TY - CONF A1 - Lauschkin, Maik A1 - Bulling, Jannis A1 - Lugovtsova, Yevgeniya A1 - Wasmer, P. A1 - Prager, Jens T1 - Bestimmung von Materialparametern aus dem dispersiven Verhalten geführter Wellen mittels neuronaler Netze N2 - 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. T2 - DAGA 2020 - 46. Jahrestagung für Akustik CY - Meeting was canceled DA - 16.03.2020 KW - Machinelles Lernen KW - Geführte Ultraschallwellen KW - Materialcharakterisierung KW - Elastische Konstanten KW - Isotrope Materialien PY - 2020 SN - 978-3-939296-17-1 SP - 571 EP - 574 PB - Deutsche Gesellschaft für Akustik e.V. CY - Berlin AN - OPUS4-50765 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - Characterization of a Flexible Piezopolymer-based Interdigital Transducer for Selective Excitation of Ultrasonic Guided Waves N2 - 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. T2 - IEEE International Ultrasonics Symposium CY - Online meeting DA - 06.09.2020 KW - Lamb waves KW - Non-Destructive Testing KW - Structural Health Monitoring KW - Polyvinylidene Fluoride (PVDF) PY - 2020 AN - OPUS4-51202 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya A1 - Bulletti, A. A1 - Giannelli, P. A1 - Capineri, L. A1 - Prager, Jens T1 - Characterization of a Flexible Piezopolymer-based Interdigital Transducer for Selective Excitation of Ultrasonic Guided Waves N2 - 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. T2 - I2020 IEEE International Ultrasonics Symposium (IUS) CY - Online meeting DA - 07.09.2020 KW - Lamb waves KW - Non-Destructive Testing KW - Structural Health Monitoring KW - Polyvinylidene Fluoride (PVDF) PY - 2020 SN - 978-1-7281-5448-0 SP - 1261, 45 AN - OPUS4-51441 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bulling, Jannis A1 - Franosch, Georg A1 - Lugovtsova, Yevgeniya A1 - Prager, Jens ED - Rizzo, P. ED - Milazzo, A. T1 - Sensitivity of Ultrasonic Guided Waves to Elastic Constants: A Numerical Study N2 - 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. T2 - European Workshop on Structural Health Monitoring (EWSHM 2020) CY - Online meeting DA - 06.07.2020 KW - Scaled Boundary Finite Element Method KW - Lamb waves KW - Dispersion curves KW - Carbon fibre reinforced polymer KW - Transverse isotropy PY - 2021 SN - 978-3-030-64593-9 DO - https://doi.org/10.1007/978-3-030-64594-6_73 VL - 127 SP - 759 EP - 768 PB - Springer CY - Cham AN - OPUS4-51986 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Held, Mathias A1 - Rashwan, Abdalla A1 - Bulling, Jannis A1 - Lugovtsova, Yevgeniya A1 - Lauschkin, Maik A1 - Prager, Jens T1 - Inverse Bestimmung elastischer Materialparameter aus dem Ausbreitungsverhalten geführter Ultraschallwellen mittels eines Convolutional Neuronal Networks N2 - 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. T2 - DAGA 2021 CY - Vienna, Austria DA - 15.08.2021 KW - Geführte Ultraschallwellen KW - Inverse Probleme KW - Materialcharakterisierung KW - Maschinelles Lernen KW - Dispersion KW - Lamb Wellen PY - 2021 SN - 978-3-939296-18-8 VL - 47 SP - 659 EP - 662 AN - OPUS4-53492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zeipert, H. A1 - Johannesmann, S. A1 - Nicolai, Marcel A1 - Lugovtsova, Yevgeniya A1 - Prager, Jens A1 - Henning, B. T1 - Quantifying the coupling strength of adhesively bonded materials by investigating mode repulsion regions N2 - 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. T2 - DAGA 2021 CY - Vienna, Austria DA - 15.08.2021 KW - Ultrasonic guided waves KW - Multi-layered structures KW - Laser excited ultrasonic waves PY - 2021 SP - 1532 EP - 1535 AN - OPUS4-53581 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Mesnil, O. A1 - Prager, Jens A1 - Gohlke, Dirk A1 - Boller, C. T1 - Damage quantification in an aluminium-CFRP composite structure using guided wave wavenumber mapping: Comparison of instantaneous and local wavenumber analyses N2 - 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. KW - Ultrasonic guided waves KW - Instantaneous wavenumber analysis KW - Local wavenumber analysis KW - Signal processing PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-528203 DO - https://doi.org/10.1016/j.ndteint.2021.102472 SN - 0963-8695 VL - 122 SP - 2472 PB - Elsevier Ltd. CY - Amsterdam, Netherlands AN - OPUS4-52820 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Tschöke, K. A1 - Müller, I. A1 - Memmolo, V. A1 - Moix-Bonet, M. A1 - Moll, J. A1 - Lugovtsova, Yevgeniya A1 - Golub, M. A1 - Sridaran Venkat, R. A1 - Schubert, L. T1 - Feasibility of Model-Assisted Probability of Detection Principles for Structural Health Monitoring Systems based on Guided Waves for Fibre-Reinforced Composites N2 - In many industrial sectors, Structural Health Monitoring (SHM) is considered as an addition to Non-Destructive Testing (NDT) that can reduce maintenance effort during lifetime of a technical facility, structural component or vehicle. A large number of SHM methods is based on ultrasonic waves, whose properties change depending on structural health. However, the wide application of SHM systems is limited due to the lack of suitable methods to assess their reliability. The evaluation of the system performance usually refers to the determination of the Probability of Detection (POD) of a test procedure. Up to now, only few limited methods exist to evaluate the POD of SHM systems, which prevent them from being standardised and widely accepted in industry. The biggest hurdle concerning the POD calculation is the large amount of samples needed. A POD analysis requires data from numerous identical structures with integrated SHM systems. Each structure is then damaged at different locations and with various degrees of severity. All of this is connected to high costs. Therefore, one possible way to tackle this problem is to perform computer-aided investigations. In this work, the POD assessment procedure established in NDT according to the Berens model is adapted to guided wave-based SHM systems. The approach implemented here is based on solely computer-aided investigations. After efficient modelling of wave propagation phenomena across an automotive component made of a carbon fibre-reinforced composite, the POD curves are extracted. Finally, the novel concept of a POD map is introduced to look into the effect of damage position on system reliability. KW - Reliability KW - Acoustics KW - Monitoring KW - Automotive engineering KW - Elastodynamic Finite Inegration Technique PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-528218 DO - https://doi.org/10.1109/TUFFC.2021.3084898 VL - 68 IS - 10 SP - 3156 EP - 3173 AN - OPUS4-52821 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Held, Mathias A1 - Rashwan, Abdalla A1 - Lauschkin, Maik A1 - Bulling, Jannis A1 - Lugovtsova, Yevgeniya A1 - Prager, Jens T1 - Inverse determination of elastic material parameters from ultrasonic guided waves dispersion measurements using Convolutional Neuronal Networks N2 - 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. T2 - SMSI 2021 2021-05-03 - 2021-05-06 digital CY - Online meeting DA - 03.05.2021 KW - Convolutional Neuronal Networks KW - Inverse Probleme KW - Materialcharakterisierung KW - guided waves KW - Dispersion PY - 2021 SN - 978-3-9819376-4-0 DO - https://doi.org/10.5162/SMSI2021/A10.2 VL - 2021 SP - 239 EP - 240 AN - OPUS4-52618 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zeipert, H. A1 - Claes, L. A1 - Johannesmann, S. A1 - Webersen, M. A1 - Lugovtsova, Yevgeniya A1 - Prager, Jens A1 - Henning, B. T1 - Measurement and simulation of Lamb waves in adhesive-bonded multilayer systems N2 - 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. T2 - SMSI 2021 Conference – Sensor and Measurement Science International CY - Online meeting DA - 03.05.2021 KW - Adhesive bonds KW - Lamb waves KW - Elastic constants KW - Non-Destructive Testing KW - Ultrasound PY - 2021 DO - https://doi.org/10.5162/SMSI2021/A8.2 SP - 91 EP - 92 AN - OPUS4-52634 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -