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 - 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 - 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 - 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 - JOUR A1 - Ahmadi, Samim A1 - Kästner, L. A1 - Hauffen, Jan Christian A1 - Jung, P. A1 - Ziegler, Mathias T1 - Photothermal-SR-Net: A customized deep unfolding neural network for photothermal super resolution imaging N2 - This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step. KW - Deep unfolding KW - Defect reconstruction KW - Elastic net KW - Inverse problems KW - Iterative shrinkage thresholding KW - Neural network KW - Nondestructive testing (NDT) KW - Photothermal imaging KW - Super resolution (SR) KW - Thermography PY - 2022 DO - https://doi.org/10.1109/tim.2022.3154803 SN - 1557-9662 VL - 71 SP - 1 EP - 9 PB - IEEE AN - OPUS4-54678 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hauffen, J. C. A1 - Kästner, L. A1 - Ahmadi, Samim A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging N2 - Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging. KW - Thermography KW - Laser KW - Machine learning KW - Optimization KW - Non-destructive testing KW - NDT KW - Neural network KW - Defect reconstruction KW - Block-sparsity KW - Active thermal imaging KW - Regularization KW - Laser thermography PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554598 DO - https://doi.org/10.3390/s22155533 SN - 1424-8220 VL - 22 IS - 15 SP - 1 EP - 15 PB - MDPI CY - Basel AN - OPUS4-55459 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lecompagnon, Julien A1 - Ahmadi, Samim A1 - Hirsch, Philipp Daniel A1 - Rupprecht, C. A1 - Ziegler, Mathias T1 - Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating N2 - Thermographic photothermal super resolution reconstruction enables the resolution of internal defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. Based on a combination of the application of special sampling strategies and a subsequent numerical optimization step in post-processing, thermographic super resolution has already proven to be superior to standard thermographic methods in the detection of one-dimensional defect/inhomogeneity structures. In our work, we report an extension of the capabilities of the method for efficient detection and resolution of defect cross sections with fully two-dimensional structured laser-based heating. The reconstruction is carried out using one of two different algorithms that are proposed within this work. Both algorithms utilize the combination of several coherent measurements using convex optimization and exploit the sparse nature of defects/inhomogeneities as is typical for most nondestructive testing scenarios. Finally, the performance of each algorithm is rated on reconstruction quality and algorithmic complexity. The presented experimental approach is based on repeated spatially structured heating by a high power laser. As a result, a two-dimensional sparse defect/inhomogeneity map can be obtained. In addition, the obtained results are compared with those of conventional thermographic inspection methods that make use of homogeneous illumination. Due to the sparse nature of the reconstructed defect/inhomogeneity map, this comparison is performed qualitatively. KW - Thermography KW - Super resolution KW - NDT KW - Inspection KW - Internal defects PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-548351 DO - https://doi.org/10.1063/5.0088102 SN - 1089-7550 VL - 131 IS - 18 SP - 1 EP - 12 PB - AIP Publishing AN - OPUS4-54835 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - 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 kilowattclass 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 highpower 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 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-454466 UR - http://cdn.ecndt2018.com/wp-content/uploads/2018/05/ecndt-0139-2018.pdf SN - 978-91-639-6217-2 SP - ECNDT-0139-2018,1 EP - 7 AN - OPUS4-45446 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 - Using an infrared camera for radiometric imaging allows the contactless temperature measurement of multiple surface pixels simultaneously. From the measured surface data, a sub-surface structure, embedded inside a sample or tissue, can be reconstructed and imaged when heated by an excitation light pulse. 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. The ground-breaking concept of super-resolution can be transferred from optics to thermographic imaging. T2 - Conference QIRT 2018 CY - Berlin, Germany DA - 25.06.2018 KW - Thermography KW - Laser thermography KW - Super resolution PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-454506 SN - 978-3-940283-94-8 DO - https://doi.org/10.1080/17686733.2019.1655247 SP - We.3.A.2, 1 EP - 7 AN - OPUS4-45450 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 - 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 -