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- 8.1 Sensorik, mess- und prüftechnische Verfahren (1)
Damit eine Simulationsrechnung, beispielsweise mit einer FEM-Software, eine ausreichend hohe Genauigkeit erreicht, muss vorausgesetzt werden, dass die Modellparameter eine sehr hohe Güte aufweisen. Die genaue Kenntnis der Materialparameter ist dabei von besonderer Bedeutung. Um diese Parameter bestimmen zu können, müssen die verwendeten Werkstoffe messtechnisch charakterisiert werden. Neben anderen Ansätzen sind dafür akustische Verfahren im Ultraschallbereich geeignet. Für dünnwandige und plattenförmige Materialien können aus den sich ausbreitenden geführten Wellen messtechnisch Dispersionskurven bestimmt und aus diesen die Materialparameter abgeleitet werden.
Da für die Signalverarbeitung und für Optimierungsaufgaben aktuell zunehmend Machine Learning Tools zum Einsatz kommen, stellt sich die Frage, ob diese Werkzeuge auch für die Ermittlung der Materialparameter aus den gemessenen Dispersionskurven eingesetzt werden können.
In der vorgestellten Untersuchung soll ein Convolutional Neural Network aufgestellt werden, welches aus Dispersionsbildern Muster extrahiert und aus diesen eine Schätzung für die Materialparameter ermittelt. Um die Machbarkeit dieses Ansatzes zu prüfen, werden zunächst nur isotrope Materialien betrachtet. Für das Netz werden mit der Scaled-Boundary-Finite-Element-Methode synthetische Daten für das Trainieren und Validieren generiert. Zusätzlich werden die Hyperparameter des neuronalen Netzes variiert, um ein optimales Model für die Schätzung zu finden. Anschließend kann das Netz mit experimentellen Daten getestet und das Ergebnis hinsichtlich der Genauigkeit bewertet werden.
In this work we experimentally verify the theoretical prediction of the recently published Energy Density Fluctuation Model (EDF-model) of thermo-acoustic sound generation. Particularly, we investigate experimentally the influence of thermal inertia of an electrically conductive film on the efficiency of thermal airborne ultrasound generation predicted by the EDF-model. Unlike widely used theories, the EDF-model predicts that the thermal inertia of the electrically conductive film is a frequency-dependent parameter. Its influence grows non-linearly with the increase of excitation frequency and reduces the efficiency of the ultrasound generation. Thus, this parameter is the major limiting factor for the efficient thermal airborne ultrasound generation in the MHz-range. To verify this theoretical prediction experimentally, five thermo-acoustic emitter samples consisting of Indium-Tin-Oxide (ITO) coatings of different thicknesses (from 65 nm to 1.44 lm) on quartz glass substrates were tested for airborne ultrasound generation in a frequency range from 10 kHz to 800 kHz. For the measurement of thermally generated sound pressures a laser Doppler vibrometer combined with a 12 lm thin polyethylene foil was used as the sound pressure detector. All tested thermo-acoustic emitter samples showed a resonance-free frequency response in the entire tested frequency range. The thermal inertia of the heat producing film acts as a low-pass filter and reduces the generated sound pressure with the increasing excitation frequency and the ITO film thickness. The difference of generated sound pressure levels for samples with 65 nm and 1.44 lm thickness is in the order of about 6 dB at 50 kHz and of about 12 dB at 500 kHz. A comparison of sound pressure levels measured experimentally and those predicted by the EDF-model shows for all tested emitter samples a relative error of less than ±6%. Thus, experimental results confirm the prediction of the EDF-model and show that the model can be applied for design and optimization of thermo-acoustic airborne ultrasound emitters.
Structural health monitoring (SHM) is a term that groups together techniques adopted to evaluate in a continued fashion the structural integrity and degradation of technical appliances. SHM is particularly attractive for components that are difficult to access or expensive to take off-line. Among many other techniques, SHM can be performed using ultrasonic guided waves (UGW) which have an advantage of traveling over Long distances. Various guided wave modes exist along with many methods for their generation and sensing, e.g by means of interdigital transducers (IDT). This contribution is dedicated to the design and characterization of a flexible piezopolymerbased IDT which allows for the selective excitation of UGW, resulting in more straightforward data analysis. The designed IDT was characterized using a 3D Laser Doppler Vibrometer (3D LDV) in the air to identify and analyze the IDT’s Vibration modes. Then the transducer was mounted on an aluminum plate, and the generated wavefield was measured with the 3D LDV.
According to this investigation, we demonstrate that it is possible to selectively excite desired guided wave mode, namely the A0 mode, suppressing the excitation of the S0 mode. Moreover, the measured wavefield allows for analysis of the directivity of the designed IDT. All in all the results show good correlation between theoretical predictions and measured values, thus allowing to use the current design in terms of selective excitation as it is.
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.
The dispersive properties of Lamb waves can be utilised for material characterisation because the frequency-wavenumber-relationship, as well as the group velocity, depend on material parameters. These dependencies make a non-destructive estimation of an elastic constant possible. This preliminary study investigates the sensitivity of dispersion curves caused by a change in elastic constants. The Scaled Boundary Finite Element Method is used to compute special dispersion curves, which show the sensitivity value of the frequency and group velocity as a colour value. This representation allows for easy identification of patterns and local effects. Two sets of dispersion curves are presented, one set for a steel plate and the other set for a plate made of a carbon fibre reinforced polymer. In general, we notice that the sensitivity often increases with the frequency and that higher-order modes seem to be more suitable for material characterisation. Moreover, specific modes respond to material changes while others are relatively unaffected, which must be taken into consideration for material characterisation.
Detailliertes Wissen über die mechanischen Eigenschaften verwendeter Materialien ist Grundvoraussetzung für viele ingenieurtechnische Aufgaben und Dienstleistungen. Zur Bestimmung der elastischen Materialparameter gibt es verschiedene klassische, zerstörende Prüfverfahren. Eine Möglichkeit der zerstörungsfreien Bestimmung liegt in der Auswertung von Messergebnissen, die auf Basis des Ausbreitungsverhaltens geführter Ultraschallwellen gewonnen wurden. Das Ausbreitungsverhalten geführter Ultraschallwellen kann mittels Dispersionsabbildungen dargestellt werden.
Um aus messtechnisch ermittelten Dispersionsabbildungen Rückschlüsse auf die Materialparameter zu ziehen, werden in der aktuellen Forschung verschiedene inverse Methoden diskutiert. Maschinelles Lernen und insbesondere Convolutional Neural Networks (CNNs) stellen eine Möglichkeit der automatisierten inversen Modellierung und Evaluierung von Bilddaten dar.
In diesem Beitrag wird gezeigt, wie das Ausbreitungsverhalten von geführten Ultraschallwellen unter Verwendung von CNNs genutzt werden kann, um die isotropen elastischen Konstanten einer plattenförmigen Struktur zu bestimmen. Hierfür werden die verwendeten Daten analysiert, das Preprocessing erläutert und eine grundlegende CNN-Architektur gewählt. Zur Auswertung des generierten Modells werden verschiedene Verfahren wie Gradienten-Mapping und die Visualisierung der verschiedenen Schichten vorgestellt. Die Anwendbarkeit der Methode wird anhand synthetischer Daten demonstriert.
In the field of non-destructive testing, Lamb waves are often used for material characterisation. The increasing computational capabilities further enable complex and detailed simulations to predict the material behaviour in reality. Since adhesive bonding of different materials is a widely used method in modern applications, a reliable measurement system to determine the quality of these adhesive bonds is needed. Investigations of the dispersive behaviour of acoustic waves in adhesively bonded multi-layered waveguides show mode repulsions in the dispersion diagrams in regions where the modes of the single materials would otherwise intersect. In previous works, changes of the distance between those modes with respect to the bonding quality are observed. The experimental data for this investigation is generated using pulsed laser radiation to excite broadband acoustic waves in plate like specimens which are detected by a piezoelectric ultrasonic transducer. Numerical data is generated using simulations via a semi-analytical finite element method. Using a combination of experimental and numerical data, the present work introduces an approach to determine a parameter which indicates the bonding quality in relation
to an ideal material coupling.
Composite-overwrapped pressure vessels (COPV) are increasingly used in the transportation industry due to their high strength to mass ratio. Throughout the years, various designs were developed and found their applications. Currently, there are five designs, which can be subdivided into two main categories - with a load-sharing metal liner and with a non-load-sharing plastic liner. The main damage mechanism defining the lifetime of the first type is fatigue of the metal liner, whereas for the second type it is fatigue of the composite overwrap. Nevertheless, one damage type which may drastically reduce the lifetime of COPV is impact-induced damage. Therefore, this barely visible damage needs to be assessed in a non-destructive way to decide whether the pressure vessel can be further used or has to be put out of service. One of the possible methods is based on ultrasonic waves. In this contribution, both conventional ultrasonic testing (UT) by high-frequency bulk waves and wavenumber mapping by low frequency guided waves are used to evaluate impact damage. Wavenumber mapping techniques are first benchmarked on a simulated aluminium panel then applied to experimental measurements acquired on a delaminated aluminium-CFRP composite plate which corresponds to a structure of COPV with a load-sharing metal liner. The analysis of experimental data obtained from measurements of guided waves propagating in an aluminium-CFRP composite plate with impact-induced damage is performed. All approaches show similar performance in terms of quantification of damage size and depths while being applied to numerical data. The approaches used on the experimental data deliver an accurate estimate of the in-plane size of the large delamination at the aluminium-CFRP interface but only a rough estimate of its depth. Moreover, none of the wavenumber mapping techniques used in the study can quantify every delamination between CFRP plies caused by the impact, which is the case for conventional UT. This may be solved by using higher frequencies (shorter wavelengths) or more advanced signal processing techniques. All in all, it can be concluded that imaging of complex impact damage in fibre-reinforced composites based on wavenumber mapping is not straightforward and stays a challenging task.
In the context of Industry 4.0 and especially in the field of Structural Health Monitoring, Condition Monitoring and Digital Twins, simulations are becoming more and more important. The exact determination of material parameters is required for realistic results of numerical simulations of the static and dynamic behavior of technical structures. There are many possibilities to determine
elastic material parameters. One possibility of non-destructive testing are ultrasonic guided waves. For the evaluation of the measurement results, mostly inverse methods are applied in order to be able to draw conclusions about the elastic material parameters from analysing the ultrasonic guided wave propagation. For the inverse determination of the elastic material Parameters with ultrasonic guided waves, several investigations were carried out, e.g. the determination of the isotropic material parameters through the point of zero-groupvelocity or anisotropic material parameters with a simplex algorithm. These investigations are based on the evaluation of dispersion images. Machine learning and in particular Convolutional Neural Networks (CNN) are one possibility of the automated evaluation from Image data, e.g. classification or object recognition problems. This article shows how the dispersive behavior of ultrasonic guided waves and CNNs can be used to determine the isotropic elastic constants of plate-like structures.
Lamb waves are a common tool in the field of non-destructive testing and are widely used for materialcharacterisation. Further, the increasing computational capability of modern systems enables the Simulation of complex and detailed material models. This work demonstrates the possibility of simulating an adhesive-bonded multilayer system by characterising each layer individually, and introduces an Approach for determining the dispersive behaviour of acoustic waves in a multilayer system via real measurements.