TY - JOUR A1 - Haller, T. A1 - Völker, Christoph A1 - Hartmann, T. T1 - Machine learning based multi-sensor fusion for the nondestructive testing of corrosion in concrete N2 - Half-cell potential mapping (HP) is the most popular non-destructive testing method (NDT) for locating corrosion damage in concrete. It is generally accepted that HP is susceptible to environmental factors caused by salt-related deterioration, such as different moisture and chloride gradients. Additional NDT methods are able to identify distinctive areas but are not yet used to estimate more accurate test results. We present a Supervised Machine Learning (SML) based approach to data fusion of seven different signal features to obtain higher quality information. SMLs are methods that explore (or learn) relationships between different (sensor) data from predefined data labels. To obtain a representative, labelled data set we conducted a comprehensive experiment simulating the deterioration cycle of a chloride exposed device in the laboratory. Our data set consists of 18 measurement campaigns, each containing HP, Ground Penetrating- Radar, Microwave Moisture and Wenner resistivity data. We compare the performance of different ML approaches. Many outperform the best single method, HP. We describe the intrinsic challenges posed by a data-driven approach in NDT and show how future work can help overcome them. T2 - SMAR2019 - 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures CY - Potsdam, Germany DA - 27.08.2019 KW - Machine Learning KW - NDT KW - Half-Cell Potential Mapping KW - Corrosion KW - Reinforced Concrete KW - Data Fusion PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-498563 UR - http://www.ndt.net/?id=24890 VL - 25 IS - 1 SP - 24890-1 EP - 24890-8 PB - NDT.net CY - Kirchwald AN - OPUS4-49856 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hauffen, J. C. A1 - Kästner, L. A1 - Ahmadi, Samim A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging N2 - Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging. KW - Thermography KW - Laser KW - Machine learning KW - Optimization KW - Non-destructive testing KW - NDT KW - Neural network KW - Defect reconstruction KW - Block-sparsity KW - Active thermal imaging KW - Regularization KW - Laser thermography PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554598 DO - https://doi.org/10.3390/s22155533 SN - 1424-8220 VL - 22 IS - 15 SP - 1 EP - 15 PB - MDPI CY - Basel AN - OPUS4-55459 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias T1 - Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating N2 - Thermographic photothermal super resolution reconstruction enables the resolution of internal defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. Based on a combination of the application of special sampling strategies and a subsequent numerical optimization step in post-processing, thermographic super resolution has already proven to be superior to standard thermographic methods in the detection of one-dimensional defect/inhomogeneity structures. In our work, we report an extension of the capabilities of the method for efficient detection and resolution of defect cross sections with fully two-dimensional structured laser-based heating. The reconstruction is carried out using one of two different algorithms that are proposed within this work. Both algorithms utilize the combination of several coherent measurements using convex optimization and exploit the sparse nature of defects/inhomogeneities as is typical for most nondestructive testing scenarios. Finally, the performance of each algorithm is rated on reconstruction quality and algorithmic complexity. The presented experimental approach is based on repeated spatially structured heating by a high power laser. As a result, a two-dimensional sparse defect/inhomogeneity map can be obtained. In addition, the obtained results are compared with those of conventional thermographic inspection methods that make use of homogeneous illumination. Due to the sparse nature of the reconstructed defect/inhomogeneity map, this comparison is performed qualitatively. KW - Thermography KW - Super resolution KW - NDT KW - Inspection KW - Internal defects PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-548351 DO - https://doi.org/10.1063/5.0088102 SN - 1089-7550 VL - 131 IS - 18 SP - 1 EP - 12 PB - AIP Publishing AN - OPUS4-54835 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias T1 - Hochaufgelöste thermografische Detektion eingeschlossener Defekte mit Hilfe von 2Dstrukturierten Beleuchtungsmustern N2 - Für die aktive Thermografie als zerstörungsfreie Prüfmethode galt lange Zeit die Faustformel, dass die Auflösung interner Defekte/Inhomogenitäten auf ein Verhältnis von Defekttiefe/Defektgröße ≤ 1 beschränkt ist. Die Ursache hierfür liegt in der diffusiven Natur der Wärmeleitung in Festkörpern. Sogenannte Super-Resolution-Ansätze erlauben seit Kurzem die Überwindung dieser physikalischen Grenze um ein Vielfaches. Damit ergibt sich die attraktive Möglichkeit die Thermografie von einem rein oberflächensensitiven Prüfverfahren hin zu einem Verfahren mit verbesserter Tiefenreichweite zu entwickeln. Wie weit diese Entwicklung getrieben werden kann, ist Gegenstand aktueller Forschung. Wir konnten bereits zeigen, dass diese klassische Grenze für 1D- und 2D Defektgeometrien mit Hilfe des Abscannens des Prüfkörpers mittels einzelner Laserspots und der anschließenden Anwendung von photothermischer Super-Resolution-Rekonstruktion überwunden werden kann. Bei dieser Methode wird eine Kombination aus sequenzieller räumlich strukturierter Beleuchtung und numerischen Optimierungsmethoden eingesetzt. Dies geschieht allerdings auf Kosten der experimentellen Komplexität, die zu einer langen Messdauer, großen Datensätzen und langwieriger numerischer Auswertung führt. In dieser Arbeit berichten wir über einen neuen experimentellen Ansatz, bei dem räumlich strukturierte 2D-Beleuchtungsmuster in Verbindung mit Compressed-Sensing und Computational-Imaging-Methoden verwendet werden, um die experimentelle Komplexität deutlich zu verringern und die Methode für die Untersuchung größerer Prüfflächen nutzbar zu machen. Der experimentelle Ansatz basiert dabei auf der wiederholten (blinden) photothermischen Anregung mit räumlich strukturierten 2D-Mustern unter Verwendung moderner Projektortechnik und eines Hochleistungslasers. In der anschließenden numerischen Rekonstruktion werden mehrere Messungen unter Ausnutzung der Joint-Sparsity der Defekte innerhalb des Prüfkörpers mittels nichtlinearer konvexer Optimierungsmethoden kombiniert. Als Ergebnis kann eine 2D-sparse Defekt-/Inhomogenitätskarte erstellt werden. T2 - DGZfP-Jahrestagung 2022 CY - Kassel, Germany DA - 23.05.2022 KW - Thermografie KW - Super resolution KW - NDT KW - ZfP KW - Eingeschlossene Defekte KW - Projektor PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-548945 SN - 978-3-947971-25-1 VL - 177 SP - 1 EP - 16 PB - Deutsche Gesellschaft für Zerstörungsfreie Prüfung AN - OPUS4-54894 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Klewe, Tim A1 - Völker, Tobias A1 - Götz, J. A1 - Landmann, M. A1 - Wilsch, Gerd A1 - Kruschwitz, Sabine T1 - Sorting of construction and demolition waste by combining LIBS with NIR spectroscopy N2 - In a joint project of partners from industry and research, the automated recycling of construction and demolition waste (CDW) is investigated and tested by combing laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.). The project focuses primarily on the Berlin site to analyze the entire value chain, minimize economic/technological barriers and obstacles at the cluster level, and sustainably increase recovery and recycling rates. First measurements with LIBS and NIR spectroscopy show promising results in distinguishing various material types and indicate the potential for a successful combination. In addition, X-ray fluorescence (XRF) spectroscopy is being performed to obtain more information about the quantitative elemental composition of the different building materials. Future work will apply the developed sorting methodology in a fully automated measurement setup with CDW on a conveyor belt. T2 - NDT-CE 2022 CY - Zurich, Switzerland DA - 16.08.2022 KW - LIBS KW - NDT KW - Circular economy KW - Recycling KW - Material classification PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-555531 UR - http://www.ndt.net/?id=27220 VL - 2022/09 SP - 1 EP - 9 PB - NDT.net CY - Bad Breisig AN - OPUS4-55553 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias ED - Maldague, X. T1 - Detection of internal defects applying photothermal super resolution reconstruction utilizing two-dimensional high-power random pixel patterns N2 - In this work, we report on our progress for investigating a new experimental approach for thermographic detection of internal defects by performing 2D photothermal super resolution reconstruction. We use modern high-power laser projector technology to repeatedly excite the sample surface photothermally with varying spatially structured 2D pixel patterns. In the subsequent (blind) numerical reconstruction, multiple measurements are combined by exploiting the joint-sparse nature of the defects within the specimen using nonlinear convex optimization methods. As a result, a 2D-sparse defect/inhomogeneity map can be obtained. Using such spatially structured heating combined with compressed sensing and computational imaging methods allows to significantly reduce the experimental complexity and to study larger test surfaces as compared to the one-dimensional approach reported earlier. T2 - Quantitative Infrared Thermography 2022 CY - Paris, France DA - 04.07.2022 KW - Thermography KW - Super resolution KW - NDT KW - inspection KW - Internal defects KW - DMD KW - DLP PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-577795 DO - https://doi.org/10.21611/qirt.2022.1005 SN - 2371-4085 SP - 1 EP - 7 PB - QIRT Council AN - OPUS4-57779 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klewe, Tim A1 - Völker, Tobias A1 - Landmann, Mirko A1 - Kruschwitz, Sabine T1 - LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste N2 - AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt. T2 - 21st Ibausil - International Conference on Building Materials CY - Weimar, Germany DA - 13.09.2023 KW - NDT KW - Material cassification KW - Recycling KW - LIBS KW - Data fusion KW - Construction and demolition waste KW - Circular economy PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-590734 DO - https://doi.org/10.1002/cepa.2866 SN - 2509-7075 VL - 6 IS - 6 SP - 973 EP - 976 PB - Ernst & Sohn GmbH AN - OPUS4-59073 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias T1 - Nondestructive thermographic detection of internal defects using pixel-pattern based laser excitation and photothermal super resolution reconstruction N2 - In this work, we present a novel approach to photothermal super resolution based thermographic resolution of internal defects using two-dimensional pixel pattern-based active photothermal laser heating in conjunction with subsequent numerical reconstruction to achieve a high-resolution reconstruction of internal defect structures. With the proposed adoption of pixelated patterns generated using laser coupled high-power DLP projector technology the complexity for achieving true two-dimensional super resolution can be dramatically reduced taking a crucial step forward towards widespread practical viability. Furthermore, based on the latest developments in high-power DLP projectors, we present their first application for structured pulsed thermographic inspection of macroscopic metal samples. In addition, a forward solution to the underlying inverse problem is proposed along with an appropriate heuristic to find the regularization parameters necessary for the numerical inversion in a laboratory setting. This allows the generation of synthetic measurement data, opening the door for the application of machine learning based methods for future improvements towards full automation of the method. Finally, the proposed method is experimentally validated and shown to outperform several established conventional thermographic testing techniques while conservatively improving the required measurement times by a factor of 8 compared to currently available photothermal super resolution techniques. KW - Thermography KW - Super resolution KW - NDT KW - Inspection KW - Internal defects KW - DMD KW - DLP PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-570551 DO - https://doi.org/10.1038/s41598-023-30494-2 SN - 2045-2322 VL - 13 SP - 1 EP - 13 PB - Nature Research AN - OPUS4-57055 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yagdjian, H. A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias A1 - Gurka, M. T1 - Application of the thermal shock response spectrum (TSRS) methodology to various forms of heat sources by pulse thermography and comparison by using a rotating line scan contour search algorithm N2 - In this paper, we propose a novel contour search algorithm (CSA) for image processing. Its efficacy is evaluated through a comparative analysis with established techniques such as Canny Edge and Snakes: Active contour models, utilizing infrared thermography (IRT) images. Based on the new CSA, we investigate the influence of different pulse shapes on the IRT post-processing methodology, particularly focusing on the thermal shock response spectrum (TSRS), using two different heat sources: xenon flash lamps and a laser. Moreover, this allows for a more precise quantitative comparison of the TSRS with existing IRT post-processing techniques, including pulse phase thermography and thermal signal reconstruction, concerning the detection of defects in composite materials, particularly in carbon fiber-reinforced polymer. A quantitative comparison was performed using the Tanimoto criterion and signal-to-noise ratio. A more detailed analysis is conducted to identify inherent limitations and potential benefits of the new TSRS methodology. We further investigate and experimentally confirm our previous finding on the qualitative correlation between the one-dimensional thermal N-layer model and test data from the TSRS optimization process for defect determination. This correlation can eliminate the time-consuming optimization step, making TSRS a more attractive alternative to common IRT methods and enhancing the quantitative description of defects. KW - Thermography KW - Non-destructive testing KW - NDT KW - Defect identification KW - Laser KW - Contour search PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-615056 DO - https://doi.org/10.1063/5.0232015 SN - 1089-7550 VL - 136 IS - 175101 SP - 1 EP - 20 PB - AIP Publishing AN - OPUS4-61505 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ratkovac, Mirjana A1 - Gerards-Wünsche, Paul A1 - Thiele, Marc A1 - Brackrock, Daniel A1 - Stamm, Michael T1 - Detection and monitoring of the fatigue crack growth on welds – Application-oriented use of NDT methods N2 - Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel structures exposed to cyclic loads during their service life. Observation of welded connections is especially of high relevance due to their higher susceptibility to fatigue damage. The aim of this contribution was to monitor fatigue crack growth in thick welded specimens during fatigue tests as holistically as possible, by implementing multiple NDT methods simultaneously in order to record the crack initiation and propagation until the final fracture. In addition to well-known methods such as strain gauges, thermography, and ultrasound, the crack luminescence method developed at the Bundesanstalt für Materialforschung und -prüfung (BAM), which makes cracks on the surface particularly visible, was also used. For data acquisition, a first data fusion concept was developed and applied in order to synchronize the data of the different methods and to evaluate them to a large extent automatically. The resulting database can ultimately also be used to access, view, and analyze the experimental data for various NDT methods. During the conducted fatigue tests, the simultaneous measurements of the same cracking process enabled a comprehensive comparison of the methods, highlighting their individual strengths and limitations. More importantly, they showed how a synergetic combination of different NDT methods can be beneficial for implementation in large-scale fatigue testing but also in monitoring and inspection programs of in-service structures - such as the support structures of offshore wind turbines. T2 - Fatigue Design 2023 (FatDes 2023) CY - Senlis, France DA - 29.11.2023 KW - Fatigue KW - Welded KW - NDT KW - Crack growth PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-600238 DO - https://doi.org/10.1016/j.prostr.2024.03.062 VL - 57 SP - 560 EP - 568 PB - Elsevier B.V. AN - OPUS4-60023 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -