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 - TY - JOUR A1 - Zeipert, H. A1 - Claes, L. A1 - Johannesmann, S. A1 - Lugovtsova, Yevgeniya A1 - Nicolai, Marcel A1 - Prager, Jens A1 - Henning, Bernd ED - Jumar, U. T1 - An approach to adhesive bond characterisation using guided acoustic waves in multi-layered plates N2 - An approach for the non-destructive characterisation of adhesive bonds using guided ultrasonic waves is presented. Pulsed laser radiation is used to thermoacoustically excite broadband ultrasonic waves in a multi-layered sample, consisting of a metal plate adhesively joined to a polymeric layer using synthetic resin. The resulting signals are received by a purpose-built piezoelectric transducer. Varying the distance between excitation and detection yields spatio-temporal measurement data, from which the dispersive properties of the propagating waves can be inferred using a two-dimensional Fourier transform, assuming the plates to act as coupled waveguides. Coupled multi-layered waveguides show an effect referred to as mode repulsion, where the distance between certain modes in the frequency-wavenumber domain is assumed to be a measure of coupling strength. Measurements at different stages of curing of the adhesive layer are performed and evaluated. A comparison of the results shows changes in the dispersive properties, namely an increased modal bandwidth for the fully cured sample as well as an increased modal distance. KW - Adhesive bonding KW - Guided waves KW - Non-destructive testing KW - Ultrasound PY - 2021 DO - https://doi.org/10.1515/auto-2021-0089 VL - 69 IS - 11 SP - 962 EP - 969 PB - De Gruyter CY - Berlin/Boston AN - OPUS4-53762 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - К определению прочности клеевого соединения в многослойных материалах путем исследования областей расталкивания бегущих упругих волн T1 - Towards the determination of adhesive bonding strength of multi-layered materials by investigating guided wave mode repulsion N2 - Бегущие упругие волны часто используются в области неразрушающего контроля для определения механических характеристик материалов. Поскольку склеивание различных материалов является широко используемым методом в автомобильной и авиационной промышленности, необходима надежная система измерения для определения качества таких клеевых соединений. Дисперсионные кривые для многослойных волноводов при наличии клеевых прослоек характеризуются появлением эффекта расталкивания нормальных мод в тех областях, где соответствующие моды для отдельных материалов пересекались бы. Таким образом, в зависимости от качества клеевого соединения расстояние между этими модами изменяется. Используя комбинацию экспериментальных и численных данных, в настоящей работе представлен подход к определению параметра, указывающего на качество клеевого соединения. T2 - XXX Всероссийская школа-конференция МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ CY - Perm, Russia DA - 06.10.2021 KW - многослойный волновод KW - волны лэмбовского типа KW - контроль качества клеевого соединения PY - 2021 AN - OPUS4-53768 LA - rus AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya A1 - Zeipert, H. A1 - Johannesmann, S. A1 - Nicolai, Marcel A1 - Prager, Jens A1 - Henning, B. T1 - К определению прочности клеевого соединения в многослойных материалах путем исследования областей расталкивания бегущих упругих волн T1 - Towards the determination of adhesive bonding strength of multi-layered materials by investigating guided wave mode repulsion N2 - Бегущие упругие волны часто используются в области неразрушающего контроля для определения механических характеристик материалов. Поскольку склеивание различных материалов является широко используемым методом в автомобильной и авиационной промышленности, необходима надежная система измерения для определения качества таких клеевых соединений. Дисперсионные кривые для многослойных волноводов при наличии клеевых прослоек характеризуются появлением эффекта расталкивания нормальных мод в тех областях, где соответствующие моды для отдельных материалов пересекались бы. Таким образом, в зависимости от качества клеевого соединения расстояние между этими модами изменяется. Используя комбинацию экспериментальных и численных данных, в настоящей работе представлен подход к определению параметра, указывающего на качество клеевого соединения. T2 - XXX Всероссийская школа-конференция МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ CY - Online meeting DA - 06.10.2021 KW - многослойный волновод KW - волны лэмбовского типа KW - контроль качества клеевого соединения PY - 2021 SP - 1 EP - 3 AN - OPUS4-53769 LA - rus AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schnur, C. A1 - Moll, J. A1 - Lugovtsova, Yevgeniya A1 - Schütze, A. A1 - Schneider, T. T1 - Explainable machine learning for damage detection - In carbon fiber composite plates under varying temperature conditions N2 - Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics. T2 - 48th Annual Review of Progress in Quantitative Nondestructive Evaluation CY - Online meeting DA - 28.07.2021 KW - Explainable machine learning KW - Guided waves KW - Damage detection KW - Structural health monitoring KW - Composite structures PY - 2021 SN - 978-0-7918-8552-9 DO - https://doi.org/10.1115/QNDE2021-75215 SP - 1 EP - 6 PB - American Society of Mechanical Engineers (ASME) CY - New York, NY AN - OPUS4-54219 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kudela, P. A1 - Radzienski, M. A1 - Moix-Bonet, M. A1 - Willberg, C. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Tschöke, K. A1 - Moll, J. T1 - Dataset on full ultrasonic guided wavefield measurements of a CFRP plate with fully bonded and partially debonded omega stringer N2 - The fourth dataset dedicated to the Open Guided Waves platform presented in this work aims at a carbon fiber composite plate with an additional omega stringer at constant temperature conditions. The dataset provides full ultrasonic guided wavefields. A chirp signal in the frequency range 20-500 kHz and Hann windowed tone-burst signal with 5 cycles and carrier frequencies of 16.5 kHz, 50 kHz, 100 kHz, 200 kHz and 300kHz are used to excite the wave. The piezoceramic actuator used for this purpose is attached to the center of the stringer side surface of the core plate. Three scenarios are provided with this setup: (1) wavefield measurements without damage, (2) wavefield measurements with a local stringer debond and (3) wavefield measurements with a large stringer debond. The defects were caused by impacts performed from the backside of the plate. As result, the stringer feet debonds locally which was verified with conventional ultrasound measurements. The dataset can be used for benchmarking purposes of various signal processing methods for damage imaging. The detailed description of the dataset is published in Data in Brief Journal. KW - Open data KW - Ultrasonic guided waves KW - Experimental data PY - 2021 DO - https://doi.org/10.5281/zenodo.5105861 PB - Zenodo CY - Geneva AN - OPUS4-54504 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kudela, P. A1 - Radzienski, M. A1 - Moix-Bonet, M. A1 - Willberg, C. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Tschöke, K. A1 - Moll, J. T1 - Dataset on full ultrasonic guided wavefield measurements of a CFRP plate with fully bonded and partially debonded omega stringer N2 - The fourth dataset dedicated to the Open Guided Waves platform presented in this work aims at a carbon fiber composite plate with an additional omega stringer at constant temperature conditions. The dataset provides full ultrasonic guided wavefields. Two types of signals were used for guided wave excitation, namely chirp signal and tone-burst signal. The chirp signal had a frequency range of 20-500kHz. The tone-burst signals had a form of sine modulated by Hann window with 5 cycles and carrier frequencies 16.5kHz, 50kHz, 100kHz, 200kHz, 300kHz. The piezoceramic actuator used for this purpose was attached to the center of the stringer side surface of the core plate. Three scenarios are provided with this setup: (1) wavefield measurements without damage, (2) wavefield measurements with a local stringer debond and (3) wavefield measurements with a large stringer debond. The defects were caused by impacts performed from the backside of the plate. As result, the stringer feet debonds locally which was verified with conventional ultrasound measurements. KW - Lamb waves KW - Composite panel KW - Impact damage KW - Damage detection KW - Scanning laser Doppler vibrometry KW - Structural health monitoring KW - Non-destructive evaluation KW - Open data PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-545242 DO - https://doi.org/10.1016/j.dib.2022.108078 SN - 2352-3409 VL - 42 SP - 1 EP - 13 PB - Elsevier CY - Amsterdam AN - OPUS4-54524 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - Reconstruction of Elastic Constants of Isotropic and Anisotropic Materials using Ultrasonic Guided Waves N2 - Acoustic methods are ideally suited for determining the mechanical properties of different materials non-destructively. The availability of such methods is particularly important for fiber-reinforced polymers (FRPs) because their properties strongly depend on the manufacturing process and in-service conditions. Since FRPs are mostly used in thin-walled components, properties can be derived from the dispersion curves of ultrasonic guided waves (UGWs). Our approach is based on an inverse procedure in which the numerically calcu-lated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite and a 3D laser Doppler vibrometer (3D LDV) to record the waves. Compared to the ap-proaches based on laser excitation, the PZT provides a better signal-to-noise ra-tio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows capturing in-plane and out-of-plane components and thus providing more dispersion information. Since the inverse procedure requires many iterations before elastic properties are retrieved, an ef-ficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement between theoretical and experimental curves is demonstrated. T2 - 10th European Workshop on Structural Health Monitoring (EWSHM 2022) CY - Palermo, Italy DA - 04.07.2022 KW - Lamb waves KW - Elastic waves KW - Fibre-reinforced polymers KW - Inverse procedure KW - Scaled Boundary Finite Element Method PY - 2022 AN - OPUS4-55236 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Olino, M. A1 - Lugovtsova, Yevgeniya A1 - Memmolo, V. A1 - Prager, Jens T1 - Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks N2 - The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage. T2 - IEEE International Workshop on Metrology for AeroSpace CY - Pisa, Italy DA - 27.06.2022 KW - Ultrasound KW - Ultrasonic Guided Waves KW - Structural Health Monitoring PY - 2022 SN - 978-1-6654-1076-2 DO - https://doi.org/10.1109/MetroAeroSpace54187.2022.9856029 SP - 598 EP - 601 AN - OPUS4-55268 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mueller, I. A1 - Freitag, S. A1 - Memmolo, V. A1 - Moix-Bonet, M. A1 - Möllenhoff, K. A1 - Golub, M. A1 - Sridaran Venkat, R. A1 - Lugovtsova, Yevgeniya A1 - Eremin, A. A1 - Moll, J. A1 - Tschöke, K. ED - Rizzo, P. ED - Milazzo, A. T1 - Performance Assessment for Artificial Intelligence-Based Data Analysis in Ultrasonic Guided Wave-Based Inspection: A Comparison to Classic Path-Based Probability of Detection N2 - Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment. With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case. Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs. T2 - 10th European Workshop on Structural Health Monitoring (EWSHM 2022) CY - Palermo, Italy DA - 04.07.2022 KW - Probability of Detection KW - Composites KW - Open Guided Waves Platform KW - Artificial Neural Network PY - 2022 SN - 978-3-031-07257-4 DO - https://doi.org/10.1007/978-3-031-07258-1 SN - 2366-2557 VL - 2 SP - 953 EP - 961 PB - Springer CY - Cham, Switzerland AN - OPUS4-55269 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Tschöke, K. A1 - Mueller, I. A1 - Memmolo, V. A1 - Sridaran Venkat, R. A1 - Golub, M. A1 - Eremin, A. A1 - Moix-Bonet, M. A1 - Möllenhoff, K. A1 - Lugovtsova, Yevgeniya A1 - Moll, J. A1 - Freitag, S. ED - Rizzo, P. ED - Milazzo, A. T1 - A Model-Assisted Case Study Using Data from Open Guided Waves to Evaluate the Performance of Guided Wave-Based Structural Health Monitoring Systems N2 - Reliability assessment of Structural Health Monitoring (SHM) systems poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements. Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed. T2 - 10th European Workshop on Structural Health Monitoring (EWSHM 2022) CY - Palermo, Italy DA - 04.07.2022 KW - Performance assessment KW - Ultrasonic Guided Waves KW - Open Guided Waves Platform PY - 2022 SN - 978-3-031-07257-4 DO - https://doi.org/10.1007/978-3-031-07258-1 SN - 2366-2557 VL - 2 SP - 938 EP - 944 PB - Springer CY - Cham, Switzerland AN - OPUS4-55270 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -