Wissenschaftliche Artikel der BAM
Reliability of NDT is affected by human factors, which have thus far received the least amount of attention in the reliability assessments. With increased use of automation, in terms of mechanised testing (automation-assisted inspection and the corresponding evaluation of data), higher reliability standards are believed to have been achieved. However, human inspectors, and thus human factors, still play an important role throughout this process and the risks involved in this application are unknown. The aim of this study was to explore for the first time the risks associated with mechanised NDT and find ways of mitigating their effects on the inspection performance. Hence, the objectives were to identify and Analyse potential risks in mechanised NDT and devise measures against them. To address those objectives, a risk assessment in form of a Failure Modes and Effects Analysis (FMEA) was conducted. This analysis revealed potential for failure during both the acquisition and evaluation of NDT data that could be assigned to human, technology, and organisation. Since the existing preventive measures were judged to be insufficient to defend the system from identified failures, new preventive measures were suggested.
Entwicklung eines luftgekoppelten Ultraschall-Echo-Prüfverfahrens mittels fluidischer Anregung
(2019)
In vielen technischen Bereichen werden Ultraschallverfahren zur zer-störungsfreien Werkstoffprüfung eingesetzt. Dabei wird ein Schallpuls von einem Prüfkopf in ein Prüfobjekt eingebracht. Der Puls kann unter anderem durch Membra-nen oder Piezoelemente erzeugt werden und wird in der Regel durch direkten Kontakt oder über ein Koppelmittel an das Objekt übertragen. Luftgekoppelter Ultraschall spielt in kommerziellen Anwendungen bisher eine untergeordnete Rolle, da die Dif-ferenz der akustischen Impedanzen von Luft und Festkörpern immense Verluste beim Übergang des Schallsignals hervorruft.
In diesem Beitrag soll ein neuartiges Anregungsprinzip vorgestellt werden, mit dem ein Großteil dieser Verluste vermieden wird. Anstelle eines Festkörpers soll mit Hilfe einer fluidischen Düse Druckluft zur Signalerzeugung eingesetzt werden. In die-ser Düse wird eine selbsterhaltende Strömungsinstabilität erzeugt, die einen Schall-puls von bis zu 100 kHz hervorruft, sodass der Impedanzverlust in die Umgebungsluft entfällt. Da die charakteristische Frequenz eines fluidisch generierten Pulses maßgeb-lich von der Bauform der Düse und dem anliegenden Druck abhängt, lässt sich mittels einer geeigneten Strömungsregelung ein breiter Frequenzbereich zur Abtastung nut-zen. Die so emittierten Pulse werden auf das Prüfobjekt gerichtet und die reflektierten Signale mit einem Laservibrometer an der Oberfläche des Objekts im Echo-Verfahren abgetastet. Von drei signalmindernden Materialübergängen bei gewöhnlichem luftge-koppeltem Ultraschall bleibt in dem hier vorgeschlagenen Messystem lediglich die Grenzfläche von Luft zu Prüfkörper, sodass eine höhere Signalausbeute als bisher er-wartet werden kann.
The digital photography has almost completely substituted the film photography. The film replacement is also fast progressing in medical X-ray radiography. This process is slower in NDT and especially in Europe. Reasons for the hesitating change to digital radiography (RT-D) in NDT are the necessary time for adoption of standards and the conservative request for film RT by auditors and NDT managers for applications in large plants and at construction areas. The fast serial inspection for small castings is already almost completely dominated by RT-D due to the cost effective short exposure and interpretation times. Standards were developed in parallel at CEN, ISO, ASTM and ASME. Unfortunately, the standard practices are different and the requirements on image quality and useable hardware are different too. The first standard series on Computed Radiography were developed and published by CEN and ASTM in 2005. Harmonized classification and qualification standards are available but the published practices are different. ASTM has developed the first standards for application of Digital Detector Arrays (DDA) in 2010. The first digital RT ISO standard practice is ISO 17636-2 (2013), which describes the practice for application of DDAs and Imaging Plates for weld inspection. At the first time this standard provides requirements for the selection of suitable hardware. Minimum image quality requirements are specified in analogy to film radiography and 3 Compensation Principles are defined to enable the application of a wider range of digital detectors. A comparison of the different international digital RT standards is given and first experiences with ISO 17636-2 are discussed. New standards on RT wall thickness and corrosion measurements (EN 16407, film and digital) have been developed recently.
Machine learning based multi-sensor fusion for the nondestructive testing of corrosion in concrete
(2020)
Half-cell potential mapping (HP) is the most popular non-destructive testing method (NDT) for locating corrosion damage in concrete. It is generally accepted that HP is susceptible to environmental factors caused by salt-related deterioration, such as different moisture and chloride gradients. Additional NDT methods are able to identify distinctive areas but are not yet used to estimate more accurate test results. We present a Supervised Machine Learning (SML) based approach to data fusion of seven different signal features to obtain higher quality information. SMLs are methods that explore (or learn) relationships between different (sensor) data from predefined data labels. To obtain a representative, labelled data set we conducted a comprehensive experiment simulating the deterioration cycle of a chloride exposed device in the laboratory. Our data set consists of 18 measurement campaigns, each containing HP, Ground Penetrating- Radar, Microwave Moisture and Wenner resistivity data. We compare the performance of different ML approaches. Many outperform the best single method, HP. We describe the intrinsic challenges posed by a data-driven approach in NDT and show how future work can help overcome them.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2022)
Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging.
Analyzing the reliability of non-destructive tests using the modular modell - a practical approach
(2016)
Non-destructive testing is an important tool to guarantee the safety of railway traffic.
The infrastructure with tracks, switches and sleepers is regularly tested, the
locomotives and wagons with their wheels, bogies and axles as well. Many years of experience and some events lead in Germany to a good practice in testing the railway components. Now, European authorities are drafting a system of common requirements and standards for the European Railway Market. The German practice combines an intensive training of the NDT-personnel including sufficient time for practical exercises with organizational measures of the companies, responsible for rolling stock and infrastructure. Through the example of UT-testing of railway axles it will be shown, how training and organizational measures influence the reliability of such testing.
The usefulness and purpose of evaluating nondestructive testing (NDT) systems and their capabilities has changed in the last decade. The conventional method of simply applying a familiar statistical algorithm to say whether the system is usable for the tasks is history.
Nowadays, multiple parameter methods which describe the probabilities of detection (POD) of different systems or real defects need new characteristics and a broader variety of statistical models to describe the true system behaviour. The appraisal of the NDT system involves diverse departments within a company (engineering, NDT-operators, and statisticians), but is, at the same time, more needed and requested than in the past. In this article, an approach is discussed in which professionals from different fields worked well together, accomplishing cost-intensive metallographic studies in correlation with well-understood physical behaviour of NDT-methods as well as deep-discussed mathematical methods to create a holistic evaluation of the technical reliability for a specific radiographic testing (RT) equipment. The first part of the publication will show the comparison between metallographic grinding and the RT indications. An essential innovation over past evaluation methods was the use of a multi-scale smoothing algorithm, which describes physical parameters, which were not used in evaluation like the POD in this way in the past.
In the second part the statistical requirements for the POD take the focus. It can often be hard to make significant statements; especially in the case where only a small amount of data is available. The combination of data and the use of knowledge from simulations are essential. One possible solution will be shown for the RT evaluation. The methodology is used for evaluating the digital RT system for the inspection of electron-beam welds, which was method considered to seal the Finnish copper canisters for the final deposit of spent nuclear fuel.
In a joint project of partners from industry and research, the automated recycling of construction and demolition waste (CDW) is investigated and tested by combing laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.). The project focuses primarily on the Berlin site to analyze the entire value chain, minimize economic/technological barriers and obstacles at the cluster level, and sustainably increase recovery and recycling rates. First measurements with LIBS and NIR spectroscopy show promising results in distinguishing various material types and indicate the potential for a successful combination. In addition, X-ray fluorescence (XRF) spectroscopy is being performed to obtain more information about the quantitative elemental composition of the different building materials. Future work will apply the developed sorting methodology in a fully automated measurement setup with CDW on a conveyor belt.
LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste
(2023)
AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt.
In this contribution, we present a dual high-energy X-ray imaging technique for cargo container inspection using the 'spectral high-energy X-ray attenuation method'. This method is based on attenuation of continuous highenergy spectra. The developed experimental technique consists of a betatron as high-energy (up to 7.5 MeV) X-ray source and a matrix detector with high spatial resolution (400 ìm) for digital X-ray imaging. In order to evaluate the material discrimination capability using dual high-energy X-ray imaging, a test specimen is proposed, comprising step wedges of different low and high atomic number (Z) materials. The selected X-ray spectra for the dual-energy experiments correspond to 3 MV and 7.5 MV acceleration potential of the betatron. We evaluated the ratio between low- and high-energy X-ray attenuation coefficients quantitatively based on simulated poly-energetic high-energy X-ray source spectra and the detector sensitivity using the 'analytical Radiographic Testing inspection simulation tool' (aRTist) developed at BAM. The simulated effective attenuation coefficients are compared with corresponding experimental results in order to establish a method for identification of low- and high-Z materials in the container. Finally, important applications of the proposed technique in the context of aviation security are discussed.