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 - 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 - 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 - 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 - Ahmadi, Samim 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 - CONF A1 - Ahmadi, Samim T1 - Neue Verfahren der thermografischen Super Resolution mit strukturierter 1D-Lasererwärmung N2 - Die thermografische ZfP basiert auf der Wechselwirkung von thermischen Wellen mit Inhomogenitäten. Die Ausbreitung von thermischen Wellen von der Wärmequelle zur Inhomogenität und zur Detektionsoberfläche entsprechend der thermischen Diffusionsgleichung führt dazu, dass zwei eng beieinander liegende Defekte fälschlicherweise als ein Defekt im gemessenen Thermogramm erkannt werden können. Um diese räumliche Auflösungsgrenze zu durchbrechen, also eine Super Resolution zu realisieren, kann die Kombination von räumlich strukturierter Erwärmung und numerischen Verfahren des Compressed Sensings verwendet werden. Für unsere Arbeiten benutzen wir Hochleistungs-Laser im Kilowatt-Bereich um die Probe entweder hochaufgelöst entlang einer Linie (1D) abzurastern oder strukturiert zu erwärmen. Die Verbesserung des räumlichen Auflösungsvermögens zur Defekterkennung hängt dann im klassischen Sinne direkt von der Anzahl der Messungen ab. Mithilfe des Compressed Sensings und Vorkenntnissen über das System ist es jedoch möglich die Anzahl der Messungen zu reduzieren und trotzdem Super Resolution zu erzielen. Wie viele Messungen notwendig sind und wie groß der Auflösungsgewinn gegenüber der konventionellen thermografischen Prüfung mit flächiger Erwärmung ist, hängt von einer Reihe von Messparametern, der Messstrategie, Probeneigenschaften und den verwendeten Rekonstruktionsalgorithmen ab. Unsere Studien befassen sich mit dem Einfluss der experimentellen Parameter, wie z.B. der Pulslänge der Laserbeleuchtung und der Größe des Laserspots. Weiterhin haben wir uns mit der Wahl der Parameter in der Rekonstruktion auseinandergesetzt, die einen Einfluss auf das im Compressed Sensing zugrundeliegende Minimierungsproblem haben. Für jeden getesteten Parametersatz wurde eine Rekonstruktionsqualität berechnet. Schließlich wurden die Defektrekonstruktionen basierend auf den Parameternsätzen verglichen, sodass eine Parameterwahl für hohe Rekonstruktionsqualitäten mit thermografischer Super Resolution empfohlen werden kann. T2 - DGZfP-Jahrestagung 2021 CY - Online meeting DA - 10.05.2021 KW - Super resolution KW - Thermografie KW - Strukturiert KW - Photothermisch PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527820 AN - OPUS4-52782 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ahmadi, Samim T1 - Neue Verfahren der thermografischen Super Resolution mit strukturierter 1D-Lasererwärmung N2 - Die thermografische ZfP basiert auf der Wechselwirkung von thermischen Wellen mit Inhomogenitäten. Die Ausbreitung von thermischen Wellen von der Wärmequelle zur Inhomogenität und zur Detektionsoberfläche entsprechend der thermischen Diffusionsgleichung führt dazu, dass zwei eng beieinander liegende Defekte fälschlicherweise als ein Defekt im gemessenen Thermogramm erkannt werden können. Um diese räumliche Auflösungsgrenze zu durchbrechen, also eine Super Resolution zu realisieren, kann die Kombination von räumlich strukturierter Erwärmung und numerischen Verfahren des Compressed Sensings verwendet werden. Für unsere Arbeiten benutzen wir Hochleistungs-Laser im Kilowatt-Bereich um die Probe entweder hochaufgelöst entlang einer Linie (1D) abzurastern oder strukturiert zu erwärmen. Die Verbesserung des räumlichen Auflösungsvermögens zur Defekterkennung hängt dann im klassischen Sinne direkt von der Anzahl der Messungen ab. Mithilfe des Compressed Sensings und Vorkenntnissen über das System ist es jedoch möglich die Anzahl der Messungen zu reduzieren und trotzdem Super Resolution zu erzielen. Wie viele Messungen notwendig sind und wie groß der Auflösungsgewinn gegenüber der konventionellen thermografischen Prüfung mit flächiger Erwärmung ist, hängt von einer Reihe von Messparametern, der Messstrategie, Probeneigenschaften und den verwendeten Rekonstruktionsalgorithmen ab. Unsere Studien befassen sich mit dem Einfluss der experimentellen Parameter, wie z.B. der Pulslänge der Laserbeleuchtung und der Größe des Laserspots. Weiterhin haben wir uns mit der Wahl der Parameter in der Rekonstruktion auseinandergesetzt, die einen Einfluss auf das im Compressed Sensing zugrundeliegende Minimierungsproblem haben. Für jeden getesteten Parametersatz wurde eine Rekonstruktionsqualität berechnet. Schließlich wurden die Defektrekonstruktionen basierend auf den Parameternsätzen verglichen, sodass eine Parameterwahl für hohe Rekonstruktionsqualitäten mit thermografischer Super Resolution empfohlen werden kann. T2 - DGZfP-Jahrestagung 2021 CY - Online meeting DA - 10.05.2021 KW - Super resolution KW - Laserthermografie KW - Strukturiertes Heizen KW - Photothermisch PY - 2021 AN - OPUS4-52783 LA - deu 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 - 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 - 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 - 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 - Ahmadi, Samim 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 - Ahmadi, Samim 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 - Ahmadi, Samim T1 - Thermal Super Resolution Image Reconstruction Using Structured Laser Heating 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. 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 - 7th Autumn School METTI (Thermal Measurements and Inverse Techniques) CY - Porquerolles Island, Hyères, France DA - 29.09.2019 KW - Super resolution KW - Virtual wave KW - Laser thermography KW - VCSEL array KW - Joint sparsity KW - Compressed sensing PY - 2019 AN - OPUS4-49881 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -