TY - JOUR A1 - Bayerlein, Bernd A1 - Hanke, T. A1 - Muth, Thilo A1 - Riedel, Jens A1 - Schilling, Markus A1 - Schweizer, C. A1 - Skrotzki, Birgit A1 - Todor, A. A1 - Moreno Torres, Benjami A1 - Unger, Jörg F. A1 - Völker, Christoph A1 - Olbricht, Jürgen T1 - A Perspective on Digital Knowledge Representation in Materials Science and Engineering N2 - The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples. In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge. KW - Data infrastructures KW - Digital representations KW - Digital workflows KW - Knowledge graphs KW - Materials informatics KW - Ontologies KW - Vocabulary providers PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546729 DO - https://doi.org/10.1002/adem.202101176 SN - 1438-1656 SP - 1 EP - 14 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-54672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Altenburg, Simon A1 - Straße, Anne A1 - Gumenyuk, Andrey A1 - Maierhofer, Christiane T1 - In-situ monitoring of a laser metal deposition (LMD) process: comparison of MWIR, SWIR and high-speed NIR thermography N2 - Additive manufacturing offers a range of novel applications. However, the manufacturing process is complex and the production of almost defect-free parts with high reliability and durability is still a challenge. Thermography is a valuable tool for process surveillance, especially in metal additive manufacturing processes. The high process temperatures allow one to use cameras usually operating in the visible spectral range. Here, we compare the results of measurements during the manufacturing process of a commercial laser metal deposition setup using a mid wavelength infrared camera with those from a short wavelength infrared camera and those from a visual spectrum high-speed camera with band pass filter in the near infrared range. KW - Additive Manufacturing KW - Process monitoring KW - Thermography KW - LMD KW - Metal KW - MWIR KW - SWIR KW - NIR PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-516318 DO - https://doi.org/10.1080/17686733.2020.1829889 VL - 19 IS - 2 SP - 97 EP - 114 PB - Taylor & Francis Group CY - London, UK AN - OPUS4-51631 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Altenburg, Simon A1 - Chien, M. A1 - Bavendiek, F. A1 - Krankenhagen, Rainer T1 - Schichtdickenbestimmung von Oberflächenschutzsystemen für Beton mit Impulsthermografie T1 - Thickness determination of surface Protection systems for concrete by means of impulse thermography N2 - Im Bauwesen werden Polymerbeschichtungen auf Beton häufig eingesetzt um zum einen, ein bestimmtes Aussehen zu schaffen und zum anderen, das Bauteil vor Alterung, Verschleiß und Schädigung zu schützen. Für praktisch alle Ziele ist die Wirkung von der eigens dafür definierten Schichtdicke der Polymerbeschichtung abhängig. Daher wird die Dicke der Beschichtung nach erfolgtem Schichtauftrag überprüft. Für den in diesem Zusammenhang anspruchsvollen mineralischen Untergrund Beton stehen bislang allerdings nur zerstörende Prüfverfahren zur Verfügung. Aus diesem Grund wurden im Rahmen des Projektes IRKUTSK ein auf aktiver Thermografie basierendes Verfahren sowie ein Gerät für den vor-Ort-Einsatz entwickelt, mit dessen Hilfe eine zerstörungsfreie Schichtdickenbestimmung möglich ist. Hier wird ein kurzer Einblick in das zur Schichtdickenbestimmung entwickelte Thermografieverfahren gegeben. Die Besonderheiten bei der quantitativen Auswertung, die durch die Teiltransparenz der Polymerbeschichtungen auftreten, werden erläutert. Die Funktion des Verfahrens für einlagige Systeme wird anhand von Labormessungen mit verschiedenen optischen Quellen zur thermischen Anregung illustriert. KW - Beton KW - Oberflächenschutzsystem KW - Schichtdickenbestimmung KW - Thermografie PY - 2018 DO - https://doi.org/10.3139/120.111210 SN - 0025-5300 VL - 60 IS - 7-8 SP - 759 EP - 764 PB - Hanser Verlag CY - München, Deutschland AN - OPUS4-45566 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Altenburg, Simon A1 - Bernegger, Raphael A1 - Krankenhagen, Rainer T1 - Absorption coefficient dispersion in flash thermography of semitransparent solids N2 - Pulse and flash thermography are experimental techniques which are widely used in the field of non-destructive testing for materials characterization and defect detection. We recently showed that it is possible to determine quantitatively the thickness of semitransparent polymeric solids by fitting of results of an analytical model to experimental flash thermography data, for both transmission and reflection configuration. However, depending on the chosen experimental configuration, different effective optical absorption coefficients had to be used in the model to properly fit the respective experimental data, although the material was always the same. Here, we show that this effect can be explained by the wavelength dependency of the absorption coefficient of the sample material if a polychromatic light source, such as a flash lamp, is used. We present an extension of the analytical model to describe the decay of the heating irradiance by two instead of only one effective absorption coefficient, greatly extending its applicability. We show that using this extended model, the experimental results from both measurement configurations and for different sample thicknesses can be fitted by a single set of parameters. Additionally, the deviations between experimental and modeled surface temperatures are reduced compared to a single optimized effective absorption coefficient. T2 - 19th International Conference on Photoacoustic and Photothermal Phenomena CY - Bilbao, Spain KW - Absorptance KW - Dispersion KW - Flash thermography KW - Infrared thermography KW - NDT KW - Semitransparency PY - 2018 DO - https://doi.org/10.1007/s10765-018-2474-0 SN - 0195-928X SN - 1572-9567 VL - 40 IS - 1 SP - 13, 1 EP - 13 PB - Springer Nature AN - OPUS4-47105 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Thummerer, G. A1 - Breitwieser, S. A1 - Mayr, G. A1 - Lecompagnon, Julien A1 - Burgholzer, P. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Multi-dimensional reconstruction of internal defects in additively manufactured steel using photothermal super resolution combined with virtual wave based image processing N2 - We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wavebased inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution. KW - Active thermography KW - Additive manufacturing KW - Stainless steel KW - ADMM KW - Block regularization KW - Internal defects KW - Joint sparsity KW - Laser excitation KW - Multi-dimensional reconstruction KW - Photothermal super resolution KW - Virtual waves PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-525330 DO - https://doi.org/10.1109/tii.2021.3054411 SN - 1551-3203 SN - 1941-0050 VL - 17 IS - 11 SP - 7368 EP - 7378 PB - IEEE CY - New York, NY AN - OPUS4-52533 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Burgholzer, P. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Laser excited super resolution thermal imaging for nondestructive inspection of internal defects N2 - A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple measurement events. This concerted approach of experimental measurement strategy and numerical optimization enables the resolution of internal defects and outperforms conventional thermographic inspection techniques. KW - Super Resolution KW - Laser Thermography KW - Non Destructive Testing KW - Comressed Sensing KW - Inverse Problem KW - Thermography PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-519016 DO - https://doi.org/10.1038/s41598-020-77979-y VL - 10 IS - 1 SP - 22357 PB - Springer Nature AN - OPUS4-51901 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Kästner, L. A1 - Hauffen, Jan Christian A1 - Jung, P. A1 - Ziegler, Mathias T1 - Photothermal-SR-Net: A customized deep unfolding neural network for photothermal super resolution imaging N2 - This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step. KW - Deep unfolding KW - Defect reconstruction KW - Elastic net KW - Inverse problems KW - Iterative shrinkage thresholding KW - Neural network KW - Nondestructive testing (NDT) KW - Photothermal imaging KW - Super resolution (SR) KW - Thermography PY - 2022 DO - https://doi.org/10.1109/tim.2022.3154803 SN - 1557-9662 VL - 71 SP - 1 EP - 9 PB - IEEE AN - OPUS4-54678 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Photothermal super resolution imaging: A comparison of different thermographic reconstruction techniques N2 - This paper presents different super resolution reconstruction techniques to overcome the spatial resolution limits in thermography. Pseudo-random blind structured illumination from a onedimensional laser array is used as heat source for super resolution thermography. Pulsed thermography measurements using an infrared camera with a high frame rate sampling lead to a huge amount of data. To handle this large data set, thermographic reconstruction techniques are an essential step of the overall reconstruction process. Four different thermographic reconstruction techniques are analyzed based on the Fourier transform amplitude, principal component analysis, virtual wave reconstruction and the maximum thermogram. The application of those methods results in a sparse basis representation of the measured data and serves as input for a compressed sensing based algorithm called iterative joint sparsity (IJOSP). Since the thermographic reconstruction techniques have a high influence on the result of the IJOSP algorithm, this paper Highlights their Advantages and disadvantages. KW - Super resolution KW - Compressed sensing KW - Laser thermography KW - Virtual wave KW - Defect reconstruction PY - 2020 DO - https://doi.org/10.1016/j.ndteint.2020.102228 VL - 111 SP - 2228 PB - Elsevier Ltd. CY - Netherlands AN - OPUS4-50419 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Burgholzer, P. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Super resolution laser line scanning thermography N2 - In this paper we propose super resolution measurement and post-processing strategies that can be applied in thermography using laser line scanning. The implementation of these techniques facilitates the separation of two closely spaced defects and avoids the expected deterioration of spatial resolution due to heat diffusion. The experimental studies were performed using a high-power laser as heat source in combination with pulsed thermography measurements (step scanning) or with continuous heating measurements (continuous scanning). Our work shows that laser line step scanning as well as continuous scanning both can be used within our developed super resolution (SR) techniques. Our SR techniques make use of a compressed sensing based algorithm in post- processing, the so-called iterative joint sparsity (IJOSP) approach. The IJOSP method benefits from both - the sparse nature of defects in space as well as from the similarity of each measurement. In addition, we show further methods to improve the reconstruction quality e.g. by simple manipulations in thermal image processing such as by considering the effect of the scanning motion or by using different optimization algorithms within the IJOSP approach. These super resolution image processing methods are discussed so that the advantages and disadvantages of each method can be extracted. Our contribution thus provides new approaches for the implementation of super resolution techniques in laser line scanning thermography and informs about which experimental and post-processing parameters should be chosen to better separate two closely spaced defects. KW - Super resolution KW - Laser thermography KW - Compressed sensing KW - Laser scanning KW - Joint sparsity PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-509796 DO - https://doi.org/10.1016/j.optlaseng.2020.106279 SN - 0143-8166 VL - 134 SP - 106279 PB - Elsevier Ltd. AN - OPUS4-50979 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -