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In flash thermography, the temperature transient is strongly influenced by the temporal shape of the heating pulse for samples with high thermal diffusivity or very thin samples. Here, we present a closed phenomenological approximation of the temporal shape of pulses of Xe-flash lamps. It is a non-stitched solution, has a simple Laplace transform and is suitable for different lamps and energy settings. It is demonstrated that simulated temperature transients, based on this approximation, are well consistent with experimental data.
That human factors (HF) affect the reliability of NDT is not novelty. Still, when it comes to reliability assessments, the role of people is often neglected. Reliability is typically expressed in terms of POD curves, and the effects of human and organisational factors on the inspection are typically tackled by the regulations, procedures and by the qualification and training of the inspection personnel. However, studies have shown that even the most experienced personnel can make mistakes and that the reliability in the field is never as high as the reliability measured in the POD experiments. Generally, HF are considered too unpredictable and too uncontrollable to model. If that is the fact, then what can we do? The engineering perspective to this problem has often been to find ways to automate inspections and, recently, to make use of artificial intelligence tools to decrease the direct effect of people on the inspection results and improve the overall efficiency and reliability. However, despite automation and AI, people remain the key players, though their tasks change. The contemporary approach to HF is not to engineer them out of the system but to design human-machine systems that make the best use of both. In this talk, ways of tackling HF in the design of systems and processes will be presented.
It is known that human factors (HF) affect the reliability of non-destructive testing (NDT). However, reliability is often expressed in probability of detection (POD) curves, obtained in practical trials, where human and organisational factors are considered only indirectly, through the few people taking part in the trials. Recently, we have observed an increase in the use of numerical modelling to obtain POD curves outside of practical trials. The so-called model-assisted POD(MAPOD) approaches have so far only very rarely included some kind of variation to account for HF. This talk presents different possibilities to include HF in MAPOD and discusses the advantages and disadvantages of each approach.
Non-destructive testing (NDT) is a major contributor to the safe railway operation. Even though NDT reliability in railway maintenance is affected by human factors, there are only just a few studies published in this field so far. Education and training of the NDT personnel are some of the most important drivers of safe and reliable NDT. Continuously improving current practices and tools used for educational purposes can be achieved not only through technical content, but also through the attention to human factors. The aim of this study was to deepen the understanding of possible human-related risks in the manual ultrasonic inspection of the hollow railway axles and to suggest measures to improve the education and training of the NDT personnel. This was achieved by means of Failure Modes and Effects Analysis (FMEA) carried out with eight NDT experts and by a survey of 27 experienced inspectors. The results show that failures can happen throughout the entire NDT process. Prevention of those failures could be improved through the optimization of the organization, technology, documentation and regulations, working conditions and the general process, and through the optimization of the formal education and training. Specialized training of the executives, extended training of the supervisors and the inspectors and improvement of the inspection documentation have been suggested. The study also showed potential for the improvements of the inspection in the field.
Eine zentrale Aufgabe der zerstörungsfreien Prüfung und der Strukturüberwachung (engl. Structural Health Monitoring - SHM) mit Ultraschallwellen ist die Bewertung von Schäden in Bauteilen. In vielen Bauteilen, wie zum Beispiel platten- und schalenförmigen Strukturen, Rohrleitungen oder Laminaten, breitet sich der Ultraschall in Form geführter Wellen aus. Zwar haben geführte Wellen eine relativ große Reichweite innerhalb des Bauteils und ermöglichen so eine großflächige Prüfung, ihre multimodalen und dispersiven Eigenschaften erschweren jedoch die Analyse der vom Schaden kommenden Reflexionen. Eine Möglichkeit, die Messsignale zu interpretieren und die Schäden zu charakterisieren, ist deren Vergleich mit der Wellenausbreitung in einem digitalen Modell. Hierbei stellt sich die Aufgabe, den Schaden im digitalen Modell anhand der Messdaten zu rekonstruieren. Diese Rekonstruktion beschreibt ein inverses Problem, das mehrere Vorwärtsrechnungen braucht, um das Schadensmodell an die Messdaten anzupassen.Durch die kleine Wellenlänge von Ultraschallwellen sind klassische Vorwärtsmethoden wie die Finte Elemente Methode rechenintensiv, weshalb die Autoren die semi-analytische Scaled Boundary Finite Element Method (SBFEM) benutzen, um den Rechenaufwand zu verringern. Im Beitrag wird ein inverses Verfahren basierend auf dem Automatischen Differenzieren in Kombination mit der SBFEM vorgestellt und an verschiedenen Schadenstypen in 2D-Querschnittmodellen von Wellenleitern getestet. In der präsentierten Vorstudie werden dafür „Messdaten“ aus unabhängigen Simulationen verwendet.
Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature increase is measured at the samples surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm.
Entwicklung eines luftgekoppelten Ultraschall-Echo-Prüfverfahrens mittels fluidischer Anregung
(2020)
In vielen technischen Bereichen werden Ultraschallverfahren zur zerstörungsfreien Werkstoffprüfung (ZfP) eingesetzt um auf Basis der Signalstärke und der Laufzeit Einbauteile und Beschädigungen zu orten. Luftgekoppelter Ultraschall spielt bisher in kommerziellen Anwendungen vor Allem im Bauwesen eine untergeordnete Rolle, da die Differenz der akustischen Impedanzen von Luft und Festkörpern immense Verluste beim Übergang des Schallsignals hervorruft.
Im Rahmen des Promotionsvorhabens soll die Eignung eines neuartigen Anregungsprinzip untersucht werden, mit dem ein Großteil dieser Verluste vermieden werden soll. Anstelle eines Festkörpers soll mit Hilfe einer fluidischen Düse Druckluft zur Signalerzeugung eingesetzt werden. Die Impedanzverluste zwischen Aktuatormembran und Umgebungsluft entfallen daher.
Die gezielte Schallerzeugung durch einen pulsierenden Freistrahl ist weitgehend unerforscht. Es ist daher notwendig, den so erzeugten Schallpuls in der Interaktion mit dem transienten Strömungsfeld zu untersuchen. Das kompressible Medium Luft und die geringen räumlichen Dimensionen einer hochfrequenten Pulsdüse werfen darüber hinaus einige Herausforderungen hinsichtlich der eingesetzten Messtechnik auf. Hier sollen geeignete Verfahren weiterentwickelt und validiert werden, um die Eignung des fluidisch erzeugten Pulses zu überprüfen.
In diesem Vortrag werden erste Messungen an einem fluidischen Schalter mit denen an einem kommerziellen Luftultraschallprüfkopf verglichen.
Composite pressure vessels for transporting dangerous goods and for hydrogen and natural gas vehicles consist of a load-bearing composite and a gas-tight, metallic or polymeric barrier layer (liner). To investigate the aging behavior of such composite pressure vessels, BAM carried out the interdisciplinary project COD-AGE. The aim of the project was the development of methods and models for the description and determination of the aging behavior of carbon fiber composites using the example of pressure vessels in order to better predict aging and safe working life. One focus of this project was the provision of suitable NDT methods. These included both test-related tests and the possible development of test equipment for later practical use.
In the lecture, test results of the age-related eddy current test on composite pressure vessels are presented.
In aging tests, pressure vessels made of an approximately 4 mm thick aluminum liner and approx. 8 mm thick CFRP layer were examined. Typical application of such pressure vessels are respiratory protective devices of the fire department. The pressure vessels were tested using conventional eddy current technology from the outer and inner side as well as with high-frequency eddy current technology. Both damage to the metallic liner and structures of the CFRP could be detected. A particular mechanical challenge was the inspection of the inside of the liners, since a cylindrical surface with an inside diameter of 150 mm has to be tested with an access of only 15 mm diameter.
Ultrasonic coda wave interferometry can detect small changes in scattering materials like concrete. We embedded ultrasonic transducers in the Gänstorbrücke Ulm, a monitored road bridge in Germany, to test the methodology. Since fall 2020, we've been monitoring parts of the bridge and comparing the results to commercial monitoring systems. We calculate signal and volumetric velocity changes using coda waves, and long-term measurements show that the influence of temperature on strains and ultrasound velocity changes can be monitored. Velocity change maps indicate that different parts of the bridge react differently to environmental temperature changes, revealing local material property differences. A load experiment with trucks allows calibration to improve detectability of possibly damaging events. Our work focuses on measurement reliability, potential use of and distinction from temperature effects, combination with complementary sensing systems, and converting measured values to information for damage and life cycle assessment.
Non-destructive testing of rail tracks is carried out by using rail inspection cars equipped with ultrasonic and eddy current measurement. The evaluation of test data is mainly done manually, supported by a software tool which pre-selects relevant indications shown to the evaluators. The resulting indications have to be checked on-site using hand-held testing equipment. Maintenance interventions are then derived on the basis of these on-site findings.
Overall aim of the AIFRI (Artificial Intelligence For Rail Inspection) project - funded by the German Federal Ministry of Digital and Transport (BMDV) as part of the mFUND programme under funding code 19FS2014 – is to increase the degree of automation of the inspection process from the evaluation of the data to the planning of maintenance interventions. The accuracy of defect detection shall be increased by applying AI methods in order to enable an automated classification of detected indications into risk classes. For this purpose, data from both eddy current inspections and ultrasonic inspections will be used in combination.
Within the framework of this data-driven project, relevant defect patterns and artefacts present in the rail are analysed and implemented into a configurable digital twin. With the help of this digital twin virtual defects can be generated and used to train AI algorithms for detection and classification. With the help of reliability assessment trained AI algorithms will be evaluated with regard to the resulting quality in defect detection and characterisation.
A particular aspect of the development of AI methods is the data fusion of different NDT data sources: Thereby, synergies are used that arise from linking eddy current and ultrasonic inspection data in a combined model.
In the course of the project a demonstrator consisting of the developed IT-tool and an asset management system will be implemented and tested in the field using real-world data.