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 - TY - JOUR A1 - Schnur, C. A1 - Goodarzi, P. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Prager, Jens A1 - Tschöke, K. A1 - Moll, J. A1 - Schütze, A. A1 - Schneider, T. T1 - Towards interpretable machine learning for automated damage detection based on ultrasonic guided waves N2 - Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand. Here, this toolbox is applied to a guided wave-based SHM dataset for varying temperatures and damage locations, which is freely available on the Open Guided Waves platform. A classification rate of 96.2% is achieved, demonstrating reliable and automated damage detection. Moreover, the ability of the ML model to identify a damaged structure at untrained damage locations and temperatures is demonstrated. KW - Composite structures KW - Structural health monitoring KW - Carbon fibre-reinforced plastic KW - Interpretable machine learning KW - Automotive industry PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-542060 DO - https://doi.org/10.3390/s22010406 SN - 1424-8220 VL - 22 IS - 1 SP - 1 EP - 19 PB - MDPI CY - Basel AN - OPUS4-54206 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Brence, Blaž A1 - Lugovtsova, Yevgeniya A1 - Prager, Jens T1 - Interdigital Transducers for Structural Health Monitoring N2 - Interdigital transducers (IDTs) are a well-known tool for excitation of surface acoustic waves. The use of IDTs is versatile, but they are most commonly employed as actuators for excitation of ultrasonic guided waves (UGWs). However, they are still a relatively new technology, which leaves many possibilities for future research, especially in the scope of newly emerging structural health monitoring (SHM) systems. IDTs offer low weight, design flexibility and beam directivity, which make them ideal candidates for employment in such systems. Due to the IDTs’ and waves’ complexity, problems often cannot be described analytically, therefore they require numerical solutions and experimental validations. In this contribution, a novel, simple use of IDTs, in the scope of SHM is described. Firstly, numerical findings acquired with finite element method are presented. To validate those results, experiments in a plate-like waveguide are carried out. A good agreement between them is found. The results show the potential of the IDTs in yet another prospective application, which could be attractive for adoption in the future. T2 - 48. Jahrestagung für Akustik (DAGA) CY - Stuttgart, Germany DA - 21.03.2022 KW - Lamb waves KW - Ultrasonic Guided Waves KW - Selective excitation PY - 2022 SP - 221 EP - 224 AN - OPUS4-55501 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - Application of Temperature Compensation Strategies for Ultrasonic Guided Waves to 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 and impact on probability of detection (POD). This paper quantitatively describes two different methods to compensate the temperature effect, namely the optimal baseline selection (OBS) and the baseline signal stretch (BSS) extending their application to the case of a distributed sensor networks (DSN). This latter introduces a number of possible data to explore compensation strategies which do not necessarily returns univocal results. Hence, a decision framework is needed, which takes into consideration multiple ultrasonic time traces with different arrival times and amplitude. In detail, 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 a frequent value warning is introduced to find the more probable temperature with increasing reliability of the assessment. The same procedure is applied using the BSS algorithm. Finally, the use of both approaches is introduced, comparing the capability of the mixed algorithm to correctly sort temperature information from OBS and then apply the BSS combining the frequent value warning to have a unique correction all over the DSN. 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 combinations of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS and BSS approaches making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions. In addition, the possibility to combine BSS approached also demonstrates that the use of compensation strategies improves detectability and localization of damage even in a DSN. This result can be used to improve the SHM system reliability, with promising perspectives in increasing POD. T2 - ASME 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE2022) CY - San Diego, CA, USA DA - 25.07.2022 KW - Performance assessment KW - Elastic waves KW - Structural Health Monitoring PY - 2022 AN - OPUS4-55427 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lugovtsova, Yevgeniya T1 - Towards Characterisation of Elastic Constants of Composite Materials by means of Ultrasonic Guided Waves N2 - The availability of non-destructive methods is particularly important for composites, e.g., carbon or glass fiber-reinforced polymers because their properties strongly depend on the manufacturing process and in-service conditions. Composites are mostly used in thin-walled components which are perfectly suited for the characterisation with ultrasonic guided waves (UGWs). In this contribution, we demonstrate sensitivities of UGW to different elastic constants of a composite material. Then we present a characterisation procedure which can be used to in-fer elastic properties. Our approach is based on an inverse procedure in which the numeri-cally calculated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite various UGW modes and a 3D laser Doppler vibrometer (3D LDV) to record them. Compared to the approaches based on laser excitation, the PZT provides a better signal-to-noise ratio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows cap-turing in-plane and out-of-plane components giving more dispersion information for a better characterisation. Since the inverse procedure requires many iterations before elastic prop-erties are retrieved, an efficient 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 be-tween theoretical and experimental curves is demonstrated. T2 - ASME 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE2022) CY - San Diego, CA, USA DA - 25.07.2022 KW - Carbon fibre reinforced polymer KW - Glass fibre reinforced polymer KW - Inverse procedure PY - 2022 AN - OPUS4-55425 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Barzegar, M. A1 - Pasadas, D. J. A1 - Ribeiro, A. L. A1 - Ramos, H. G. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis T1 - Polar Coordinate for Damage Imaging of Adhesively Bonded Plates Using Ultrasonic Guided Waves and Laser Doppler Vibrometer Measurements N2 - Wavefield measurements by a scanning laser Doppler vibrometer are generally carried out in a cartesian coordinate. As a piezoelectric transducer generates Lamb waves following radial paths, the use of a polar coordinate can be a suitable alternative to the use of a cartesian coordinate. Therefore, in the proposed method, using a single transducer placed on the center of the specimen, the measured wavefields are transformed into polar coordinates, making several identical radial line inspections from the center in a direction of incident waves. Taking advantage of the properties of the polar coordinates, a signal processing technique is proposed through a frequency-wavenumber filtering process in these coordinates. In this technique, by using proper filters, unwanted wave modes of the incident wave along with all reflected waves are filtered out. In addition, the conventional features of RMS and Euclidean distance are adapted for the polar coordinate system to image the bonded plate. The proposed signal processing and damage imaging are first introduced through a numerical simulation. Then, the performance of the proposed technique is presented by experimental measurements of two specimens including adhesively bonded carbon fiber-reinforced plastic composite plates and bonded aluminum plates. KW - Lamb waves KW - Composites KW - Disbond PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-573386 DO - https://doi.org/10.1109/TIM.2023.3267528 SN - 0018-9456 VL - 72 SP - 1 EP - 11 PB - IEEE CY - Piscataway Township, New Jersey, USA AN - OPUS4-57338 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Prager, Jens A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Held, Mathias A1 - Klärner, M. A1 - Winkler, T. A1 - Kroll, L. T1 - Akustische Bestimmung der Werkstoffparameter faserverstärkter Kunststoffe durch Auswertung der Dispersionseigenschaften geführter Wellen N2 - Akustische Verfahren eignen sich hervorragend zur Bestimmung der Werkstoffeigenschaften. Die Verfügbarkeit derartiger Verfahren ist vor allem für Kunststoffe wichtig, da deren Eigenschaften stark abhängig vom jeweiligen Herstellungsprozess und vom Alterungszustand sind. Exakte und vollständige Werte sind daher in Datenbanken oder von Herstellern nur begrenzt zu finden. Insbesondere die Entwicklung von Methoden zur Charakterisierung faserverstärkter Kunststoffe (FKV) ist nach wie vor Gegenstand der Forschung. Hier müssen anisotropiebedingt mehrere Kennwerte bestimmt werden. Da FKV zumeist als dünnwandige Bauteile zum Einsatz kommen, können die Werkstoffparameter aus den Dispersionseigenschaften der Lamb-Wellen, die sich in diesen Strukturen ausbreiten, abgeleitet werden. Dazu ist eine räumliche Abtastung des sich ausbreitenden Schallfelds erforderlich. In der vorliegenden Untersuchung wird dieser Ansatz für die relativ neue Werkstoffklasse der faserverstärkten Thermoplaste angewendet. Diese zeichnet ein ausgeprägtes Dämpfungsverhalten und eine Anisotropie der Materialparameter aus. Dazu wurde das Schallfeld im Ultraschallbereich mit einem Laser-Doppler-Vibrometers vermessen. Rechnerisch bestimmte Dispersionskurven wurden dann an die gemessenen Werte angepasst, womit die richtungsabhängigen Materialparameter bestimmt werden konnten. Im Vortrag wird das Messverfahren vorgestellt und auf spezielle Probleme, die sich z.B. aus dem Dämpfungsverhalten des Werkstoffs ergeben, eingegangen. Ausgewählte gemessene Werte werden mit den Ergebnissen von Referenzverfahren verglichen. T2 - DAGA 2021 - 47. Jahrestagung für Akustik CY - Vienna, Austria DA - 15.08.2021 KW - Ultraschall KW - Composites KW - Thermoplastische Kunststoffe PY - 2021 SP - 52 EP - 55 PB - Deutsche Gesellschaft für Akustik (DEGA) CY - Berlin AN - OPUS4-57340 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nicolai, Marcel A1 - Zeipert, H. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Johannesmann, S. A1 - Prager, Jens A1 - Henning, B. ED - Nicolai, Marcel T1 - Characterization of adhesion strength using guided ultrasonic waves N2 - Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen. Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren. T2 - DAGA 2023 CY - Hamburg, Germany DA - 06.03.2023 KW - SBFEM KW - Adhesive Bonding KW - Kissing Bonds KW - NDT KW - Ultrasonic Guided Waves PY - 2023 UR - https://pub.dega-akustik.de/DAGA_2023 SN - 978-3-939296-21-8 SP - 823 EP - 826 PB - Deutsche Gesellschaft für Akustik e.V. CY - Berlin AN - OPUS4-57378 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nicolai, Marcel A1 - Zeipert, H. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Prager, Jens A1 - Henning, B. A1 - Lozano Duarte, Daniel Hernando T1 - Charakterisierung von Haftfestigkeiten mittels geführter Ultraschallwellen N2 - Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen. Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren. T2 - Schall 23 CY - Wetzlar, Germany DA - 20.03.2023 KW - Adhesive Bonding KW - Kissing Bonds KW - NDT KW - Ultrasonic Guided Waves KW - SBFEM PY - 2023 AN - OPUS4-57379 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Sablowski, J. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Kupsch, C. T1 - Experimental Study of Ultrasonic Guided Waves in a Bipolar Plate of a Fuel Cell N2 - Water management in proton-exchange membrane fuel cells (PEMFCs) is critical for efficient operation. However, in-situ measurements of the water distribution in an operating PEMFC are challenging. In this study, we investigate key aspects of ultrasonic guided wave (UGW) propagation through the bipolar plate of a PEMFC using 3D scanning laser Doppler vibrometry (3D LDV). Our results provide insights for the design and optimization of UGW-based sensor systems for water detection in PEMFCs. T2 - 2023 IEEE International Ultrasonics Symposium (IUS) CY - Montreal, QC, Canada DA - 03.09.2023 KW - Ultrasonic guided waves KW - Laser Doppler vibrometry KW - Fuel cells KW - Water management PY - 2023 DO - https://doi.org/10.1109/IUS51837.2023.10307327 SP - 1 EP - 4 PB - IEEE AN - OPUS4-59540 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Barzegar, M. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Mishurova, Tatiana A1 - Pasadas, Dario J. A1 - Ribeiro, Artur L. A1 - Ramos, Helena G. T1 - Adhesive Porosity Analysis of Composite Adhesive Joints Using Ultrasonic Guided Waves N2 - Adhesively bonded composite joints can develop voids and porosity during fabrication, leading to stress concentration and a reduced load-carrying capacity. Hence, adhesive porosity analysis during the fabrication is crucial to ensure the required quality and reliability. Ultrasonic-guided wave (UGW)-based techniques without advanced signal processing often provide low-resolution imaging and can be ineffective for detecting small-size defects. This article proposes a damage imaging process for adhesive porosity analysis of bonded composite plates using UGWs measured by scanning laser Doppler vibrometer (LDV). To implement this approach, a piezoelectric transducer is mounted on the composite joint specimen to generate UGWs, which are measured over a densely sampled area. The signals obtained from the scan are processed using the proposed signal processing in different domains. Through the utilization of filter banks in frequency and wavenumber domains, along with the root-mean-square calculation of filtered signals, damage images of the adhesive region are obtained. It has been observed that different filters provide information related to different void sizes. Combining all the images reconstructed by filters, a final image is obtained which contains damages of various sizes. The images obtained by the proposed method are verified by radiography results and the porosity analysis is presented. The results indicate that the proposed methodology can detect the pores with the smallest detectable pore area of 2.41 mm^2, corresponding to a radius of 0.88 mm, with an overall tendency to overestimate the pore size by an average of 11%. KW - Adhesives KW - Damage imaging KW - Nondestructive testing (NDT) KW - Porosity analysis KW - Signal processing KW - Ultrasonic guided waves (UGWs) PY - 2024 DO - https://doi.org/10.1109/TUFFC.2024.3371671 VL - 71 IS - 4 SP - 485 EP - 495 PB - Institute of Electrical and Electronics Engineers (IEEE) AN - OPUS4-59970 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Barzegar, M. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Mishurova, Tatiana A1 - Pasadas, D. A1 - Ribeiro, A. A1 - Ramos, H. T1 - Automatic improved-resolution imaging of composite adhesive joints using time-frequency-wavenumber filtering applied to ultrasonic guided wavefields N2 - This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm. T2 - 2023 IEEE International Ultrasonics Symposium (IUS) CY - Montreal, QC, Canada DA - 03.09.2023 KW - Adhesive joints KW - Ultrasonic guided waves KW - Laser Doppler vibrometer KW - Damage imaging KW - Non-destructive testing KW - Porosity analysis PY - 2023 DO - https://doi.org/10.1109/IUS51837.2023.10307423 SP - 1 EP - 4 PB - IEEE AN - OPUS4-58795 LA - eng 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. ED - Kundu, T. ED - Reis, H. ED - Ihn, J.-B. ED - Dzenis, Y. 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 - 2021 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 VL - QNDE2021-75215 SP - 1 EP - 6 PB - The American Society of Mechanical Engineers (ASME) CY - New York, USA AN - OPUS4-56723 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yablokov, A. A1 - Lugovtsova, Yevgeniya A1 - Serdyukov, A. T1 - Uncertainty quantification of multimodal surface wave inversion using artificial neural networks N2 - An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results – using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time. KW - Multi-layers KW - Multichannel analysis of surface waves (MASW) KW - Characterisation of soil sites KW - Monte Carlo simulation KW - Field data PY - 2023 DO - https://doi.org/10.1190/geo2022-0261.1 SN - 0016-8033 VL - 88 IS - 2 SP - 1 EP - 43 PB - Society of Exploration Geophysicists CY - Tulsa, Okla. AN - OPUS4-56624 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -