TY - CONF A1 - Heckel, Thomas A1 - Vahlsing, Thorsten A1 - Raum, Hanne A1 - Casperson, Ralf A1 - Pohl, Rainer A1 - Heckel, Thomas A1 - Beilken, D. A1 - Dilz, K. A1 - Rühe, S. T1 - FE-simulation of eddy current signals produced from basic model cracks for running surface rail defects N2 - Non-destructive testing for surface crack detection and head check depth quantification at the gauge corner of railway tracks can be achieved using eddy current methods. With the extension of the tested zone to the running surface, rail defect signal types other than head checks can be measured. Due to their mostly irregular shape, a quantitation based on a calibration against regular test cracks of varying depth may not be linear. Estimates of the expected influence of more complex crack patterns may be obtained by a finite element simulation of sufficiently simple limiting cases, like two displaced or intersecting cracks or a simply branched or flexed crack. As a first step, a 3D finite element model of the HC10 eddy current probe distributed by Prüftechnik Linke und Rühe (PLR), Germany was built and verified against measured results from an (easily fabricated) reference block with isolated long cracks. T2 - Railway Engineering 2019 CY - Edinburgh, UK DA - 03.07.2019 KW - Finite element analysis KW - Eddy current testing KW - Rail inspection PY - 2019 AN - OPUS4-48530 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pelkner, Matthias A1 - Maierhofer, Christiane A1 - Altenburg, Simon T1 - Process monitoring in metal AM@BAM, the project ProMoAM N2 - In this presentation we give an overview of activities regarding non-destructive testing of AM components during the manufacturing process. For this purpose, we installed different NDT methods inside the AM systems. The results obtained during the manufacturing process are presented and discussed. T2 - 74th IIW Annual Assembly and International Conference CY - Online meeting DA - 07.07.2021 KW - Non-destructive testing KW - Additive manufacturing KW - Online monitoring PY - 2021 AN - OPUS4-53186 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bernegger, Raphael A1 - Altenburg, Simon A1 - Maierhofer, Christiane T1 - Iterative numerical 2D-modelling for quantification of material defects by pulsed thermography N2 - This paper presents a method to quantify the geometry of defects such as flat bottom holes (FBH) and notches in opaque materials by a pulse thermography (PT) experiment and a numerical model. The aim was to precisely describe PT experiments in reflection configuration with a simple and fast numerical model in order to use this model and a fit algorithm to quantify defects within the material. The algorithm minimizes the difference between the time sequence of a line shaped region of interest (ROI) on the surface (above the defect) from the PT experiment and the numerical data. Therefore, the experimental data can be reconstructed with the numerical model. In this way, the defect depth of a notch or FBH and its width or diameter was determined simultaneously. A laser was used for heating which was widened to a top hat spatial profile to ensure homogeneous illumination (rectangular impulse profile in time). The numerical simulation considers heating conditions and takes thermal losses due to convection and radiation into account. We quantified the geometry of FBH and notches in steel and polyvinyl chloride plasticized (PVC-U) materials with an accuracy of < 5 %. KW - Pulsed thermography KW - Numerical modelling KW - Data reconstruction KW - Opaque materials KW - 2D model KW - Flat bottom holes KW - Notches PY - 2019 DO - https://doi.org/10.1063/1.5099719 SN - 0094-243X SP - 020015-1 EP - 11 PB - AIP AN - OPUS4-47974 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 - INPR 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 paper presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super resolution (SR) imaging. Photothermal imaging is a well-known technique in active thermography for nondestructive inspection of defects in materials such as metals or composites. A grand challenge of active thermography is to overcome the spatial resolution limitation imposed by heat diffusion in order to accurately resolve each defect. The photothermal SR approach enables to extract high-frequency spatial components based on the deconvolution with the thermal point spread function. However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, hand-crafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, Photothermal-SR-Net is proposed in this paper, which performs deconvolution by deep unfolding considering the underlying physics. This enables to super resolve 2D thermal images for nondestructive testing with a substantially improved convergence rate. Since defects appear sparsely in materials, Photothermal-SR-Net applies trained blocksparsity thresholding to the acquired thermal images in each convolutional layer. The performance of the proposed approach is evaluated and discussed using various deep unfolding and thresholding approaches applied to 2D thermal images. Subsequently, studies are conducted on how to increase the reconstruction quality and the computational performance of Photothermal-SR-Net is evaluated. 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 - Photothermal super resolution KW - Nondestructive testing KW - Deep unfolding KW - Deep learning KW - Deep imaging KW - Physics-based deep learning KW - Laser thermography KW - Elastic net KW - Iterative shrinkage thresholding algorithm PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-525371 DO - https://doi.org/10.48550/arXiv.2104.10563 SN - 2331-8422 SP - 1 EP - 10 PB - Cornell University CY - Ithaca, NY AN - OPUS4-52537 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - INPR A1 - Ahmadi, Samim A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Burgholzer, P. A1 - Jung, P. A1 - Caire, G. 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 - Photothermal KW - Imaging KW - Compressed sensing KW - Internal defects KW - Nondestructive testing PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-518866 DO - https://doi.org/10.48550/arXiv.2007.03341 SN - 2331-8422 SP - 1 EP - 9 PB - Cornell University CY - Ithaca, NY AN - OPUS4-51886 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiel, Erik A1 - Ziegler, Mathias A1 - Ahmadi, Samim A1 - Portella, Pedro Dolabella T1 - Structured heating in active thermography by using laser arrays N2 - Lock-in- and flash thermography are standard methods in active thermography. They are widely used in industrial inspection tasks e.g. for the detection of delaminations, cracks or pores. The requirements for the light sources of these two methods are substantially different. While lock-in thermography requires sources that can be easily and above all fast modulated, the use of flash thermography requires sources that release a very high optical energy in the very short time. By introducing high-power vertical cavity surface emitting lasers (VCSELs) arrays to the field of thermography a source is now available that covers these two areas. VCSEL arrays combine the fast temporal behavior of a diode laser with the high optical irradiance and the wide illumination range of flash lamps or LEDs and can thus potentially replace all conventional light sources of thermography. However, the main advantage of this laser technology lies in the independent control of individual array areas. It is therefore possible to heat not only in terms of time, but also in terms of space. This new degree of freedom allows the development of new NDT methods. We demonstrate this approach using a test problem that can only be solved to a limited extent in active thermography, namely the detection of very thin, hidden defects in metallic materials that are aligned vertically to the surface. For this purpose, we generate destructively interfering thermal wave fields, which make it possible to detect defects within the range of the thermal wave field high sensitivity. This is done without pre-treatment of the surface and without using a reference area to depths beyond the usual thermographic rule of thumb. T2 - ConaEnd&Iev 2018 CY - Sao Paulo, Brazil DA - 27.08.2018 KW - VCSEL KW - Active thermography KW - Laser KW - Structured heating KW - Subsurface defects PY - 2018 AN - OPUS4-45851 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Hirsch, Philipp Daniel A1 - Karagianni, Christina A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. T1 - Photothermal super resolution imaging: a comparison of different reconstruction techniques N2 - The diffusive nature of heat propagation complicates the separation of two closely spaced defects. This results in a fundamental limitation in spatial resolution. Therefore, super resolution (SR) image reconstruction can be used. SR processing techniques based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern. This paper presents the results after applying SR algorithms such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Two different data processing strategies are evaluated and discussed regarding their influence on the reconstruction goodness as well as their complexity. Moreover, the degradation of the SR reconstruction by the choice of regularization parameters in data processing is discussed. The application of both SR techniques that are evaluated in this paper results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects. The fundamental difference between both SR techniques is their complexity. T2 - 46th Annual Review of Profress in Quantitative Nondestructive Evaluation CY - Portland, OR, USA DA - 14.07.2019 KW - Super resolution KW - Virtual wave KW - Laser thermography KW - 1d laser KW - Joint sparsity KW - Laser array KW - VCSEL array KW - High-power laser KW - Fourier transform KW - Dimension reduction PY - 2019 AN - OPUS4-48579 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 - 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 - TY - INPR A1 - Ahmadi, Samim A1 - Hauffen, Jan Christian A1 - Kästner, L. 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. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data 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 than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging. KW - Iterative shrinkage thresholding algorithm KW - Neural network KW - Deep learning KW - Active thermography KW - Photothermal super resolution PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-525364 DO - https://doi.org/10.48550/arXiv.2012.03547 SN - 2331-8422 SP - 1 EP - 11 PB - Cornell University CY - Ithaca, NY AN - OPUS4-52536 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 - CONF A1 - Ziegler, Mathias A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Lecompagnon, Julien A1 - Hassenstein, Christian A1 - Thiel, Erik A1 - Pech May, Nelson Wilbur T1 - Using spatial and temporal shaping of laser-induced diffuse thermal wave fields in thermography N2 - The diffuse nature of thermal waves is a fun-damental limitation in thermographic nonde-structive testing. In our studies we investigated different approaches by shaping the thermal wave fields which result from heating. We have used high-power laser sources to heat metallic samples. Using these spatial and temporal shaping techniques leads to a higher detection sensitivity in our measurements with the infra-red camera. In this contribution we show our implementation of shaping laser-induced diffuse thermal wave fields and the effect on the defect reconstruction quality. T2 - SMSI 2020 Conference CY - Online meeting DA - 22.06.2020 KW - Thermal wave KW - Diffusion KW - High-power laser KW - Thermography KW - Spatiotemporal shaping PY - 2020 DO - https://doi.org/10.5162/SMSI2020/C5.1 SP - 179 EP - 180 AN - OPUS4-50897 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Krankenhagen, Rainer A1 - Ziegler, Mathias A1 - Maierhofer, Christiane ED - Maldague, X. T1 - Systematic errors in the evaluation of uncorrected data from thermographic lock-in measurements N2 - Lock-in thermography (LT) is based on the correct evaluation of phase differences between the temperature oscillations at different surface regions of the object under test during periodic heating. Since the usual heating procedures contain a DC component, the actual heating pattern achieved is not harmonic. This causes systematic deviations when phase differences are determined by means of harmonic analysis, e.g. with FFT analysis. The resulting errors depend clearly on the ratio between DC and AC amplitude, which is demonstrated at simulated and experimentally recorded temperature transients. Further experimental LT data obtained by different oscillating energy inputs showed a variety of possible shapes of transients with different DC components. T2 - 14th QIRT Conference CY - Berlin, Germany DA - 26.06.2018 KW - NDT KW - Lock-in Thermography KW - FFT PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-453768 SP - 539 EP - 547 PB - QIRT Council AN - OPUS4-45376 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thummerer, G. A1 - Mayr, G. A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias A1 - Burgholzer, P. T1 - Photothermal Image Reconstruction in Opaque Media with Virtual Wave Backpropagation N2 - Thermographic reconstruction of defects that lie in the bulk of a sample is a difficult task because entropy production during heat diffusion leads to information loss. To reconstruct defects one has to solve an inverse heat conduction problem. The quality of the reconstruction is closely related to the information content of the observed data set that is reflected by the decreasing ability to spatially resolve a defect with growing defect depth. In this work we show a 2D reconstruction of rectangular slots with different width-to-depth ratios in a metallic sample. For this purpose, we apply the virtual wave concept and incorporate positivity and sparsity as prior information to overcome the diffusion-based information loss partially. The reconstruction is based on simulated and experimental pulse thermography data. In the first reconstruction step, we compute a virtual wave field from the surface temperature data. This allows us, in the second step, to use ultrasonic backpropagation methods for image reconstruction. KW - Virtual wave concept KW - Thermography KW - Photothermal Technique KW - Image reconstruction PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-506166 DO - https://doi.org/10.1016/j.ndteint.2020.102239 VL - 112 SP - 102239 PB - Elsevier Ltd. CY - Netherlands AN - OPUS4-50616 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Lecompagnon, Julien A1 - Hassenstein, Christian A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - New techniques in super resolution photothermal imaging for nondestructive testing N2 - In this work we focus on our most recent studies to super resolution (SR) laser thermography. The goal of SR nondestructive testing methods is to facilitate the separation of closely spaced defects. We explain how to combine laser scanning with SR techniques. It can be shown that stepwise as well as continuous scanning techniques are applicable. Finally, we discuss the effect of experimental parameters and im-age processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography. T2 - SMSI 2020 Conference CY - Online meeting DA - 22.06.2020 KW - Super resolution KW - Laser thermography KW - Nondestructive testing KW - Laser scanning KW - Photothermal imaging PY - 2020 DO - https://doi.org/10.5162/SMSI2020/C4.1 SP - 169 EP - 170 AN - OPUS4-50895 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - de Oliveira Guilherme Buzanich, Ana A1 - Radtke, Martin A1 - Yusenko, Kirill A1 - Stawski, Tomasz A1 - Kulow, Anicó A1 - Cakir, Cafer Tufan A1 - Röder, Bettina A1 - Naese, Christoph A1 - Britzke, Ralf A1 - Sintschuk, Michael A1 - Emmerling, Franziska T1 - BAMline - A real-life sample materials research beamline N2 - With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research. KW - Extended X-ray absorption fine structure KW - Energy storage KW - Environmental impacts KW - Nondestructive testing techniques KW - X-ray fluorescence spectroscopy KW - Corrosion KW - Near edge X-ray absorption fine structure spectroscopy KW - X-ray absorption spectroscopy PY - 2023 DO - https://doi.org/10.1063/5.0157194 VL - 158 IS - 24 SP - 1 EP - 22 PB - AIP Publishing AN - OPUS4-57824 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 - Hönig, Gerald A1 - Schlichting, S. A1 - Wagner, M. R. A1 - Müssener, J. A1 - Hill, P. A1 - Grieb, T. A1 - Teubert, J. A1 - Schörmann, J. A1 - Rosenauer, A. A1 - Eickhoff, M. A1 - Hoffmann, A. A1 - Callsen, G. T1 - QCSE tuning in polar GaN/AlN heterostructures N2 - We show both theoretically and experimentally how the encapsulation of the active region by additional guard layers can be used to achieve a significant reduction of the built-in electric fields in polar nitride heterostructures. This reduction of the QCSE results in a strongly enhanced emission intensity and faster recombination dynamics in the active region. In particular we are able to shift the emission energy of 4-nm-thick GaN nano-discs up to 3.32 eV, which is just 150 meV below the bulk GaN bandgap as compared to a red-shift of about 1 eV in a conventional heterostructure with the same thickness. T2 - SPIE. PHOTONICS WEST OPTO CY - San Francisco, CA, USA DA - 29.01.2018 KW - QCSE KW - Piezopolarization KW - Spontaneous Polarization KW - IFGARD KW - Nanoheterostructures KW - Nonpolar PY - 2018 AN - OPUS4-43383 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 - Thermographic Detection of Internal Defects using Photothermal Super Resolution Reconstruction and 2D structured Illumination Patterns N2 - For a long time, the rule of thumb for active thermography as a non-destructive testing method was that the resolution of internal defects/inhomogeneities is limited to a ratio of defect depth/defect size ≤ 1. This is due to the diffusive nature of thermal conduction in solids. So-called super resolution approaches have recently allowed this physical limit to be overcome many times over. This offers the attractive possibility of developing thermography from a purely near surface-sensitive testing method to one with improved depth range. How far this development can be pushed is the subject of current research. We have already been able to show that this classical limitation for one- and two-dimensional defect geometries can be overcome by illuminating the test object sequentially in a structured manner with individual laser spots and thus subsequently calculating a defect map from the resulting measurement data by applying photothermal super resolution reconstruction, which allows significantly improved separation of individual closely spaced defects. As a result, this method benefits strongly from the combination of sequential spatially structured illumination and modern numerical optimization methods, which come at the expense of higher experimental complexity. This leads to long measurement times, large data sets, and tedious numerical analysis, in contrast to the application of established standard thermographic methods with homogeneous illumination. In this work, we report on the application of full-area spatially structured two-dimensional illumination patterns, which, by applying state-of-the-art laser projector technology in conjunction with a high-power laser, makes it possible to achieve an efficient implementation of photothermal super-resolution reconstruction even for larger test areas in the first place. T2 - 13th European Conference on Non-destructive Testing CY - Lisbon, Portugal DA - 03.07.2023 KW - Thermography KW - Super resolution KW - Digital light processing KW - Material testing KW - Internal defects KW - DMD PY - 2023 AN - OPUS4-57909 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Rupprecht, Christian A1 - Ziegler, Mathias T1 - Thermographic testing using 2D pseudo-random illumination and photothermal super resolution reconstruction N2 - Due to the diffusive nature of heat propagation in solids, the detection and resolution of internal defects with active thermography based non-destructive testing is commonly limited to a defect-depth-to-defect-size ratio greater than or equal to one. In the more recent past, we have already demonstrated that this limitation can be overcome by using a spatially modulated illumination source and photothermal super resolution-based reconstruction. Furthermore, by relying on compressed sensing and computational imaging methods we were able to significantly reduce the experimental complexity to make the method viable for investigating larger regions of interest. In this work we share our progress on improving the defect/inhomogeneity characterization using fully 2D spatially structured illumination patterns instead of scanning with a single laser spot. The experimental approach is based on the repeated blind pseudo-random illumination using modern projector technology and a high-power laser. In the subsequent post-processing, several measurements are then combined by taking advantage of the joint sparsity of the defects within the sample applying 2D-photothermal super resolution reconstruction. Here, enhanced nonlinear convex optimization techniques are utilized for solving the underlying ill-determined inverse problem for typical simple defect geometries. As a result, a higher resolution defect/inhomogeneity map can be obtained at a fraction of the measurement time previously needed. T2 - Thermosense: Thermal Infrared Applications XLIV CY - Orlando, FL, USA DA - 05.04.2022 KW - Thermography KW - Super resolution KW - NDT KW - Material testing KW - Internal defects KW - DMD KW - DLP PY - 2022 AN - OPUS4-54667 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Burgholzer, P. A1 - Berer, T. A1 - Gruber, J. A1 - Mayr, G. A1 - Hendorfer, G. T1 - Thermographic super resolution using structured 1D laser illumination and joint sparsity N2 - Thermographic NDE is based on the interaction of thermal waves with inhomogeneities. These inhomogeneities are related to sample geometry or material composition. Although thermography is suitable for a wide range of inhomogeneities and materials, the fundamental limitation is the diffusive nature of thermal waves and the need to measure their effect radiometrically at the sample surface only. The propagation of the thermal waves from the heat source to the inhomogeneity and to the detection surface results in a degradation in the spatial resolution of the technique. A new concerted ansatz based on a spatially structured heating and a joint sparsity of the signal ensemble allows an improved reconstruction of inhomogeneities. As a first step to establish an improved thermographic NDE method, an experimental setup was built based on structured 1D illumination using a flash lamp behind a mechanical aperture. As a follow-up to this approach, we now use direct structured illumination using a 1D laser array. The individual emitter cells are driven by a random binary pattern and additionally shifted by fractions of the cell period. The repeated measurement of these different configurations with simultaneously constant inhomogeneity allows for a reconstruction that makes use of joint sparsity. With analytical-numerical modelling or numerical FEM simulations, we study the influence of the parameters on the result of non-linear reconstruction. For example, the influence of the illumination pattern as a variable heat flux density and Neumann boundary condition for convolution with the constant Green's function can be studied. These studies can be used to derive optimal conditions for a measurement technique. T2 - 62. International School of Quantum Electronics die Tagung “Progress in Photoacoustic & Photothermal Phenomena" CY - Erice, Italy DA - 06.09.2018 KW - Super resolution KW - Virtual wave KW - Laser thermography KW - 1d laser KW - Joint sparsity KW - Laser array KW - VCSEL array KW - High-power laser PY - 2018 AN - OPUS4-46180 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Puthiyaveettil, N. A1 - Ziegler, Mathias A1 - Myrach, Philipp A1 - Unnikrishnakurup, Sreedhar A1 - Krishnamurthy, C. V. A1 - Balasubramaniam, K. T1 - Numerical study of laser line thermography for crack detection at high temperature N2 - The detection of cracks before the failure is highly significant when it comes to safety-relevant structures. Crack detection in metallic samples at high surface temperature is one of the challenging situation in manufacturing industries. Laser thermography has already proved its detection capability of surface cracks in metallic samples at room temperature. In this work a continuous wave (CW) laser use to generate a laser, which is using to scan the metal surface with notch. The corresponding heat distribution on the surface monitored using infrared thermal (IR) camera. A simplified 3D model for laser thermography is developed and validated with experimental results. A dedicated image processing algorithm developed to improve the detectability of the cracks. To understand the dependency of surface temperature, laser power, laser scanning speed etc. in defect detection, we carried out parametric studies with our validated model. Here we report the capability of laser thermography in crack detection at elevated temperature. T2 - Conference QIRT 2018 CY - Berlin, Germany DA - 25.06.2018 KW - Thermography KW - Laser Thermography KW - Cracks PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-454441 DO - https://doi.org/10.21611/qirt.2018.076 AN - OPUS4-45444 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim T1 - Lock-in Thermography using High-Power Laser Sources N2 - Optical lock-in thermography is a completely contactless and very sensitive NDT technique. As an optical source of energy, incandescent lamps are most commonly used because they are relatively inexpensive and offer high irradiances at the test specimen. However, they are strongly restricted by their low modulation bandwidth with a maximum modulation frequency of only about 1 Hz. The use of high-power kilowatt-class laser sources, e.g. diode laser arrays, pushes this constraint beyond 100 Hz. This allows for the exploration of the near-surface region of metals and layer systems with better and more accurate penetration depth and depth resolution. Moreover, these lasers are virtually free of any additional thermal radiation that could interfere with the “true” thermal response emitted from the heated sample. In turn, they can be easily used in a one-sided test configuration. We present current activities with kilowatt-class high-power laser sources for advanced lock-in thermography and focus on the application of laser arrays that offer a very high irradiation strength over a large sample area beyond the mentioned advantages. T2 - 12th European Conference on Non-destructive Testing CY - Gothenburg, Sweden DA - 11.06.2018 KW - Thermography KW - Laser Thermography KW - Lock-in Thermography PY - 2018 AN - OPUS4-45445 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim T1 - Lock-in Thermography using High-Power Laser Sources N2 - Optical lock-in thermography is a completely contactless and very sensitive NDT technique. As an optical source of energy, incandescent (i.e. halogen) lamps are most commonly used because they are relatively inexpensive and offer high irradiances at the test site. However, they are strongly restricted by their low modulation bandwidth with a maximum modulation frequency of only about 1 Hz. The use of high-power kilowatt-class laser sources, e.g. diode laser arrays, pushes this constraint beyond 100 Hz, see Fig.1. This allows for the exploration of the near-surface region of metals and layer systems with better and more accurate penetration depth and depth resolution. Moreover, these lasers are virtually free of any additional thermal radiation that could interfere with the “true” thermal response emitted from the heated sample. In turn, they can be easily used in a one-sided test configuration. Using the one-dimensional solution to the thermal heat diffusion equation together with the absorptance of the material which is illuminated with a harmonically modulated light source, we can calculate the temperature oscillation at the surface of a solid. As a second step, we calculate the corresponding oscillation of the total thermal emission using Stefan-Boltzmann law as a first order approximation and taking into account the emissivity of the material. Within this framework we can calculate the minimal irradiance of a light source necessary to provoke a measurable signal within a thermographic camera at a noise equivalent temperature difference (NETD) of 30 mK. In Fig. 2 this relationship is displayed for a wide spectrum of modulation frequencies and for a number of different light sources scaled to the same electrical input power and illumination area. Using this figure, it is now easily possible to analyze the range of materials to be tested using lock-in thermography, since only the materials (dotted lines) below the irradiance-vs-frequency curves (solid lines) are heated in excess of the camera’s NETD. This figure clearly shows that laser sources considerably increase the application range of lock-in thermography, since especially for metals with a high reflectance and high thermal diffusivity a high irradiance is vitally important to allow for lock-in texting. We present current activities with kilowatt-class high-power laser sources for advanced lock-in thermography and focus on the application of laser arrays that offer a very high irradiation strength over a large sample area beyond the mentioned advantages. T2 - Conference QIRT 2018 CY - Berlin, Germany DA - 25.06.2018 KW - Thermography KW - Laser Thermography KW - Lock-in Thermography PY - 2018 AN - OPUS4-45449 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ziegler, Mathias A1 - Maierhofer, Christiane A1 - Krankenhagen, Rainer A1 - Röllig, Mathias T1 - Characterization of defects in fibre reinforced composites (FRC) using passive and active thermography N2 - Impact damages and delaminations in fibre-reinforced composites (FRC) might not be visible at the surface, but could have an influence on the resistance and on the long-term behaviour of the component. Therefore, and especially for safety relevant structures, non-destructive methods are required for the assessment of such damages. Active thermography methods are suitable to characterize damages after loading using different kind of excitation techniques and various configurations of infrared (IR) camera and heating sources. Here, flash lamps, impulse excitation with infrared radiator and lock-in technique with halogen lamps or widened laser beams are suited. In addition, non-optical sources like sonotrodes (requiring direct contact to the structure) or induction generators (only suited for carbon fibre reinforced polymer (CFRP) structures) could be applied as well. For the investigation of the evolution of the damage during the impact, passive thermography can be applied in-situ. Elastic and plastic deformations alter the temperature of the structure and thus the temperature on the surface. In this contribution, at first the general principles of quantitative defect characterisation in FRC using active thermography with flash, impulse and lock-in excitation are described. Optical and thermal properties of the FRC material and its anisotropy are considered. Results of phase differences obtained at flat bottom holes with flash and lock-in thermography are compared for qualifying both methods for quantitative defect characterization. Secondly, the damage evolution of CFRP and GFRP structures under impact load and static tensile loading is described. The spatial and temporal evolution of the surface temperature enables us to distinguish matrix cracks or fibre-matrix separation from delaminations between the layers. Afterwards, all results for loading defects, obtained by passive and active thermography, are compared with each other. Fig. 1 and 2 show the difference of passive and flash thermography obtained at impact and tensile loaded CFRP plates, respectively. As one purpose of these investigations is the development of standards within national (DIN) and European (CEN) standardisation bodies, new draft and final standards are presented and further needs are discussed at the end of the presentation. T2 - INTERNATIONAL SCHOOL OF QUANTUM ELECTRONICS, 62nd Course, Progress in Photoacoustic & Photothermal Phenomena CY - Erice, Italy DA - 06.09.2018 KW - Thermography KW - Flash thermography KW - Lock-in thermography KW - CFRP KW - GFRP PY - 2018 AN - OPUS4-46283 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiel, Erik A1 - Kreutzbruck, M. A1 - Studemund, T. A1 - Ziegler, Mathias T1 - Thermal wave interference with high-power VCSEL arrays for locating vertically oriented subsurface defects N2 - Among the photothermal methods, full-field thermal imaging is used to characterize materials, to determine thicknesses of layers, or to find inhomogeneities such as voids or cracks. The use of classical light sources such as flash lamps (impulse heating) or halogen lamps (modulated heating) led to a variety of nondestructive testing methods, in particular, lock-in and flash-thermography. In vertical-cavity surface-emitting lasers (VCSELs), laser light is emitted perpendicularly to the surface with a symmetrical beam profile. Due to the vertical structure, they can be arranged in large arrays of many thousands of individual lasers, which allows power scaling into the kilowatt range. Recently, a high-power yet very compact version of such a VCSEL-array became available that offers both the fast timing behavior of a laser as well as the large illumination area of a lamp. Moreover, it allows a spatial and temporal control of the heating because individual parts of the array can be controlled arbitrarily in frequency, amplitude, and phase. In conjunction with a fast infrared camera, such structured heating opens up a field of novel thermal imaging and testing methods. As a first demonstration of this approach, we chose a testing problem very challenging to conventional thermal infrared testing: The detection of very thin subsurface defects perpendicularly oriented to the surface of metallic samples. First, we generate destructively interfering thermal wave fields, which are then affected by the presence of defects within their reach. It turned out that this technique allows highly sensitive detection of subsurface defects down to depths in excess of the usual thermographic rule of thumb, with no need for a reference or surface preparation. T2 - 44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION CY - Provo, Utah DA - 16.07.2017 KW - Laser applications KW - Thermography KW - VCSEL KW - Subsurface defects PY - 2018 SN - 978-0-7354-1644-4 DO - https://doi.org/10.1063/1.5031547 SN - 0094-243X VL - 1949 SP - UNSP 060001, 1 EP - 8 AN - OPUS4-45171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Burgholzer, P. A1 - Mayr, G. T1 - Thermography using High-Power Laser Arrays N2 - Due to their high irradiance and wide modulation bandwidth, high-power lasers open up a wide field of application. For example, the classical methods of pulse and lock-in thermography can be realized in high quality. In addition, structured heating is also possible by using arrays of such lasers. This makes it possible to implement new thermographic methods, such as interference-based detection of cracks or super resolution. T2 - Fifth NDTonAIR Training Event: Thermography Workshop CY - Linz, Austria DA - 13.02.2019 KW - Thermography KW - Laser Thermography KW - Super Resolution KW - Thermal Waves KW - NDT PY - 2019 AN - OPUS4-47491 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Hirsch, Philipp Daniel A1 - Karagianni, Christina A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. T1 - A comparison of different techniques for photothermal super resolution image reconstruction N2 - The separation of two closely located defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows an improved reconstruction of closely located defects. This new technique has also been studied using 1D laser arrays in active thermography. The post-processing can be roughly described by two steps: 1. Finding a sparse basis representation using a reconstruction algorithm such as the Fourier transform, 2. Application of an iterative joint sparsity (IJOSP) method to the firstly reconstructed data. For this reason, different methods in post-processing can be compared using the same measured data set. The focus in this work was the variation of reconstruction algorithms in step 1 and its influence on the results from step 2. More precise, the measured thermal waves can be transformed to virtual (ultrasound) waves that can be processed by applying ultrasound reconstruction algorithms and finally the super resolution algorithm. Otherwise, it is also possible to make use of a Fourier transform with a subsequent super resolution routine. These super resolution thermographic image reconstruction techniques in post-processing are discussed and evaluated regarding performance, accuracy and repeatability. T2 - 20-th International Conference on Photoacoustic and Photothermal Phenomena CY - Moscow, Russia DA - 07.07.2019 KW - Super resolution KW - Virtual wave KW - Laser thermography KW - 1d laser KW - Joint sparsity KW - Laser array KW - VCSEL array KW - High-power laser KW - Fourier transform KW - Dimension reduction PY - 2019 AN - OPUS4-48592 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Hirsch, Philipp Daniel A1 - Karagianni, Christina A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. T1 - Photothermal super resolution image reconstruction using structured 1d laser illumination N2 - The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern. This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown. The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects. T2 - 46th Annual Review of Profress in Quantitative Nondestructive Evaluation CY - Portland, OR, USA DA - 14.07.2019 KW - Super resolution KW - Virtual wave KW - Laser thermography KW - 1d laser KW - Joint sparsity KW - Laser array KW - VCSEL array KW - High-power laser PY - 2019 AN - OPUS4-48591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Thiel, Erik A1 - Ziegler, Mathias T1 - Thermal wave field engineering using structured 1D laser illumination N2 - Thermal waves are solutions of the heat diffusion equation for periodic boundary conditions and can be seen analogously to strongly damped waves. Although the underlying differential equation differs from the wave equation, the essential property for analogy between both equations is linearity such that superposition applies. This linearity is maintained even after a linear transformation, such as the Fourier transform from time to frequency domain. It follows that the temporal superposition principle is already used in active thermography, e.g. in pulsed thermography, as a superposition of many individual frequencies. However, the systematic spatial superposition has not yet been fully exploited, mainly due to a lack of suitable energy sources. As a first step, we are investigating how thermal wave fields of arbitrary space-time structures can be engineered using structured laser illumination. The proof of principle was shown using a laser coupled projector. Unfortunately, the available optical output power was limited due to the thermal stress limit of the device. That is why we are working towards a more sophisticated moving 1D array of high-power diode lasers. We characterized the novel light source and believe that apart from the benefit of spatial and temporal illumination it can combine the temporal regimes of impulse and lock-in thermography. In a second step, we investigate moving and oscillating line sources with different line shapes. We use a Green’s Function ansatz to analytically model the thermal wave propagation of structured 1D laser illumination in isotropic materials. Furthermore, we show some methods how they can be implemented. With this technique, we were able to accelerate our detection method firstly presented in for vertical narrow defects by factor three. Generally, we believe that this technique opens up similar opportunities than in other NDE methods. High-resolution ultrasound, for example, is also based on the superposition of single emitters and a recent concept suggests an option to deal with the diffusion wave character of the thermal waves. T2 - 62. International School of Quantum Electronics die Tagung “Progress in Photoacoustic & Photothermal Phenomena” CY - Erice, Italy DA - 06.09.2018 KW - Thermal wave KW - Thermal wave field KW - Thermal engineering KW - Structured laser illumination KW - 1d laser KW - Laser array KW - Laser thermography PY - 2018 AN - OPUS4-46193 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thiel, Erik A1 - Ahmadi, Samim A1 - Ziegler, Mathias T1 - Two-dimensional interference of photothermally generated moving thermal waves N2 - Structured illumination using high-power diode lasers generates a two-dimensional interference of thermal waves. In addition, the sources and the sample are moving relative to each other. Using different configurations, we investigate the validity of the temporal and spatial superposition principle of the heat diffusion equation for these cases both experimentally and by numerical-analytical modelling. Furthermore, we investigate the potential of this approach for non-destructive testing. T2 - 14th Quantitative Infrared Thermography Conference CY - Berlin, Germany DA - 24.05.2018 KW - Thermography KW - Thermal Wave KW - VCSEL KW - Laser KW - Thermal diffusion PY - 2018 AN - OPUS4-45621 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ziegler, Mathias A1 - Ahmadi, Samim A1 - Thiel, Erik A1 - Krankenhagen, Rainer A1 - Maierhofer, Christiane T1 - Benefits & peculiarities of using highpower lasers for lock-in thermography N2 - Optical lock-in thermography is a completely contactless and very sensitive NDE technique. As an optical source of energy, incandescent (i.e. halogen) lamps are most commonly used because they are relatively inexpensive, do not need any work safety measures and offer high irradiances at the test site. However, they are strongly restricted by their low modulation bandwidth with a maximum modulation frequency of only about 1 Hz. The use of high-power kilowatt-class laser sources, e.g. diode laser arrays, pushes this constraint beyond 100 Hz. This allows for the exploration of the near-surface region of metals and layer systems with better and more accurate penetration depth and depth resolution. Moreover, these lasers are virtually free of any additional thermal radiation that could interfere with the “true” thermal response emitted from the heated sample. In turn, they can be easily used in a one-sided test configuration. Altogether using lasers considerably increases the application range of lock-in thermography, since especially for metals with a high reflectance and high thermal diffusivity a high irradiance is vitally important to allow for lock-in testing [1, 2]. We report on the mentioned benefits of using such high-power lasers and analyze the range of materials to be tested using lock-in thermography in dependence on the laser irradiance, the modulation frequency, the infrared camera as well as the optical and thermal material parameters. In this context, we also address a number of systematic errors caused by the use of ideal and non-ideal heat sources. For example, the measured phase angle in lock-in thermography depends on the irradiance and the modulation bandwidth of the source. This in turn has a decisive influence on the uncertainty in the quantification of, e.g. layer thicknesses. T2 - INTERNATIONAL SCHOOL OF QUANTUM ELECTRONICS, 62nd Course, Progress in Photoacoustic & Photothermal Phenomena CY - Erice, Italy DA - 06.09.2018 KW - Thermography KW - Laser thermography KW - Lock-in thermography KW - NDT PY - 2018 AN - OPUS4-46282 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Burgholzer, P. A1 - Berer, T. A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim A1 - Gruber, J. A1 - Mayr, G. A1 - Hendorfer, G. T1 - Blind structured illumination as excitation for super-resolution photothermal radiometry N2 - Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature evolution is measured at the sample’s surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. The structured illumination is realized by parallel laser lines from a vertical-cavity surface-emitting laser (VCSEL) array controlled by a random binary pattern generator. By using 150 different patterns of structured illumination and our iterative joint sparsity algorithm, it was possible to resolve 1 mm thick lines at a distance down to 0.5 mm, which results in a resolution enhancement of approximately a factor of four compared to the resolution of 5.9 mm for homogenous illuminated thermographic reconstruction. KW - Super-resolution imaging KW - Thermography KW - Blind structured illumination KW - VCSEL array PY - 2019 DO - https://doi.org/10.1080/17686733.2019.1655247 SN - 1768-6733 VL - 17 IS - 4 SP - 268 EP - 278 PB - Taylor & Francis Group CY - Milton, UK AN - OPUS4-49122 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Puthiyaveettil, N. A1 - Thomas K, R. A1 - Unnikrishnakurup, S. A1 - Myrach, Philipp A1 - Ziegler, Mathias A1 - Balasubramaniam, K. T1 - Laser line scanning thermography for surface breaking crack detection modeling and experimental study N2 - Crack detection in metallic samples at high surface temperature, hostile and hazardous environments, etc. is challenging situation in any manufacturing industries. Most of the present NDE methods are suitable only for lower surface temperatures, especially room temperature. In this situation, we need a fast and non-contact NDT method which can be applied even in high sample surface temperature. Laser thermography is one of the techniques having a high potential in non-contact inspection. As a preliminary investigation, in this article, we have studied the potentiality of laser line thermography in crack detection at room temperature. In laser line thermography, a continuous wave (CW) laser is used to generate a laser line, which in turn is used to scan the metal surface. The heat distribution over the sample surface is recorded by an infrared thermal (IR) camera. Two different approaches are reported in this work. Firstly, a stationary laser line source and its interaction with cracks; secondly, moving laser line source scanning over a surface with crack. When the distance between crack centre to laser line centre increases, crack detectability will decrease; and when laser power increases, crack detectability will increase. A dedicated image processing algorithm was developed to improve the detectability of the cracks. To understand the heat transfer phenomenon, a simplified 3D model for laser thermography was developed for the heat distribution during laser heating and was validated with experimental results. Defects were incorporated as a thermally thin resistive layer (TTRL) in numerical modeling, and the effect of TTRL in heat conduction is compared with experimental results. KW - Thermography KW - Laser Thermography KW - Cracks KW - FEM KW - NDT PY - 2019 DO - https://doi.org/10.1016/j.infrared.2019.103141 VL - 104 SP - 103141 PB - Elsevier B.V. AN - OPUS4-49941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Puthiyaveettil, N. A1 - Thomas, K. R. A1 - Myrach, Philipp A1 - Ziegler, Mathias A1 - Rajagopal, P. A1 - Balasubramaniamam, K. T1 - Defect detection in steel bars up to 600 °C using laser line thermography N2 - Crack detection in steel bars at high surface temperatures is a critical problem in any manufacturing industry. Surface breaking cracks are the major problems during the billet casting. Many NDT techniques are proven its capability in crack detection at room temperature. Here, we are demonstrating the possibility of exposure of cracks using laser line thermography at higher surface temperatures (up to 600 °C). A continuous-wave (CW) laser is used to excite the sample kept at higher surface temperatures. The temperature distribution over the sample due to the laser line scanning is captured using a temperature calibrated infrared (IR) thermal camera. The response of the sample temperature in crack detection is investigated using a validated FE model. The impact of the oxide layer in crack detection is investigated by using two types of samples; one without any oxide layer and the second is with the oxide layer. The influence of laser power in the detection of defects at high temperatures is studied. 3D numerical models were developed for the cases; when the sample is with oxide layer and without any oxide layer for a better understanding of physics. The surface temperature rise due to laser heating is higher for the scaled sample compared to the no-scale sample. The presence of the oxide layer above the parent metal will reduce the reflectivity of the surface. Lower reflectivity will lead to increased absorption of incident energy so that the surface temperature rise will be higher than the surface with no scale. Thermal contrast linearly depends on laser power, which means higher laser power will increase the defect detectability even at a higher surface temperature. KW - Laser thermography KW - High temperature KW - Modeling KW - Surface cracks KW - Non-destructive testing PY - 2020 DO - https://doi.org/10.1016/j.infrared.2020.103565 SN - 1350-4495 VL - 111 SP - 103565 PB - Elsevier B.V. AN - OPUS4-51573 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Puthiyaveettil, N. A1 - Kidangan, R. A1 - Unnikrishnakurup, Sreedhar A1 - Krishnamurthy, C. V. A1 - Ziegler, Mathias A1 - Myrach, Philipp A1 - Balasubramaniam, K. T1 - Numerical study of laser line thermography for crack detection at high temperature N2 - The detection of cracks before the failure is highly significant when it comes to safety-relevant structures. Crack detection in metallic samples at high surface temperature is one of the challenging situation in manufacturing industries. Laser thermography has already proved its detection capability of surface cracks in metallic samples at room temperature. In this work a continuous wave (CW) laser use to generate a laser, which is using to scan the metal surface with notch. The corresponding heat distribution on the surface monitored using infrared thermal (IR) camera. A simplified 3D model for laser thermography is developed and validated with experimental results. A dedicated image processing algorithm developed to improve the detectability of the cracks. To understand the dependency of surface temperature, laser power, laser scanning speed etc. in defect detection, we carried out parametric studies with our validated model. Here we Report the capability of laser thermography in crack detection at elevated temperature. T2 - 14th Quantitative InfraRed Thermography Conference CY - Berlin, Germany DA - 25.06.2018 KW - Thermal contrast KW - Laser Thermography KW - FEM KW - Surface cracks KW - NDT PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-499113 DO - https://doi.org/10.21611/qirt.2018.076 SN - 2371-4085 VL - 2018 SP - 685 EP - 686 AN - OPUS4-49911 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Burgholzer, P. A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim A1 - Gruber, J. A1 - Mayr, G. A1 - Hendorfer, G. A1 - Haltmeier, M. T1 - Blind structured illumination as excitation for super-resolution photothermal radiometry N2 - Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature increase is measured at the samples surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. T2 - Fifth NDTonAIR Training Event: Thermography Workshop CY - Linz, Austria DA - 13.02.2019 KW - Super resolution KW - Thermography KW - Laser Thermography KW - Compressed Sensing KW - NDT PY - 2019 AN - OPUS4-49912 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Thiel, Erik A1 - Karagianni, Christina A1 - Hirsch, Philipp Daniel A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Photothermal super resolution image reconstruction using structured 1D laser illumination N2 - The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern. This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown. The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects. T2 - Quantitative Nondestructive Evaluation Conference 2019 CY - Portland, OR, USA DA - 14.07.2019 KW - Super resolution KW - Photothermal KW - Thermography KW - Laser PY - 2019 SP - Paper 8593, 1 PB - ASME AN - OPUS4-50924 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Burgholzer, P. A1 - Berer, T. A1 - Ziegler, Mathias A1 - Thiel, Erik A1 - Ahmadi, Samim A1 - Gruber, J. A1 - Mayr, G. A1 - Hendorfer, G. T1 - Blind structured illumination as excitation for super-resolution photothermal radiometry N2 - The main drawback in radiometric imaging is the degradation of the spatial resolution with increasing depth, which results in blurred images for deeper lying structures. We circumvent this degradation with blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. We demonstrate this by imaging a line pattern and a star-shaped structure through a metal sheet with a resolution four times better than the width of the thermal point-spread-function. The ground-breaking concept of super-resolution can be transferred from optics to diffusive imaging by defining a thermal point-spread-function similar to the Abbe limit for a certain optical wavelength. T2 - 14th Quantitative InfraRed Thermography Conference, QIRT 2018 CY - Berlin, Germany DA - 25.06.2018 KW - Thermography KW - Laser Thermography KW - Compressed Sensing KW - Super Resolution PY - 2018 AN - OPUS4-49940 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pavasarytė, Lina A1 - Azevedo do Nascimento, Allana A1 - Cysne Barbosa, Ana Paula A1 - Trappe, Volker A1 - Melo, Daniel T1 - Effects of particle size and particle concentration of poly (ethylene-co-methacrylic acid) on properties of epoxy resin N2 - Self-healing polymers have been developed to improve durability and reduce costs associated with maintenance during service. The addition of thermoplastics to thermosets to produce mendable polymers appears as a promising selfhealing technique. In this study, poly (ethylene-co-methacrylic acid) (EMAA) was added to epoxy resin and the effects of EMAA addition on epoxy properties were evaluated. Specimens with two different contents of thermoplastic and particles sizes were manufactured. A two-level full factorial experimental design was used to evaluate the effect of particle size and particle content on properties of epoxy modified with addition of EMAA. Tensile tests and dynamic mechanical analysis (DMA) were used and the evaluated responses were tensile strength, modulus of elasticity, and glass transition temperature (Tg). X-ray computed tomography (XCT) was used to investigate particle size and concentration after manufacturing. It was found that the particle concentration has greater effects on stress–strain behavior of epoxy while Tg was not significantly affected by neither of the analyzed entrance variables. KW - Fracture KW - Self-healing KW - Epoxy KW - Thermoplastic PY - 2024 DO - https://doi.org/10.1002/app.55677 SN - 0021-8995 SP - 1 EP - 14 PB - Wiley online library AN - OPUS4-60205 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 - 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 - CONF A1 - Ziegler, Mathias A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. T1 - Thermographic super resolution reconstruction using 2D pseudo-random pattern illumination N2 - Thermographic non-destructive testing is based on the interaction of thermal waves with inhomogeneities. The propagation of thermal waves from the heat source to the inhomogeneity and to the detection surface according to the thermal diffusion equation leads to the fact that two closely spaced defects can be incorrectly detected as one defect in the measured thermogram. In order to break this spatial resolution limit (super resolution), the combination of spatially structured heating and numerical methods of compressed sensing can be used. The improvement of the spatial resolution for defect detection then depends in the classical sense directly on the number of measurements. Current practical implementations of this super resolution detection still suffer from long measurement times, since not only the achievable resolution depends on performing multiple measurements, but due to the use of single spot laser sources or laser arrays with low pixel count, also the scanning process itself is quite slow. With the application of most recent high-power digital micromirror device (DMD) based laser projector technology this issue can now be overcome. T2 - ICPPP21: International Conference on Photoacoustic and Photothermal Phenomena CY - Bled, Slovenia DA - 19.06.2022 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:b43-551224 UR - https://indico.ung.si/event/5/contributions/237/ AN - OPUS4-55122 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias ED - Zalameda, J. N. ED - Mendioroz, A. T1 - Full-frame thermographic super-resolution with 2D-structured laser heating N2 - Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination. T2 - Thermosense: Thermal Infrared Applications XLIII CY - Online meeting DA - 12.04.2021 KW - Thermography KW - super-resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 DO - https://doi.org/10.1117/12.2586093 VL - 11743 SP - 11743-26, 10 PB - SPIE AN - OPUS4-52524 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias T1 - 2D-Photothermal Super Resolution with Sparse Matrix Stacking N2 - Thermographic super resolution techniques allow the spatial resolution of defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. In this work, we report on the extension of this approach towards a full frame 2D super resolution technique. The approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample T2 - Sensor and Measurement Science International Conference SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Thermography KW - Super-resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 SN - 978-3-9819376-4-0 DO - https://doi.org/10.5162/SMSI2021/C2.2 VL - SMSI 2021 - Sensors and Instrumentation SP - 183 EP - 184 AN - OPUS4-52589 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias T1 - Full-frame thermographic super-resolution with 2D-structured laser heating N2 - Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination. T2 - Thermosense: Thermal Infrared Applications XLIII CY - Online meeting DA - 12.04.2021 KW - Thermography KW - Super-resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11743/117430T/Full-frame-thermographic-super-resolution-with-2D-structured-laser-heating/10.1117/12.2586093.full AN - OPUS4-52526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Burgholzer, Peter A1 - Jung, Peter A1 - Caire, Giuseppe A1 - Ziegler, Mathias T1 - Laser excited super resolution thermal imaging for nondestructive testing N2 - The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography. T2 - Sensor and Measurement Science International Conference SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Super resolution KW - Laser thermography KW - Nondestructive testing KW - Laser scanning KW - Photothermal imaging PY - 2021 SP - 181 EP - 182 AN - OPUS4-52780 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias T1 - 2D-Photothermal super-resolution with sparse matrix stacking N2 - Thermographic super resolution techniques allow the spatial resolution of defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. In this work, we re-port on the extension of this approach towards a full frame 2D super resolution technique. The approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. T2 - Sensor and Measurement Science International Conference SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Thermography KW - Super-resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 AN - OPUS4-52579 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias ED - Kimata, M. ED - Shaw, J. A. ED - Valenta, C. R. T1 - Investigations on photothermal super resolution reconstruction using 2D-structured illumination patterns N2 - Active thermography as a nondestructive testing modality suffers greatly from the limitations imposed by the diffusive nature of heat conduction in solids. As a rule of thumb, the detection and resolution of internal defects/inhomogeneities is limited to a defect depth to defect size ratio greater than or equal to one. Earlier, we demonstrated that this classical limit can be overcome for 1D and 2D defect geometries by using photothermal laser-scanning super resolution. In this work we report a new experimental approach using 2D spatially structured illumination patterns in conjunction with compressed sensing and computational imaging methods to significantly decrease the experimental complexity and make the method viable for investigating larger regions of interest. T2 - Future Sensing Technologies Conference 2021 CY - Online meeting DA - 15.11.2021 KW - Thermography KW - Super resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 DO - https://doi.org/10.1117/12.2603838 VL - 11914 SP - 124 EP - 131 PB - International Society for Optics and Photonics. SPIE AN - OPUS4-53745 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Paul, A. A1 - Ziegler, Mathias T1 - Pulse-compression laser thermography using a modified Barker code: Enhanced detection of subsurface defects N2 - Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm. T2 - SPIE Defense + Commercial Sensing 2021 CY - Online meeting DA - 13.04.2021 KW - Pulse-compression laser thermography KW - Barker codes KW - Non-destructive testing PY - 2021 DO - https://doi.org/10.1117/12.2586078 SN - 0277-786X VL - 11743 SP - 1 EP - 11 PB - SPIE CY - Bellingham, Wash. AN - OPUS4-53247 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Ziegler, Mathias T1 - Surface breaking crack detection algorithm for flying spot and line thermography based on the Canny approach N2 - In this work we introduce an algorithm based on the well-known Canny approach for effectual crack detection in thermographic films obtained using flying spot thermography (FST) or flying line thermography (FLT). The proposed algorithm performs faster than another algorithm, for crack detection, based on the application of two Sobel filters (one in x and another one in y directions). For FLT it is shown that processing 10-25 % of the thermograms of a thermographic film required to scan a whole sample is enough to obtain good results. In contrast, using the Sobel filter approach requires the processing of twice the thermographic film length. Experimental measurements are performed on a metallic component of complex shape which contains real defects, that is, surface breaking cracks due to industrial use. The specimen is tested using flying line thermography. Three different scanning speeds are tested: 10, 30 and 60 mms-1 with laser powers of 50, 60 and 120 W respectively. The sample and an infrared camera are aligned and fixed on a motorized linear stage. The diode laser LDM500 (500 W max power) is fixed on an optical bench separately from the linear stage. The results obtained with the proposed algorithm are additionally compared with a previously established algorithm for flying spot thermography based on the Sobel filter. It is shown that the proposed algorithm based on the Canny approach, can be used in automated systems for thermographic non-destructive testing. T2 - SPIE Future Sensing Technologies 2021 CY - Online meeting DA - 14.11.2021 KW - Flying line thermography KW - Flying spot thermography KW - Canny approach KW - automated thermographic nondestructive testing PY - 2021 DO - https://doi.org/10.1117/12.2603913 SP - 119140M-1 EP - 119140M-6 AN - OPUS4-53961 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Paul, A. A1 - Ziegler, Mathias T1 - Pulse-compression laser thermography using a modified Barker code: Enhanced detection of subsurface defects N2 - Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm. T2 - SPIE Defense + Commercial Sensing 2021 CY - Online meeting DA - 13.04.2021 KW - Pulse-compression laser thermography KW - Barker codes KW - Non-destructive testing PY - 2021 AN - OPUS4-53249 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim A1 - Lecompagnon, Julien A1 - Hirsch, Philipp Daniel A1 - Burgholzer, Peter A1 - Jung, Peter A1 - Caire, Giuseppe A1 - Ziegler, Mathias T1 - Laser excited super resolution thermal imaging for nondestructive testing N2 - The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography. T2 - Sensor and Measurement Science International Conference SMSI 2021 CY - Online meeting DA - 03.05.2021 KW - Super resolution KW - Laser thermography KW - Nondestructive testing KW - Laser scanning KW - Photothermal imaging PY - 2021 AN - OPUS4-52781 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 - Influence of the number of measurements on detecting internal defects using photothermal super resolution reconstruction with random pixel patterns N2 - In this work, the limits of using spatially structured heating combined with subsequent photothermal super resolution reconstruction for the thermographic detection and resolution of internal defects are investigated. The approach is based on the application of modern high-power laser projector technology, which is used to repeatedly project varying spatially structured 2D pixel patterns to photothermally heat the object under test. After processing the generated thermographic data using nonlinear convex optimisation in conjunction with exploiting the joint-sparse nature of the defect signals within the individual measurements, a high-resolution 2D-sparse defect/inhomogeneity map is obtained. The main focus of the investigation is set on the influence of the number of individual measurements on the achievable reconstruction quality. Using numerical simulations based on an analytical representation of the forward solution to the underlying inverse problem, the convergence rate over performed measurements of the achievable reconstruction quality is determined. Finally, all findings are experimentally validated by reconstructing a set of internal defects in an additively manufactured sample. In this work, it is shown that for a variety of different defect separation distances, the projection of 50 different pixel patterns allows for a good trade-off between experimental complexity and reconstruction quality. KW - Super resolution KW - Digital micromirror device KW - Digital light processing KW - Internal defects PY - 2023 DO - https://doi.org/10.1080/17686733.2023.2223392 SN - 2116-7176 SP - 1 EP - 11 PB - Taylor & Francis AN - OPUS4-57778 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 - Mendioroz, A. ED - Avdelidis, N. P. T1 - Thermographic testing using 2D pseudo-random illumination and photothermal super resolution reconstruction N2 - Due to the diffusive nature of heat propagation in solids, the detection and resolution of internal defects with active thermography based non-destructive testing is commonly limited to a defect-depth-to-defect-size ratio greater than or equal to one. In the more recent past, we have already demonstrated that this limitation can be overcome by using a spatially modulated illumination source and photothermal super resolution-based reconstruction. Furthermore, by relying on compressed sensing and computational imaging methods we were able to significantly reduce the experimental complexity to make the method viable for investigating larger regions of interest. In this work we share our progress on improving the defect/inhomogeneity characterization using fully 2D spatially structured illumination patterns instead of scanning with a single laser spot. The experimental approach is based on the repeated blind pseudo-random illumination using modern projector technology and a high-power laser. In the subsequent post-processing, several measurements are then combined by taking advantage of the joint sparsity of the defects within the sample applying 2D-photothermal super resolution reconstruction. Here, enhanced nonlinear convex optimization techniques are utilized for solving the underlying ill-determined inverse problem for typical simple defect geometries. As a result, a higher resolution defect/inhomogeneity map can be obtained at a fraction of the measurement time previously needed. T2 - Thermosense: Thermal Infrared Applications XLIV CY - Orlando, Florida, USA DA - 05.04.2022 KW - Thermography KW - Super resolution KW - NDT KW - Material testing KW - Internal defects KW - DMD KW - DLP PY - 2022 DO - https://doi.org/10.1117/12.2618562 SN - 0277-786X VL - 12109 SP - 1 EP - 10 PB - SPIE AN - OPUS4-54909 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 - Overcoming the Spatial Resolution Limits imposed by the Thermal MTF with Thermographic Photothermal Super Resolution Reconstruction N2 - The achievable spatial resolution of active thermographic testing is inherently limited by the diffusive nature of heat conduction in solids. This degradation of the achievable spatial resolution for a semi-infinite body acting on a defect signal can be approximated by spatial convolution with the Green’s function of the heat PDE. As the degradation in spatial resolution is dependent on the depth 𝐿, a common rule of thumb specifies that for proper detection, any defect should feature a spatial extension greater or equal to the depth it is located at. However, as the exact shape of a defect can have a large impact on its severity, at best a proper reconstruction of the defect shape should be performed, which therefore must also deal with the aforementioned adverse effects of heat conduction. One recent method to overcome the spatial resolution limit of thermographic testing is the photothermal super resolution reconstruction method. It is based on performing multiple active thermographic measurements on the same region of interest (ROI) with varying spatially structured heating and subsequent numerical reconstruction of the measured defect signals by solving a severely ill-posed inverse reconstruction problem relying on heavy regularization. By extending the experimental implementation of the method to make use of random-pixel patterns projected onto the ROI using a laser-coupled DLP-projector, defect reconstructions can now be performed within a reasonable time frame (~15 min per ROI) at high accuracy. Compared to conventional thermographic testing methods, the photothermal super resolution reconstruction stands out by resulting in a sparse representation of the defect structure of the ROI, making it especially well-suited to further automatic defect classification and quality assurance measures in an Industry 4.0 context. T2 - INTERNATIONAL SCHOOL OF QUANTUM ELECTRONICS: 67th Course: Progress in Photoacoustic & Photothermal Phenomena CY - Erice, Italy DA - 24.09.2023 KW - Thermography KW - Super resolution KW - NDT KW - Internal defects KW - DLP PY - 2023 AN - OPUS4-58472 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 - 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 AN - OPUS4-55262 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Hirsch, Philipp Daniel A1 - Lecompagnon, Julien A1 - Ziegler, Mathias T1 - Robot-assisted laser thermography - Towards automatic characterization of surface defects N2 - By means of laser thermography, surface defects, in particular surface breaking cracks, can be detected with high sensitivity. Basically, this requires a focused heat source (high-power laser), a thermographic camera and a relative movement between laser and test object, as well as a suitable evaluation algorithm to distinguish between surface defects and defect-free areas. In this paper we report on a method in which the relative motion is realised by a robot to fully inspect large and non-planar test objects such as rail sections, turbine blades, gears, etc. We show the influence of the excitation laser, which can be varied in terms of spot geometry, wavelength, and scan scheme, and we demonstrate our evaluation algorithms with the aim of automatically detecting surface defects. T2 - 16th Quantitative Infrared Thermography Conference CY - Paris, France DA - 04.07.2022 KW - Flying line thermography KW - Surface breaking defects KW - Robot-assisted thermography PY - 2022 AN - OPUS4-55560 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Hirsch, Philipp Daniel A1 - Lecompagnon, Julien A1 - Ziegler, Mathias T1 - Robot-assisted laser thermography for surface breaking crack detection on complex shaped components N2 - Laser thermography using a focused (spot or line) beam has proved to be effective for detection of surface breaking cracks on planar samples. In this work, we use the same principle, but applied to complex shaped components, like a rail cross-section, a gear, and a gas turbine blade. We use a six-axis robot to move the sample in-front of our thermographic setup. Several scanning-path and thermographic parameters are explored: scanning speed, density of points in each scanning slice, laser power, camera framerate. Additionally, we explore semi-automatic evaluation algorithms for crack detection, as well as 2D-to-3D registration of the found indications. T2 - SPIE Future Sensing Technologies 2023 CY - Yokohama, Japan DA - 18.04.2023 KW - Flying line thermography KW - Crack-detection algorithms PY - 2023 UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12327/1232715/Robot-assisted-infrared-thermography-for-surface-breaking-crack-detection-on/10.1117/12.2666757.short AN - OPUS4-57594 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pech May, Nelson Wilbur A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias T1 - Automatic inspection of surface breaking cracks using laser scanning thermography N2 - In this work, we report on a method for automatic inspection of components using laser scanning thermography, in which the relative motion is performed by a robot to fully inspect complex test objects such as turbine blades. We demonstrate our evaluation algorithms with the aim of automatically detecting surface defects on calibrated specimens. We show the influence of the excitation laser, which can be varied in terms of spot geometry, wavelength, and scan scheme. Additionally, we show some advantages, versatility, and current challenges of using a programmed robot for non-destructive evaluation in thermography. T2 - International Conference in Photoacoustics and Photothermal Phenomena (ICPPP21) CY - Bled, Slovenia DA - 19.06.2022 KW - Flying line thermography KW - Surface breaking defects KW - Canny approach PY - 2022 AN - OPUS4-55386 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 - Kästner, L. A1 - Ahmadi, Samim A1 - Jonietz, Florian A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias A1 - Lambrecht, J. T1 - Classification of Spot-Welded Joints in Laser Thermography Data Using Convolutional Neural Networks N2 - Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this article, we propose an approach for quality inspection of spot weldings using images from laser thermography data. We propose data preparation approaches based on the underlying physics of spot-welded joints, heated with pulsed laser thermography by analyzing the intensity over time and derive dedicated data filters to generate training datasets. Subsequently, we utilize convolutional neural networks to classify weld quality and compare the performance of different models against each other. We achieve competitive results in terms of classifying the different welding quality classes compared to traditional approaches, reaching an accuracy of more than 95 percent. Finally, we explore the effect of different augmentation methods. KW - Active thermal imaging KW - Laser thermography KW - Spot-welded joints KW - Convolutional neural network KW - Classification KW - Data processing PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-524216 DO - https://doi.org/10.1109/ACCESS.2021.3063672 VL - 9 SP - 48303 EP - 48312 AN - OPUS4-52421 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pech May, Nelson Wilbur A1 - Ziegler, Mathias T1 - Detection of surface breaking cracks using flying line laser thermography: A Canny-based algorithm N2 - In this work, we introduce a new algorithm for effectual crack detection using flying line laser thermography, based on the well-known Canny approach. The algorithm transforms the input thermographic sequence into an edge map. Experimental measurements are performed on a metallic component that contains surface breaking cracks due to industrial use. The specimen is tested using flying line thermography at different scanning speeds and laser input powers. Results obtained with the proposed algorithm are additionally compared with a previously established algorithm for flying spot thermography. The proposed Canny-based algorithm can be used in automated systems for thermographic non-destructive testing. T2 - Advanced Infrared Technology and Applications 2021 CY - Online meeting DA - 26.10.2021 KW - Canny approach KW - Flying line thermography KW - Crack detection PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539628 DO - https://doi.org/10.3390/engproc2021008022 SN - 2673-4591 VL - 8 IS - 1 SP - 1 EP - 4 PB - MDPI CY - Basel AN - OPUS4-53962 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Breese, Philipp Peter A1 - Becker, Tina A1 - Heinrichsdorff, F. A1 - Altenburg, Simon T1 - From Thermographic In-situ Monitoring to Porosity Detection – A Deep Learning Framework for Quality Control in Laser Powder Bed Fusion N2 - In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk. T2 - SMSI - Sensor and Measurement Science International 2023 CY - Nürnberg, Germany DA - 08.05.2023 KW - Porosity KW - Laser powder bed fusion KW - In-situ monitoring KW - Thermography KW - Machine Learning PY - 2023 UR - https://www.ama-science.org/proceedings/details/4404 DO - https://doi.org/10.5162/SMSI2023/C5.4 SP - 179 EP - 180 AN - OPUS4-57616 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Becker, Tina A1 - Breese, Philipp Peter A1 - Scheuschner, Nils A1 - Maierhofer, Christiane A1 - Ulbricht, Alexander A1 - Frisch, Tobias A1 - Mohr, Gunther A1 - Altenburg, Simon T1 - Defect prediction in laser powder bed fusion based on thermographic features utilizing convolutional neural networks N2 - The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived. T2 - GIMC SIMAI YOUNG 2022 CY - Pavia, Italy DA - 29.09.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Convolutional Neural Networks PY - 2022 AN - OPUS4-56331 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Becker, Tina A1 - Breese, Philipp Peter A1 - Scheuschner, Nils A1 - Maierhofer, Christiane A1 - Ulbricht, Alexander A1 - Fritsch, Tobias A1 - Mohr, Gunther A1 - Altenburg, Simon T1 - Defect prediction on the Base of Thermographic features in Laser Powder Bed Fusion Utilizing Machine Learning Algorithms N2 - Avoiding the formation of defects such as keyhole pores is a major challenge for the production of metal parts by Laser Powder Bed Fusion (LPBF). The use of in-situ monitoring by thermographic cameras is a promising approach to detect defects, however the data is hard to analyze by conventional algorithms. Therefore, we investigate the use of Machine Learning (ML) in this study, as it is a suitable tool to model complex processes with many influencing factors. A ML model for defect prediction is created based on features extracted from process thermograms. The porosity information calculated from an x-ray Micro Computed Tomography (µCT) scan is used as reference. Physical characteristics of the keyhole pore formation are incorporated into the model to increase the prediction accuracy. Based on the prediction result, the quality of the input data is inferred and future demands on in-situ monitoring of LPBF processes are derived. T2 - Additive Manufacturing Benchmarks 2022 CY - Bethesda, MA, USA DA - 14.08.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Machine Learning KW - Defect prediction PY - 2022 AN - OPUS4-55591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Becker, Tina A1 - Breese, Philipp Peter A1 - Scheuschner, Nils A1 - Altenburg, Simon T1 - Machine Learning based defect detection in Laser Powder Bed Fusion utilizing thermographic feature data N2 - The formation of irregularities such as keyhole porosity pose a major challenge to the manufacturing of metal parts by laser powder bed fusion (PBF-LB/M). In-situ thermography as a process monitoring technique shows promising potential in this manner since it is able to extract the thermal history of the part which is closely related to the formation of irregularities. In this study, we investigate the utilization of machine learning algorithms to detect keyhole porosity on the base of thermographic features. Here, as a referential technique, x-ray micro computed tomography is utilized to determine the part's porosity. An enhanced preprocessing workflow inspired by the physics of the keyhole irregularity formation is presented in combination with a customized model architecture. Furthermore, experiments were performed to clarify the role of important parameters of the preprocessing workflow for the task of defect detection . Based on the results, future demands on irregularity prediction in PBF-LB/M are derived. T2 - International Conference on NDE 4.0 CY - Berlin, Germany DA - 24.10.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Convolutional Neural Networks PY - 2022 AN - OPUS4-56332 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Breese, Philipp Peter A1 - Ulbricht, Alexander A1 - Mohr, Gunther A1 - Altenburg, Simon T1 - A deep learning framework for defect prediction based on thermographic in-situmonitoring in laser powder bed fusion N2 - The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers. Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity. KW - Laser Powder Bed Fusion (PBF-LB/M, L-PBF) KW - Selective Laser Melting (SLM) KW - SWIR thermography KW - Online monitoring KW - Flaw detection KW - Machine learning KW - Convolutional neural networks (CNN) PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-575148 DO - https://doi.org/10.1007/s10845-023-02117-0 SN - 0956-5515 SP - 1 EP - 20 PB - Springer AN - OPUS4-57514 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maierhofer, Christiane A1 - Thiel, Erik A1 - Altenburg, Simon A1 - Mohr, Gunther A1 - Thiede, Tobias A1 - Mishurova, Tatiana A1 - Paul, Andrea A1 - Kranzmann, Axel A1 - Hilgenberg, Kai A1 - Pittner, Andreas A1 - Bruno, Giovanni A1 - Sommer, Konstantin A1 - Gumenyuk, Andrey T1 - Quality control in additive manufacturing via in-situ monitoring and non-destructive testing N2 - More than 80 representatives of SMEs, industrial companies and research institutes met on September 12 at the workshop "Challenges in Additive Manufacturing: Innovative Materials and Quality Control" at BAM in Adlershof to discuss the latest developments in materials and quality control in additive manufacturing. In special lectures, researchers, users and equipment manufacturers reported on the latest and future developments in additive manufacturing. Furthermore, funding opportunities for projects between SMEs and research institutions on a national and European level were presented. T2 - Challenges in Additive Manufacturing: Innovative Materials and Quality Control CY - Berlin, Germany DA - 12.09.2018 KW - Additive manufacturing KW - Quality control KW - Non-destructive testing KW - In-situ monitoring PY - 2018 AN - OPUS4-46072 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, G. T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser powder bed fusion (PBF-LB/M, L-PBF) KW - Selective laser melting KW - Thermography KW - Machine learning PY - 2023 DO - https://doi.org/10.1515/teme-2023-0062 SN - 0171-8096 SN - 2196-7113 VL - 90 SP - 85 EP - 96 PB - De Gruyter CY - Berlin AN - OPUS4-58366 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pelkner, Matthias A1 - Stegemann, Robert A1 - Sonntag, Nadja A1 - Pohl, Rainer A1 - Kreutzbruck, Marc T1 - Benefits of GMR sensors for high spatial resolution NDT applications N2 - Magneto resistance sensors like GMR (giant magneto resistance) or TMR (tunnel magneto resistance) are widely used in industrial applications, examples are position measurement and read heads of hard disk drives. However, in case of non-destructive testing (NDT) applications these sensors, although their properties are outstanding like high spatial resolution, high field sensitivity, low cost and low energy consumption, never reached a technical transfer to an application beyond sci-entific scope. This paper deals with benefits of GMR/TMR sensors in terms of high spatial resolution testing for different NDT applica-tions. The first example demonstrates the preeminent advantages of MR-elements compared with conventional coils used in eddy current testing (ET). The probe comprises one-wire excitation with an array of MR elements. This led to a better spatial resolution in terms of neighboring defects. The second section concentrates on MFL-testing (magnetic flux leakage) with active field excitation during and before test-ing. The latter illustrated the capability of highly resolved crack detection of a crossed notch. This example is best suited to show the ability of tiny magnetic field sensors for magnetic material characterization of a sample surface. Another example is based on characterization of samples after tensile test. Here, no external field is applied. The magnetization is only changed due to external load and magnetostriction leading to a field signature which GMR sensors can resolve. This gives access to internal changes of the magnetization state of the sample under test. T2 - QNDE 2017 CY - Provo, Utah, USA DA - 16.07.2017 KW - GMR KW - Non-destructive testing KW - Sensor arrays KW - Spatial resolution PY - 2018 SN - 978-0-7354-1644-4 DO - https://doi.org/10.1063/1.5031535 SN - 0094-243X VL - 1949 SP - UNSP 040001, 1 EP - 10 AN - OPUS4-45050 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, Gerald T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in PBF-LB/M N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg im Breisgau, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser Powder Bed Fusion (PBF-LB/M, L-PBF) KW - Selective Laser Melting KW - Thermography KW - Machine Learning PY - 2023 AN - OPUS4-59192 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Breese, Philipp Peter A1 - Becker, Tina A1 - Heinrichsdorff, F. A1 - Altenburg, Simon T1 - From Thermographic In-situ Monitoring to Porosity Detection – A Deep Learning Framework for Quality Control in Laser Powder Bed Fusion N2 - In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk. T2 - Sensor and Measurement Science International CY - Nurnberg, Germany DA - 08.05.2023 KW - Laser powder bed fusion KW - In-situ monitoring KW - Thermography KW - Machine Learning KW - Porosity PY - 2023 AN - OPUS4-57614 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -