defects without losing the necessary information. The result contains the needed information for the computation of POD-curves for real defects with an acceptable amount of information, even for sparse amount of data. In this paper is shown limitations of the Bayesian approach and how it can be applied to NDT. The Bayesian approach is applied in this case to the evaluation of radiographic testing. Bayesian approach is applied to determine POD-curves for the inspection techniques of nuclear fuel disposal canisters. The reason for using Bayesian approach is the high safety demands and also the low amount of real defects due to the high quality of the reliable production techniques.