TY - CONF A1 - Chaudhuri, Somsubhro T1 - WTB-IRT: Modelling and Measurement of Thermal Contrast in wind turbine rotor blades (WTBs) N2 - To understand the results that can be obtained with thermography of operational wind turbine blades, a climate chamber based experiment was performed. The results of these experiments were additionally modelled using COMSOL Multiphysics. The results have been presented at the conference. T2 - Advanced Infrared Technology and Applications (AITA) 2025 CY - Kobe, Japan DA - 15.09.2025 KW - Thermography KW - Thermografie KW - Wind turbine rotor blades KW - Windenergie Anlage Rotorblätter KW - FEA PY - 2025 AN - OPUS4-64222 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Chaudhuri, Somsubhro A1 - Krankenhagen, Rainer A1 - Lapšanská, Ivana A1 - Stamm, Michael T1 - WTB-IRT: Modelling and Measurement of Thermal Contrast in Wind Turbine Rotor Blades (WTBs) N2 - The rapid growth of wind energy infrastructure over the past two to three decades has led to an urgent need for advanced non-destructive testing (NDT) methods—both for newly installed wind turbine blades (WTBs) and for ageing components nearing the end of their service life. Among emerging techniques, passive infrared thermography (IRT) offers a promising solution by enabling contactless, time-efficient inspection based on naturally occurring thermal variations. The effectiveness of passive IRT depends on the presence of sufficient thermal contrast to distinguish surface features, subsurface structures, and defects. To better understand the possibility of obtaining such contrast in composite structures such as WTBs, a controlled study was carried out on a blade section exposed to programmed temperature transients in a climate chamber. Infrared measurements were recorded, and the thermal behaviour of the specimen was simulated using finite element models (FEM) in COMSOL Multiphysics 6.3. Although direct validation is limited by measurement uncertainties and transient effects, the comparison provides insight into the capabilities and limitations of FEM in replicating real-world thermal behaviour. This paper focuses specifically on the challenges related to the modelling approach. T2 - 18th International Workshop on Advanced Infrared Technology and Applications (AITA 2025) CY - Kobe, Japan DA - 15.09.2025 KW - Thermography KW - Wind energy KW - Wind turbine rotor blades KW - Windenergie Anlage Rotorblätter KW - FEA PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-642308 DO - https://doi.org/10.3390/proceedings2025129015 VL - 129 IS - 1 SP - 1 EP - 5 PB - MDPI CY - Basel AN - OPUS4-64230 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Scheuschner, Nils A1 - Altenburg, Simon A1 - Pignatelli, Giuseppe A1 - Maierhofer, Christiane A1 - Straße, Anne A1 - Gornushkin, Igor B. A1 - Gumenyuk, Andrey T1 - Vergleich der Messungen der Schmelzbadtemperatur bei der Additiven Fertigung von Metallen mittels IR-Spektroskopie und Thermografie T1 - Comparison of measurements of the melt pool temperature during the additive production of metals by means of IR spectroscopy and thermography N2 - Im Rahmen des Themenfeldprojektes „Process Monitoring of AM“ (ProMoAM) evaluiert die Bundesanstalt für Materialforschung und -Prüfung (BAM) gegenwärtig die Anwendbarkeit verschiedenster ZfP-Verfahren zur in-situ Prozessüberwachung in der additiven Fertigung (AM) von Metallen in Hinblick auf die Qualitätssicherung. Einige der wichtigsten Messgrößen sind hierbei die Temperatur des Schmelzbades und die Abkühlrate, welche starken Einfluss auf das Gefüge und die Eigenspannung haben. Aufgrund der Zugänglichkeit zum Werkstück während des Bauprozesses bieten sich optische Verfahren zu Temperaturbestimmung an. Hierbei stellen jedoch u. a. die hohe Bandbreite der zu messenden Temperaturen, die Bestimmung der Emissivität und ihre Änderung bei Phasenübergängen der verwendeten Legierung große experimentelle Herausforderungen dar. Eine weitere Herausforderung stellt für die IR-Spektroskopie die Absorption durch das Schutzgas und weitere optische Elemente dar. Um diese auch in einem industriellen Umfeld kompensieren zu können, wurde eine Methode entwickelt, die das gemessene Spektrum bei der Verfestigung des Werkstoffes als Referenz nutzt. In diesem Beitrag wird die Anwendung dieser Methode für die IR-Spektrometrie als auch Thermografische Messungen beim Laser-Pulver-Auftragschweißen von 316L gezeigt, wobei beide Methoden weiterhin in Hinblick auf ihre individuellen Vor- und Nachteile miteinander verglichen werden. N2 - Within the topic area project “Process Monitoring of AM” (ProMoAM) the Federal Institute for Materials Research and Testing is currently evaluating the applicability of various NDT methods for in-situ process Monitoring in the additive manufacturing (AM) of metals with regard to quality assurance. Two of the most important variables to measure are the temperature of the molten pool and the cooling rate, which have a strong influence on the microstructure and the residual stress. Due to the accessibility of the workpiece during the construction process, optical methods for temperature determination are suitable. However, the wide range of temperatures to be measured, the determination of emissivity and its change during phase transitions of the alloy pose great experimental challenges. Another challenge for IR spectroscopy is the absorption by the inert gas and other optical elements. In order to be able to compensate for this in an industrial environment, a method was developed which uses the measured spectrum as a reference when the material is solidified. This paper shows the application of this method for IR spectrometry as well as thermographic measurements during laser powder cladding of 316L. Furthermore both methods are compared with respect to their individual Advantages and disadvantages. KW - Laser-Pulver-Auftragschweißen KW - Thermografie KW - Direct Energy Deposition KW - IR-Spektroskopie KW - Additive Fertigung KW - Laser metal deposition KW - Thermography KW - IR-spectroscopy KW - Additive manufacturing PY - 2021 DO - https://doi.org/10.1515/teme-2021-0056 VL - 88 IS - 10 SP - 626 EP - 632 PB - De Gruyter CY - Oldenburg AN - OPUS4-52987 LA - deu 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 - Stamm, Michael T1 - Towards the in-service blade inspection by ground-based passive thermography N2 - Until today, the optical inspection of rotor blades by industrial climbers is considered state of the art. However, both more and larger rotor blades and the increasing digitalization of maintenance work make modern inspection methods increasingly necessary. In this context, passive thermography can serve as a useful digital technique for in-service inspection of wind turbine blades. Unlike active thermography, this inspection method does not require an active heat source but takes advantage of heating by the sun and diurnal temperature fluctuations. This allows inspections from the ground during operation and does not require shutting down the wind turbine. However, an inspection with passive thermography is highly weather dependent. Thus, the already weak thermal signatures formed due to internal structures and possible internal damage are only strong enough under certain weather conditions. To obtain meaningful inspection results despite the relatively small thermal differences between intact and defective components, three aspects are crucial: 1. Measurements should be taken at the time of optimum weather conditions. It must be kept in mind that different internal damage will be revealed by thermal signatures under different weather conditions. 2. The thermal signature of the rotor blades, including possible damages, must be simulated with FEM simulations. In this way, the influence of different weather conditions can be predicted but also understood in the aftermath. 3. The temperature differences between identically designed and assembled rotor blades must be considered to analyze variations between blades. This work will address all these aspects and show, based on field measurements under industrial conditions (exemplarily shown in figure 1), laboratory measurements and FEM simulations, which steps must be taken to establish passive thermography as an industrial inspection method. T2 - EERA SP7 Rotor Blade workshop CY - Roskilde, Denmark DA - 23.06.2022 KW - Thermography KW - Wind energy KW - Maintenance KW - Rotor blades KW - Passive IRT PY - 2022 AN - OPUS4-55819 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon T1 - Towards hyperspectral in-situ temperature measurement in metal additive manufacturing N2 - The industrial use of additive manufacturing for the production of metallic parts with high geometrical complexity and lot sizes close to one is rapidly increasing as a result of mass individualisation and applied safety relevant constructions. However, due to the high complexity of the production process, it is not yet fully understood and controlled, especially for changing (lot size one) part geometries. Due to the thermal nature of the Laser-powder bed fusion (L-PBF) process – where parts are built up layer-wise by melting metal powder via laser - the properties of the produced part are strongly governed by its thermal history. Thus, a promising route for process monitoring is the use of thermography. However, the reconstruction of temperature information from thermographic data relies on the knowledge of the surface emissivity at each position on the part. Since the emissivity is strongly changing during the process due to phase changes, great temperature gradients, possible oxidation, and other potential influencing factors, the extraction of real temperature data from thermographic images is challenging. While the temperature development in and around the melt pool, where melting and solidification occur is most important for the development of the part properties. Also, the emissivity changes are most severe in this area, rendering the temperature deduction most challenging. A possible route to overcome the entanglement of temperature and emissivity in the thermal radiation is the use of hyperspectral imaging in combination with temperature emissivity separation (TES) algorithms. As a first step towards the combined temperature and emissivity determination in the L-PBF process, here, we use a hyperspectral line camera system operating in the short-wave infrared region (0.9 µm to 1.7 µm) to measure the spectral radiance emitted. In this setup, the melt pool of the L-PBF process migrates through the camera’s 1D field of view, so that the radiation intensities are recorded simultaneously for multiple different wavelength ranges in a spatially resolved manner. At sufficiently high acquisition frame rate, an effective melt pool image can be reconstructed. Using the grey body approximation (emissivity is independent of the wavelength), a first, simple TES is performed, and the resulting emissivity and temperature values are compared to literature values. Subsequent work will include reference measurements of the spectral emissivity in different states allowing its analytical parametrisation as well as the adaption and optimisation of the TES algorithms. An illustration of the proposed method is shown in Fig.1. The investigated method will allow to gain a deeper understanding of the L-PBF process, e.g., by quantitative validation of simulation results. Additionally, the results will provide a data basis for the development of less complex and cheaper sensor technologies for L-PBF in-process monitoring (or for related process), e.g., by using machine learning. T2 - 21st International Conference on Photoacoustic and Photothermal Phenomena CY - Bled, Slovenia DA - 19.06.2022 KW - Thermography KW - Additive manufacturing KW - L-PBF KW - Hyperspectral PY - 2022 AN - OPUS4-55152 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stamm, Michael T1 - Towards automated passive thermography of wind turbine blades N2 - Up to now, the inspection of wind turbines by industrial climbers has been considered "state of the art". However, many aspects like ever-larger wind turbines, minimizing the risk for man and machine and the advancing digitalization make modern and automated inspection methods indispensable. A particular interest here is contactless and remote methods that can be used with drones instead of climbing robots. The work presented here contributes to the long-term goal of making autonomous and advanced inspections of wind turbine rotor blades using drones ready for industrial use. Besides visual inspection, only a few inspection methods are capable of non-contact inspection on an industrial scale. Passive thermography can serve as such a contactless and digital inspection method and is well known for its applications in the inspection of buildings or electrical circuits. It can even sense both near-surface and subsurface defects. The sensitivity to subsurface defects makes one advantage of thermography over visual inspections. As a digital inspection method, it is generally also more objective and offers more comparability. For example, defects and their extent can be easily monitored and compared over time. However, its industrial application relies on thermal gradients in the inspected object such that a temperature contrast exists between damaged and sound areas. This also applies to large unheated structures such as wind turbine rotor blades, which do not have an intrinsic temperature gradient and at the same time cannot be easily heated externally. Under certain weather conditions, a change of the environmental temperature or the solar loading conditions can provide the necessary thermal gradients to make passive thermography viable for the in-service inspection of rotor blades. For a reliable use of passive thermography on "thermal passive" components, the incorporation of these environmental conditions in the planning and evaluation of thermal inspections is crucial. Compared to many other objects and buildings, wind turbine blades have varying and often unknown complex internal structures depending on the model. A special method is therefore required, that can be used independently of the internal structure of the blades and that relates the individual thermograms of the three rotor blades to each other. This allows the distinction between the thermal response of design-specific structural features and damages or irregularities between the three blades. In this work we present thermal signatures of rotating in-service rotor blades taken under industrial relevant conditions. These thermograms show surface and subsurface damages and irregularities which we contrast with structural design features by referencing the three blades to each other. In addition, we examine the strong influence of different weather conditions on the inspection results. A direct comparison of measured results with inspection reports from industrial climbers serves as a benchmark. T2 - EERA DeepWind conference CY - Trondheim, Norway DA - 19.01.2022 KW - Thermography KW - Wind energy KW - Passve IR KW - Rotor blades KW - Maintenance PY - 2022 AN - OPUS4-55818 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Chaudhuri, Somsubhro A1 - Purayil, Sruthi Krishna Kunji A1 - Kruse, Julius A1 - Madia, Mauro A1 - Nielsen, Sören T1 - Thermography-Assisted Mechanical Testing of Cold-Spray (AM) Repair N2 - Cold Spray Additive Manufacturing (CSAM) is a solid-state process that is being increasingly used for structural repairs in aerospace and energy sectors. It enables the deposition of dense material at low temperatures by accelerating metal particles to supersonic velocities, thereby reducing thermal distortion. However, the structural integrity of CSAM repairs—particularly at the interface between the deposited layer and the substrate—remains a critical concern. Various post-treatments and characterization methods have been explored to optimize performance. While X-ray Computed Tomography (XCT) is effective for sub-surface inspection, it cannot be applied in situ during mechanical testing. Digital Image Correlation (DIC), a surface-based method, also lacks sub-surface sensitivity. To address this, Infrared Thermography (IRT) was employed alongside DIC during the tensile and fatigue testing of aluminum CSAM-repaired specimens. A cooled IRT camera operating at 200 FPS captured thermal data, with lock-in processing subsequently applied in post-processing. IRT successfully detected early interfacial damage and enabled the tracking of crack propagation, which was later confirmed through fracture surface analysis. This extended abstract presents findings from fatigue tests using IRT. T2 - 18th International Workshop on Advanced Infrared Technology and Applications (AITA 2025) CY - Kobe, Japan DA - 15.09.2025 KW - Thermography KW - Thermografie KW - Thermal stress analysis KW - Cold spray KW - Damage detection PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-642299 DO - https://doi.org/10.3390/proceedings2025129018 VL - 129 IS - 1 SP - 1 EP - 5 PB - MDPI CY - Basel AN - OPUS4-64229 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Chaudhuri, Somsubhro T1 - Thermography-Assisted Mechanical Testing of Cold-Spray (AM) Repair N2 - Cold Spray Additive Manufacturing (CSAM) is a solid-state process that is being increasingly used for structural repairs in aerospace and energy sectors. It enables the deposition of dense material at low temperatures by accelerating metal particles to supersonic velocities, thereby reducing thermal distortion. However, the structural integrity of CSAM repairs—particularly at the interface between the deposited layer and the substrate—remains a critical concern. Various post-treatments and characterization methods have been explored to optimize performance. While X-ray Computed Tomography (XCT) is effective for sub-surface inspection, it cannot be applied in situ during mechanical testing. Digital Image Correlation (DIC), a surface-based method, also lacks sub-surface sensitivity. To address this, Infrared Thermography (IRT) was employed alongside DIC during the tensile and fatigue testing of aluminum CSAM-repaired specimens. A cooled IRT camera operating at 200 FPS captured thermal data, with lock-in processing subsequently applied in post-processing. IRT successfully detected early interfacial damage and enabled the tracking of crack propagation, which was later confirmed through fracture surface analysis. T2 - Advanced Infrared Technology and Applications (AITA) 2025 CY - Kobe, Japan DA - 15.09.2025 KW - Thermography KW - Thermografie KW - Thermal stress analysis KW - Cold spray KW - Damage detection PY - 2025 AN - OPUS4-64227 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon A1 - Scheuschner, Nils A1 - Maierhofer, Christiane A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Thermography in laser powder bed fusion of metals: time over threshold as feasible feature in thermographic data N2 - Thermography is one on the most promising techniques for in-situ monitoring of metal additive manufacturing processes. Especially in laser powder bed fusion processes, the high process dynamics and the strong focus of the laser beam cause a very complex thermal history within the produced specimens, such as multiple heating cycles within single layer expositions. This complicates data interpretation, e.g., in terms of cooling rates. A quantity that is easily calculated is the time a specific area of the specimen is at a temperature above a chosen threshold value (TOT). Here, we discuss variations occurring in time-over-threshold-maps during manufacturing of an almost defect free cuboid specimen. T2 - 15th Quantitative InfraRed Thermography conference CY - Online meeting DA - 21.09.2020 KW - Additive Manufacturing KW - Process monitoring KW - Thermography KW - L-PBF KW - Time over threshold PY - 2020 DO - https://doi.org/10.21611/qirt.2020.005 SP - 1 EP - 5 PB - QIRT Council CY - Quebec, Canada AN - OPUS4-52014 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon T1 - Thermography in laser powder bed fusion of metals: time over threshold as feasible feature in thermographic data N2 - Thermography is one on the most promising techniques for in-situ monitoring for metal additive manufacturing processes. The high process dynamics and the strong focus of the laser beam cause a very complex thermal history within the produced specimens, such as multiple heating cycles within single layer expositions. This complicates data interpretation, e.g., in terms of cooling rates. A quantity that is easily calculated is the time a specific area of the specimen is at a temperature above a chosen threshold value (TOT). Here, we discuss variations occurring in time-over-threshold-maps during manufacturing of a defect free cuboid specimen. T2 - 15th Quantitative InfraRed Thermography conference CY - Online meeting DA - 21.09.2020 KW - Additive Manufacturing KW - Process monitoring KW - Thermography KW - L-PBF KW - Time over threshold PY - 2020 AN - OPUS4-51630 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 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 - Ziegler, Mathias 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 - GEN A1 - Lecompagnon, Julien T1 - Thermographic Reference Dataset: Experimentally simulated Gaussian-shaped internal defects in GFRP N2 - We introduce a thermographic reference dataset consisting of 100 experimentally recorded temperature fields that replicate defect-like heat signatures in glass fiber reinforced polymer (GFRP) composites. Instead of relying on the fabrication of numerous damaged specimens, the dataset was generated by directly imprinting defect signatures onto an intact laminate using a near-infrared laser projector with spatial light modulation. The projected patterns are derived from parameterized Gaussian distributions, enabling systematic variation in defect size, shape, and orientation. The resulting steady-state thermal responses were captured with infrared thermography, providing high-resolution temperature distribution measurements for each case. This novel approach ensures that the heat transfer physics are preserved experimentally, while no special samples with different defects need to be manufactured to acquire datasets for different defect parameters. The dataset is ultimately designed as a resource for the benchmarking of thermographic non-destructive testing techniques, the validation of numerical heat transfer simulations, and the training of data-driven algorithms for defect detection in composite materials. KW - Thermography KW - Temperature KW - Composites KW - GFRP KW - Reference Data KW - Laser Projector KW - Nondestructive Testing PY - 2025 DO - https://doi.org/10.5281/zenodo.17378681 PB - Zenodo CY - Geneva AN - OPUS4-64472 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien 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 - 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 - Lapšanská, Ivana T1 - Thermographic detection and AI evaluation of leading-edge erosion N2 - The European Green Deal and the global fight against climate change call for more and larger wind turbines. To meet the increasing demand for maintenance and inspection, semi-autonomous methods of remote inspection are increasingly being developed in addition to industrial climbers performing the inspection [1, 2]. Rotor blades are exposed to extreme weather conditions throughout their lifetime causing leading edge erosion which changed the aerodynamic features of blades and can cause structural damages. The estimated annual energy production (AEP) losses caused by erosion damages are between 0.5% and 2% per year. The classification of the severity of the damage and the quantification of the resulting AEP losses are subject of scientific research. With such information, cost efficient repairs and maintenance efforts can improve the power production of wind turbines. Passive thermography presents a viable method for inspecting rotor blades, capable of identifying internal damage [3, 4] and surface erosion [5, 6]. An advantage of this method is that it not only detects rain erosion damage but also reveals temperature variations caused by resulting turbulence on the blade's surface. These turbulent effects reduce rotor blade efficiency, leading to losses in AEP. The inspection process takes approximately 10 minutes per turbine and is carried out while the turbine is fully operational, eliminating downtime and revenue losses typically associated with traditional blade inspections. This efficient inspection procedure is further enhanced by an automatic data analysis system, resulting in a substantial number of wind turbines being inspected within a specified timeframe. The automated evaluation of thermal images is executed using a fully convolutional network (FCN). The initial phase involved training an FCN using over 1500 thermal images. The primary objective was to accurately identify the thermal patterns associated with erosion damage at the leading edge. In the ongoing second phase, the emphasis is on integrating thermographic and visual images to assess the extent of the damage using an FCN. Additionally, this phase involves leveraging human factors in the FCN training process and providing a precise estimation of Annual Energy Production losses attributed to the identified rain erosion damages. T2 - EERA Deep Wind 2024 CY - Trondheim , Norway DA - 17.01.2024 KW - Wind KW - Turbulent flow KW - Thermography KW - Wind rotor blade KW - Inspection PY - 2024 UR - https://www.sintef.no/globalassets/project/eera-deepwind-2024/posters/operation-and-maintenance_ivana_lapsanska_thermographic-detection.pdf AN - OPUS4-62501 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien T1 - Thermografische Super Resolution mit 2D-strukturierter Erwärmung N2 - Thermografische Super Resolution ermöglicht die Auflösung von Defekten/Inhomogenitäten unterhalb des klassischen Limits, welches durch die Diffusionseigenschaften der thermischen Wellenausbreitung bestimmt wird. Basierend auf einer Kombination aus der Anwendung spezieller Abtaststrategien und einer anschließenden numerischen Optimierungsschritt bei der Datenauswertung hat sich die thermografische Super Resolution bereits bei der Detektion von 1D-Defekten gegenüber den Standard-Thermografieverfahren als überlegen erwiesen. In unserer Arbeit erweitern wir die Möglichkeiten der Methode zur effizienten Detektion und Auflösung von Defektquerschnitten mit einer vollständig 2D-strukturierten Erwärmung. Der experimentelle Ansatz basiert auf einer wiederholten räumlich strukturierten Erwärmung durch einen Hochleistungslaser. In einem zweiten Nachbearbeitungsschritt werden mehrere kohärente Messungen mittels mathematischer Optimierung und unter Ausnutzung der (Joint-) Sparsity der Defekte innerhalb des Prüfkörpers kombiniert. Als Ergebnis kann eine 2D-sparse Defekt-/ Inhomogenitätskarte erhalten werden. Da die Kombination von räumlich strukturierter Erwärmung und anschließender numerischer Kombination mehrerer kohärenter Messungen nicht nur die Auflösung verbessert, sondern auch die Messkomplexität drastisch erhöht, werden verschiedene Scanstrategien untersucht. Abschließend werden die erhaltenen Ergebnisse mit denen konventioneller thermografischer Prüfverfahren verglichen. T2 - DGZfP-Jahrestagung 2021 CY - Online meeting DA - 10.05.2021 KW - Thermography KW - Super-resolution KW - NDT KW - Inspection KW - Image resolution PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-526396 UR - https://jahrestagung.dgzfp.de/Programm#P45 AN - OPUS4-52639 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stamm, Michael T1 - Thermografische Ferninspektion von Windenergieanlagen im Betrieb –� Potenziale und Herausforderungen N2 - Rotorblätter zählen zu den kostenintensivsten Komponenten von Windenergieanlagen in Bezug auf Wartung und Ausfallzeiten. Mit der zunehmenden Blattlänge – aktuell bis zu 115 m – steigen auch die Anforderungen an effektive Inspektionsmethoden. Die Bundesanstalt für Materialforschung und -prüfung (BAM) entwickelt hierfür eine passive thermografische Ferninspektion vom Boden aus, die die klassische visuelle Prüfung durch Industriekletterer ergänzen oder perspektivisch ersetzen soll. Feldmessungen und Laborexperimente belegen das Potenzial dieser Technik, sowohl strömungsbedingte thermische Signaturen als auch strukturelle Anomalien innerhalb der Rotorblätter zu erfassen. Eine besondere Herausforderung liegt in der Trennung dieser überlagerten Effekte sowie in der eingeschränkten Kenntnis der inneren Blattstruktur aufgrund fehlender Designdaten. Um die Methode zur Marktreife zu führen, sind Fortschritte in der Bildverarbeitung, etwa durch eine patentierte Differenzbildung, erforderlich. Der Beitrag stellt die zugrunde liegende Messtechnik, Ergebnisse einer groß angelegten Feldstudie mit 30 Anlagen sowie die identifizierten physikalischen Einflussgrößen (Strömung, Struktur, Emissivität) vor und gibt einen Ausblick auf die nächsten Entwicklungsschritte. T2 - Thermo25 CY - Munich, Germany DA - 12.11.2025 KW - Thermography KW - Wind Turbine Blades KW - Wind KW - Rotorblätter PY - 2025 AN - OPUS4-64718 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stamm, Michael T1 - The KI-VISIR Reference Dataset: A Compilation of Thermal and Visual Inspection Data for Quantifying Leading Edge Rain Erosion N2 - This presentation introduces thermography (thermal imaging) as a key method for non-destructive testing (NDT) of wind turbine rotor blades. By leveraging solar heating and aerodynamic effects, passive thermography detects internal defects, delaminations, and surface issues like leading edge erosion. We discuss field measurements, the role of AI/Machine Learning (LATODA) for automated defect classification, and its importance for improving O&M efficiency and lifetime extension in the wind energy sector. T2 - WindEurope Annual Event 2025 CY - Copenhagen, Denmark DA - 08.04.2025 KW - Thermography KW - Wind Turbine Blades KW - AI KW - NDT KW - KI-VISIR PY - 2025 AN - OPUS4-64721 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maierhofer, Christiane T1 - Summary of in-situ monitoring in additive manufacturing - ProMoAM N2 - The quality of additively manufactured components is significantly influenced by the process parameters used during production. Thus, sensors and measuring systems are already commercially available for process monitoring, at least in metal-based additive manufacturing. However, it is not yet possible to detect defects and inhomogeneities directly or indirectly during the building process. The aim of the project ProMoAM is to develop spectroscopic and non-destructive testing methods for the in-situ evaluation of the quality of additively manufactured metal components in laser- or arc-based AM processes. In addition to passive and active methods of thermography, this includes optical tomography, optical emission spectroscopy, eddy current testing, laminography (radiography), X-ray backscattering, particle emission spectroscopy and photoacoustic methods. T2 - 2nd Workshop on In-situ Monitoring and Microstructure Development in Additive Manufactured Alloys CY - Online meeting DA - 19.04.2021 KW - In-situ monitoring KW - Additive manufacturing KW - Metals KW - Thermography PY - 2021 AN - OPUS4-52539 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ulbricht, Alexander A1 - Altenburg, Simon A1 - Sprengel, Maximilian A1 - Sommer, Konstantin A1 - Mohr, Gunther A1 - Fritsch, Tobias A1 - Mishurova, Tatiana A1 - Serrano-Munoz, Itziar A1 - Evans, Alexander A1 - Hofmann, M. A1 - Bruno, Giovanni T1 - Separation of the Formation Mechanisms of Residual Stresses in LPBF 316L N2 - Rapid cooling rates and steep temperature gradients are characteristic of additively manufactured parts and important factors for the residual stress formation. This study examined the influence of heat accumulation on the distribution of residual stress in two prisms produced by Laser Powder Bed Fusion (LPBF) of austenitic stainless steel 316L. The layers of the prisms were exposed using two different border fill scan strategies: one scanned from the centre to the perimeter and the other from the perimeter to the centre. The goal was to reveal the effect of different heat inputs on samples featuring the same solidification shrinkage. Residual stress was characterised in one plane perpendicular to the building direction at the mid height using Neutron and Lab X-ray diffraction. Thermography data obtained during the build process were analysed in order to correlate the cooling rates and apparent surface temperatures with the residual stress results. Optical microscopy and micro computed tomography were used to correlate defect populations with the residual stress distribution. The two scanning strategies led to residual stress distributions that were typical for additively manufactured components: compressive stresses in the bulk and tensile stresses at the surface. However, due to the different heat accumulation, the maximum residual stress levels differed. We concluded that solidification shrinkage plays a major role in determining the shape of the residual stress distribution, while the temperature gradient mechanism appears to determine the magnitude of peak residual stresses. KW - Additive Manufacturing KW - Laser Powder Bed Fusion KW - LPBF KW - AISI 316L KW - Online Process Monitoring KW - Thermography KW - Residual Stress KW - Neutron Diffraction KW - X-ray Diffraction KW - Computed Tomography PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-512903 DO - https://doi.org/10.3390/met10091234 VL - 10 IS - 9 PB - MDPI CY - Basel AN - OPUS4-51290 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stamm, Michael T1 - Semi-automated detection of rain erosion damages on turbine blades with passive thermography and AI image processing N2 - The European Green Deal and the global fight against climate change call for more and larger wind turbines in Europe and around the world. To meet the increasing demand for maintenance and inspection, partly autonomous methods of remote inspection are increasingly being developed in addition to industrial climbers performing the inspection. Rotor blades are exposed to extreme weather conditions throughout their lifetime of 20 years, and the leading edge erodes over time. These erosion damages change the aerodynamic features of blades and can cause structural damages. The estimated annual energy production (AEP) losses caused by erosion damages are between 0.5% and 2% per year. The classification of the severity of a rain erosion damage and the quantification of the resulting AEP losses for cost efficient repair and maintenance efforts and improved power production of wind turbines are subject of scientific research. For the inspection of wind turbine rotor blades, passive thermography is an option that has been used to detect both internal damage [3, 4] as well as erosion on the surface [5, 6]. The advantage is that, given suitable boundary conditions, not only the rain erosion damage itself but also temperature differences caused by the resulting turbulences can be observed on the surface of the blade. Turbulences reduce the efficiency of the rotor blades and result in AEP losses. Optimised thermography inspections can contribute to detect and to evaluate rain erosion damages. The thermal inspection lasts 10 minutes per turbine and is performed while the turbine is in full operation, avoiding downtime and lost opportunities for the turbine owner which are usually caused by conventional blade inspections. The timely inspection procedure is complemented by an automatic data evaluation and results in a considerable number of inspected wind turbines in a certain period of time. A fully convolutional network (FCN) is implemented for the automated evaluation of thermal images. In the presented study, more than 1000 thermographic images of blades were annotated, augmented and used to train and test the FCN. The aim is the precise marking of thermal signatures caused by erosion damage at the leading edge. The area size of the detected temperature difference caused by turbulences was used to identify and categorise damages. Certain strategies were adopted to group small individual indications as one large damage, in order to develop simplification rules based on realistic thermal imaging resolution. T2 - Wind Energy Science Conference (WESC) 2023 CY - Glasgow, Scotland DA - 23.05.2023 KW - Non-destructive testing KW - Thermography KW - Wind turbine blade PY - 2023 AN - OPUS4-58498 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Scheuschner, Nils T1 - SAMMIE - Research PBF-LB/M system for the development of in-situ monitoring methods N2 - By allowing economic on-demand manufacturing of highly customized and complex workpieces, metal based additive manufacturing (AM) has the prospect to revolutionize many industrial areas. Since AM is prone to the formation of defects during the building process, a fundamental requirement for AM is to find ways to assure the safety and reliability of the additively manufactured parts to become applicable in most fields. A possible solution for this problem lies in the deployment of various in-situ monitoring techniques. However, only a few of these techniques are commercially available and are not researched to an extent that allows to guarantee the adherence to strict quality and safety standards. Since commercial AM machines are not designed for research applications, they provide only limited access to the build chamber during the process and little control over the exact timing and parameters of the process. Therefore, for our research at BAM, we built a laser powder bed fusion system (PBF-LB/M), called “Sensor-based Additive Manufacturing MachInE” (SAMMIE). It provides a fully open system architecture with flexible accesses to the build camber and full control of the complete process. In this contribution, we show first results using thermographic cameras and optical tomography. The flexibility of SAMMIE allows us to use the multiple cameras either fixed relatively to the build plate or coaxially to the process laser. T2 - 20th World Conference on Non-Destructive Testing (WCNDT) CY - Incheon, South Korea DA - 27.05.2024 KW - PBF-LB/M KW - In situ monitoring KW - Custom machine KW - Additive Manufacturing KW - Thermography PY - 2024 AN - OPUS4-62471 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hirsch, Philipp Daniel T1 - Robotic-assisted 3D scanning and laser thermography for crack inspection on complex components N2 - The integration of automation and robotics into inspection processes has marked a transformative shift in the evaluation of complex components. This study presents a novel approach employing robotic-assisted laser thermography for the automated identification and in-depth analysis of cracks in these intricate structures. This method not only streamlines the inspection process but also eliminates the need for numerous manual steps and the use of chemicals associated with traditional methods such as dye penetrant testing. With the increasing com-plexity of components, this is an important step, especially with regard to additively manufactured components, in order to be able to guarantee component safety for a long lifecycle. T2 - 17th Quantitative InfraRed Thermography Conference (QIRT) CY - Zagreb, Croatia DA - 01.07.2024 KW - Robot KW - Flying line KW - Crack detection KW - Robot path planning KW - Thermography PY - 2024 AN - OPUS4-60914 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hirsch, Philipp Daniel A1 - Kunji Purayil, Sruthi Krishna A1 - Lecompagnon, Julien A1 - Pech May, Nelson Wilbur A1 - Ziegler, Mathias ED - Maldague, X. T1 - Robotic-Assisted 3D Scanning and Laser Thermography for Crack Inspection on Complex Components N2 - The integration of automation and robotics into non-destructive testing (NDT) marks a significant advancement in evaluating complex components. This paper introduces a novel approach using robotic-assisted laser thermography combined with automated 3D scanning to detect and analyze cracks in complex structures. The system uses an integrated line scanner with a robotic arm to capture high-resolution data, creating detailed 3D models for adaptive path planning and precise alignment correction. Laser thermography, based on localized heating and the "flying spot" approach, detects surfacenear cracks with high precision. Crack detection is achieved using the Canny algorithm optional on Fourier-transformed thermograms, offering robust results with minimal computation. This study highlights the potential of robotic-assisted 3D scanning and laser thermography as efficient and precise methods for crack inspection, advancing NDT technologies and ensuring the structural integrity of modern components. T2 - 17th International Conference on Quantitative InfraRed Thermography 2024 CY - Zagreb, Croatia DA - 01.07.2024 KW - Thermography KW - Non-destructive testing KW - Laser line KW - Robotic arm KW - Defect identification KW - Crack detection PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-653809 DO - https://doi.org/10.21611/qirt-2024-078 SP - 1 EP - 8 PB - QIRT Council AN - OPUS4-65380 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mohr, Gunther A1 - Sommer, Konstantin A1 - Knobloch, Tim A1 - Altenburg, Simon A1 - Recknagel, Sebastian A1 - Bettge, Dirk A1 - Hilgenberg, Kai T1 - Process Induced Preheating in Laser Powder Bed Fusion Monitored by Thermography and Its Influence on the Microstructure of 316L Stainless Steel Parts N2 - Undetected and undesired microstructural variations in components produced by laser powder bed fusion are a major challenge, especially for safety-critical components. In this study, an in-depth analysis of the microstructural features of 316L specimens produced by laser powder bed fusion at different levels of volumetric energy density and different levels of inter layer time is reported. The study has been conducted on specimens with an application relevant build height (>100 mm). Furthermore, the evolution of the intrinsic preheating temperature during the build-up of specimens was monitored using a thermographic in-situ monitoring set-up. By applying recently determined emissivity values of 316L powder layers, real temperatures could be quantified. Heat accumulation led to preheating temperatures of up to about 600 °C. Significant differences in the preheating temperatures were discussed with respect to the individual process parameter combinations, including the build height. A strong effect of the inter layer time on the heat accumulation was observed. A shorter inter layer time resulted in an increase of the preheating temperature by more than a factor of 2 in the upper part of the specimens compared to longer inter layer times. This, in turn, resulted in heterogeneity of the microstructure and differences in material properties within individual specimens. The resulting differences in the microstructure were analyzed using electron back scatter diffraction and scanning electron microscopy. Results from chemical analysis as well as electron back scatter diffraction measurements indicated stable conditions in terms of chemical alloy composition and austenite phase content for the used set of parameter combinations. However, an increase of the average grain size by more than a factor of 2.5 could be revealed within individual specimens. Additionally, differences in feature size of the solidification cellular substructure were examined and a trend of increasing cell sizes was observed. This trend was attributed to differences in solidification rate and thermal gradients induced by differences in scanning velocity and preheating temperature. A change of the thermal history due to intrinsic preheating could be identified as the main cause of this heterogeneity. It was induced by critical combinations of the energy input and differences in heat transfer conditions by variations of the inter layer time. The microstructural variations were directly correlated to differences in hardness. KW - Additive manufacturing KW - Laser powder bed fusion KW - In-situ process monitoring KW - Thermography KW - Heat accumulation KW - Inter layer time KW - Cellular substructure PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-529240 DO - https://doi.org/10.3390/met11071063 VL - 11 IS - 7 SP - 1063 PB - MDPI CY - Basel, Schweiz AN - OPUS4-52924 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien T1 - Practical study on the thermographic detectability of internal defects using temporally structured laser heating N2 - Modern laser systems have proven to be versatile heat sources for active thermographic testing applications. Compared to more traditional light sources, e.g. flash or halogen lamps, their output power can be easily modulated at high rates, allowing a wide variety of complex excitations to be realized. Although their total optical output power can be theoretically scaled to arbitrary values, the maximum output power is practically limited by many factors: the maximum power that the sample under test can absorb without altering the lighted surface itself, the trade-off between power density and inspected area, the cost of the laser system, etc. Furthermore, when working with spatial modulator systems, the output power could be limited to avoid provoking any damages on such devices. Nevertheless, to guarantee sufficient heating even for highly thermally conductive materials and/or deeply buried defects, the heating times can be extended, e.g., either by using step heating, long pulse thermography, or by lock-in thermography with a continuously modulated heating. However, for all these approaches, the ranging capabilities of the thermographic defect detection are reduced due to the limited frequency content of the excitation. To tackle this problem, i.e. to increase the excitation energy while preserving its frequency content, new approaches have been developed in the last two decades, among which the use of coded excitations combined with pulse-compression, and the use of multiple lock-in analysis or of a frequency modulated excitation signal. The challenges of such temporally structured heating techniques are manifold, for example, the DC component inherent in optical heating must be taken into account. In general, a wider frequency bandwidth or greater variability of the frequency components also means greater complexity for signal generation and data processing. In this paper, temporal structured excitation schemes with different degrees of complexity are compared on a high power laser system. T2 - 17th Quantitative InfraRed Thermography Conference (QIRT) CY - Zagreb, Croatia DA - 01.07.2024 KW - Thermography KW - Laser KW - NDT KW - Temporal structuring KW - Pulse-compression PY - 2024 AN - OPUS4-60563 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien A1 - Ricci, M. A1 - Laureti, S. A1 - Ziegler, Mathias ED - Maldague, X. T1 - Practical study on the thermographic detectability of internal defects using temporally structured laser heating N2 - Modern laser systems have proven to be highly versatile heat sources for active thermographic testing. Compared to more traditional light sources, e.g. flash or halogen lamps, their output power can be easily modulated at high rates, allowing a wide variety of complex excitations to be realized. Although their total optical output power can be theoretically scaled to arbitrary values, the maximum output power is practically limited by many factors: the maximum power that the sample under test can absorb without altering the lighted surface itself, the trade-off between irradiance and inspected area, the cost of the laser system, etc. Furthermore, when working with spatial modulator systems, the output power must be limited to avoid damaging such devices. Nevertheless, to guarantee a sufficient amount of heating even for highly thermally conductive materials and/or deeply buried defects, the heating times can be extended, e.g., either by using step heating, long pulse thermography, or by lock-in thermography with a continuously modulated heating. However, for all these approaches, the ranging capabilities of the thermographic defect detection are reduced due to the limited frequency content of the excitation. To tackle this problem, i.e. to increase the excitation energy while preserving its frequency content, new approaches have been developed in the last two decades, among them the use of coded excitations in combination with pulse-compression, and the use of multiple lock-in analysis or a frequency modulated excitation signal. The challenges of such temporally structured heating techniques are manifold, for example, the DC component inherent in optical heating must be taken into account. In general, a wider frequency bandwidth or greater variability of the frequency components also means greater complexity for signal generation and data processing. In this paper, temporally structured excitation schemes with different degrees of complexity are compared on a high-power laser system. T2 - 17th International Conference on Quantitative InfraRed Thermography 2024 CY - Zagreb, Croatia DA - 01.07.2024 KW - Thermography KW - Laser KW - NDT KW - Coded excitation KW - Defect identification PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-653790 DO - https://doi.org/10.21611/qirt-2024-077 SN - 2371-4085 SP - 1 EP - 9 PB - QIRT Council AN - OPUS4-65379 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon 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 - 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 - Oster, Simon T1 - Porosity prediction in metal based additive manufacturing utilizing in situ thermography N2 - Quality assessment of components produced by metal based additive manufacturing (AM) technologies such as laser powder bed fusion is rising in importance due to the increased use of AM in industrial production. Here, the presence of internal porosity was identified as a limiting factor for the final component quality. The utilization of thermography as an in-situ monitoring technique allows the determination of the part’s thermal history which was found to be connected to the porosity formation [1]. Combining the local thermal information derived from thermography with the porosity information obtained by x-ray micro computed tomography, machine learning algorithms can be utilized to predict the porosity distribution in the part. In this study, a first approach for the prediction of keyhole porosity in a cylindric specimen from AISI 316L stainless steel is presented. It is based on data augmentation using the “SmoteR” algorithm [2] to cure the dataset imbalance and a 1-dimensional convolutional neural network. [1] C.S. Lough et al., Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared thermal feature porosity probability maps. Journal of Materials Processing Technology, 302, p. 117473 (2022) https://dx.doi.org/10.1016/j.imatprotec.2021.117473 [2] L. Torgo et al., SMOTE for Regression. Progress in Artificial Intelligence, Chapter 33, p. 378-289 (2013) https://dx.doi.org/10.1007/978-3-642-40669-0_33 T2 - KI-Tag Arbeitskreis Chemometrik & Qualitätssicherung - Chemometrics meets Artificial Intelligence CY - Berlin, Germany DA - 01.04.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - Defect Prediction KW - Convolutional Neural Networks PY - 2022 AN - OPUS4-54621 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 - 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 - Lapšanská, Ivana T1 - Passive Thermografie als Inspektionsinstrument für Rotorblätter von Windkraftanlagen im Betrieb N2 - Der „European Green Deal“ und der globale Kampf gegen den Klimawandel erfordern mehr und größere Windkraftanlagen. Um dem steigenden Bedarf an Wartung und Inspektion zu bedienen, werden neben der „klassischen“ Inspektion durch Industriekletterer zunehmend auch halb autonome Methoden der Ferninspektion entwickelt. Die BAM arbeitet in mehreren Projekten an der Detektion sowohl inneren als auch oberflächlichen Schäden mittels bodenbasierter passiver Thermografie. Passive Thermografie hat den Vorteil, dass die Sonne als Wärmequelle genutzt wird und so sehr große Objekte ohne direkten Zugriff untersucht werden können. Dies erlaubt eine Inspektion von Rotorblättern von Windenergieanlagen im laufenden Betrieb. Das verhindert Ausfallzeiten und Umsatzeinbußen im Vergleich zu herkömmlichen Blattinspektionen. Neben der Automatisierung der Aufnahmetechnik stehen zwei wissenschaftliche Fragestellungen im Fokus der aktuellen Arbeiten. Auf der einen Seite sind Inspektionen mit passiver Thermografie und deren Ergebnisse stark wetterabhängig. Deswegen bedarf es der einem guten Verständnis dieser Abhängigkeit und einer Kopplung von Simulationen und experimentellen Daten. So kann gezeigt werden, welche Defekte in Rotorblätter passive Thermografie bei welchen Wetterbedingungen sichtbar macht. Auf der anderen Seite sind die Auswertung und Interpretation der schnell erfassten Inspektionsergebnisse zeitaufwendig und verlangen gute Kenntnisse der Thermografie. Um hier praxistauglicher zu werden, arbeitet die BAM an der Erstellung von Algorithmen, die eine Vorauswahl und -interpretation der Inspektionsdaten mit künstlicher Intelligenz ermöglichen. In dem Beitrag wird der messtechnische Aufbau zur bodenbasierten passiven Thermografie an Rotorblättern, der Vergleich von Simulationsdaten und Feldmessungen sowie die Arbeiten bezüglich der KI-basierten Auswertung von thermografischen Aufnahmen gezeigt. T2 - DGZfP Jahrestagung 2024 CY - Osnabrück, Germany DA - 06.05.2024 KW - Wind KW - Windrad KW - Rotorblatt KW - Thermography KW - Thermografie KW - Rotorblade PY - 2024 AN - OPUS4-62500 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Chaudhuri, Somsubhro T1 - Passive infrared thermography as an inspection tool for operational wind turbine rotor blades N2 - The growing wind energy infrastructure presents a significant challenge in the maintenance and operation of wind turbines (WT) and their intricate components. An important aspect of WT maintenance is the inspection of wind turbine rotor blades (WTB) to ensure the overall health and safety of the turbine. This inspection process involves both visual and mechanical examinations of the blades to identify any indicators of damage or wear that could compromise their performance and, consequently, the structural integrity of the entire WT system. The complexity of WTBs is compounded by their ever-expanding dimensions, exceeding 100 meters in length for 16 MW WT systems, and their multi-material composition. Within this context, passive infrared thermography emerges as a potential alternative to conventional contact- or proximity-based inspection methods. Unlike active thermography, passive thermography uses solar radiation and ambient temperature variation for thermal contrast, eliminating the need for traditional heat lamps, flash, or laser-based techniques. A novel inspection method has been developed to semi-autonomously assess wind turbine blades (WTBs) while the wind turbine (WT) is operational, from ground level. This approach leverages optimal thermal contrast, which depends on prevailing weather conditions during field measurements, enabling the visualization of both external and internal features of the WTBs through post-processing techniques. In this study, thermal data obtained through passive thermography is compared with contemporaneous visual imagery to definitively classify observed features in thermal images as either surface or sub-surface features. This analysis, coupled with corresponding weather conditions, provides valuable insights into the capabilities and limitations of the inspection technique. Additionally, finite-element-based (FE) thermal simulations of a WTB section are employed to parametrically assess the influence of weather conditions, beyond those observed during field measurements, based on a validated model. In addition, the thermal images also consist of thermal signatures of leading-edge turbulence due to possible leading-edge erosion in WTBs. These are primarily vortices, and their shape and size depend on the morphology of the damage as well as the rotational speed of the WTBs. The inspections are accompanied by automatic data evaluation of the thermal signatures. To improve the precision of erosion damage identification, a fully convolutional network (FCN) is employed, trained, and tested using over 1000 annotated thermographic blade images. Additionally, the study introduces strategies for grouping smaller damage indications and simplification rules based on realistic thermal imaging resolutions. As leading-edge erosion could potentially lead to annual energy production (AEP) losses, this technique could prove to be a powerful tool in establishing the presence of damage and the resulting AEP loss. T2 - 20th World Conference on Non-Destructive Testing CY - Incheon, South Korea DA - 27.05.2024 KW - Non-destructive testing KW - Thermografie KW - Wind turbine rotor blades KW - Windenergie Anlage Rotorblätter KW - Thermography PY - 2024 AN - OPUS4-60695 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien 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 - JOUR A1 - Mohr, Gunther A1 - Altenburg, Simon A1 - Hilgenberg, Kai T1 - On the limitations of small cubes as test coupons for process parameter optimization in laser powder bed fusion of metals N2 - The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given. T2 - Icaleo 2023 CY - Chicago, IL, USA DA - 16.10.2023 KW - Additive manufacturing KW - Heat accumulation KW - Thermal history KW - In situ monitoring KW - Representative specimens KW - Thermography PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586558 DO - https://doi.org/10.2351/7.0001080 SN - 1042-346X VL - 35 IS - 4 SP - 1 EP - 10 AN - OPUS4-58655 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 - THES A1 - Lecompagnon, Julien T1 - Nondestructive defect characterization using full-frame spatially structured super resolution laser thermography N2 - Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction. Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL). In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x). Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods. N2 - Die laserbasierte aktive thermografische Prüfung als berührungslose Methode der zerstörungsfreien Werkstoffprüfung (NDT) basiert auf der aktiven Erwärmung des Testobjekts (OuT) und Messung des resultierenden Temperaturanstiegs mit einer Infrarotkamera. Dadurch bedingt können systematische Abweichungen vom vorhergesagten Erwärmungsverhalten Aufschluss über dessen innere Struktur geben. Jedoch ist das Auflösungsvermögen für innenliegende Defekte durch die diffusive Natur der Wärmeleitung in Festkörpern begrenzt. Thermografische Super-Resolution (SR)-Methoden zielen darauf ab, diese Limitation durch die Kombination mehrerer Messungen mit jeweils unterschiedlicher strukturierter Erwärmung und mathematischer Optimierungsmethoden zu überwinden. Zur Rekonstruktion innerer Defekte mithilfe thermografischer SR-Rekonstruktionsmethodik wird für die Gesamtheit mehrerer Messungen ein schlecht gestelltes und stark regularisiertes inverses mathematisches Problem gelöst, was in einer dünnbesetzten Karte der internen Defektstruktur des OuTs resultiert. Die Inversion mittels iterativer numerischer Minimierungsverfahren profitiert dabei von einzelnen Annahmen wie der vergleichsweisen Seltenheit von Materialdefekten. Nachdem die Methode bisher experimentell fast ausschließlich auf eindimensionale Messbereiche (ROIs) beschränkt war, zielt diese Arbeit auf eine Erweiterung zur Prüfung zweidimensionaler ROIs mit arbiträren Defektverteilungen bei erträglicher experimenteller Komplexität ab. Ziel ist es, durch die Weiterentwicklung des Technologie-Reifegrades (TRL) den Technologietransfer zur industriellen Anwendung zu ermöglichen. Hierzu werden erst die numerische Erweiterung der SR-Rekonstruktionsmethodik für zweidimensionale ROIs erörtert und zwei neue Algorithmen zur Invertierung des zugrunde liegenden inversen Problems vorgestellt, sowie eine Vorwärtslösung des inversen Problems entwickelt. In Verbindung mit einem neuartigen Algorithmus zur automatisierten Bestimmung der (optimalen) Regularisierungsparameter wird erstmals die Möglichkeit geschaffen, analytische Simulationen zum Einfluss einzelner Parameter auf die erreichbare Rekonstruktionsqualität durchzuführen. Weiterhin wird der experimentelle Ansatz zur Prüfung zweidimensionaler ROIs erweitert. Mehrere Messkampagnen validieren die eingeführten Inversionsalgorithmen, die Vorwärtslösung und zwei exemplarische analytische Studien. Für die experimentelle Umsetzung wird erstmals die Verwendung lasergekoppelter DLP-Technologie für die makroskopische thermografische Prüfung nutzbar gemacht, welche die Projektion großflächiger binärer Pixelmuster ermöglicht. Dadurch kann die Anzahl der erforderlichen Messungen pro ROI ohne Qualitätseinbußen erheblich reduziert werden (bis zu 20x). Abschließend werden die erzielten Rekonstruktionsergebnisse der internen Defektstruktur eines speziell angefertigten OuTs qualitativ und quantitativ mit auf homogener Erwärmung basierenden etablierten Methoden der thermografischen Prüfung verglichen. Hier zeigt sich, dass die weitgehend rauschfreien SR-Rekonstruktionsergebnisse alle Defektrekonstruktionen der betrachteten Referenzmethoden deutlich übertreffen. KW - Nondestructive testing KW - Zerstörungsfreie Prüfung KW - Thermography KW - Thermografie KW - Super resolution KW - Structured illumination KW - Strukturierte Beleuchtung KW - Defect characterization KW - Defektcharakterisierung KW - DMD KW - DLP PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-588296 DO - https://doi.org/10.14279/depositonce-19271 SP - 1 EP - 154 PB - Technische Universität Berlin CY - Berlin AN - OPUS4-58829 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien T1 - Nondestructive defect characterization using full frame spatially structured super resolution laser thermography N2 - Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction. Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of twodimensional ROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL). In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x). Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free twodimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods. T2 - Öffentliche wissenschaftliche Aussprache an der Technischen Universität Berlin CY - Berlin, Germany DA - 31.10.2023 KW - Thermography KW - Super resolution KW - NDT KW - Material testing KW - Internal defects KW - DMD KW - DLP PY - 2023 AN - OPUS4-58771 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Junker, Birgit A1 - Stamm, Michael T1 - No downtime thermographic rotor blade inspection N2 - In this presentation, the KI-VISIR Reference Dataset, created by the Bundesanstalt für Materialforschung und -prüfung (BAM) will be discussed. It includes thermographic and visual inspection data of 30 operational wind turbines. This dataset aims to support the maintenance and inspection of wind turbines, which are increasingly being built across Germany and Europe. The data is publicly available and helps in the development of digital methods for damage classification and inspection. T2 - AMI Wind Turbine Blades CY - Düsseldorf, Germany DA - 10.12.2024 KW - Thermography KW - Wind Turbine Blades KW - AI KW - KI-VISIR KW - NDT PY - 2024 AN - OPUS4-62498 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien T1 - New options for finding defects on and below the surface using structured laser thermography N2 - In infrared thermography, the interaction of the heat flow with the internal geometry or inhomogeneities in a sample and their effect on the transient temperature distribution is used, e.g., to detect defects non-destructively. An equivalent way of describing this is the propagation of thermal waves inside the sample. Although thermography is suitable for a wide range of inhomogeneities and materials, the fundamental limitation is the diffuse nature of thermal waves and the need to measure their effect radiometrically at the sample surface only. The crucial difference between diffuse thermal waves and propagating waves, as they occur, e.g., in ultrasound, is the rapid degradation of spatial resolution with increasing defect depth. This degradation usually limits the applicability of thermography for finding small defects on and below the surface. A promising approach to improve the spatial resolution and thus the detection sensitivity and reconstruction quality of the thermographic technique lies in the shaping of these diffuse thermal wave fields using structured laser thermography. Some examples are: • Narrow crack-like defects below the surface can be detected with high sensitivity by superimposing several interfering thermal wave fields, • Defects very close to each other can be separated by multiple measurements with varying heating structures, • Defects at different depths can be distinguished by an optimized temporal shaping of the thermal excitation function, • Narrow cracks on the surface can be found by robotic scanning with focused laser spots. We present the latest results of this technology obtained with high-power laser systems and modern numerical methods. T2 - 20th World Conference on Non-Destructive Testing (WCNDT) CY - Incheon, Korea DA - 27.05.2024 KW - Thermography KW - Laser KW - NDT KW - Super-Resolution KW - DLP KW - DMD PY - 2024 AN - OPUS4-60172 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lecompagnon, Julien T1 - New methods of thermographic super resolution with structured laser heating N2 - Thermographic NDT 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. Our studies deal with the application of fully 2D-structured DMD-based excitation and subsequent super-resolution-based defect reconstruction. We analyze the influence of different testing parameters, like the number of measurements or the white content of the excitation pattern. Furthermore, we have dealt with the choice of parameters in the reconstruction that have an influence on the underlying minimization problem in terms of compressed sensing. Finally, the results of the super resolution reconstruction are compared with the results based on conventional thermographic testing methods. T2 - 20th World Conference on Non-Destructive Testing (WCNDT) CY - Incheon, Korea DA - 27.05.2024 KW - Thermography KW - Laser KW - NDT KW - Super-Resolution KW - DLP KW - DMD PY - 2024 AN - OPUS4-60171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - Multispectral in-situ monitoring of a L-PBF manufacturing process using three thermographic camera systems N2 - The manufacturing of metal parts for the use in safety-relevant applications by Laser Powder Bed Fusion (L-PBF) demands a quality assurance of both part and process. Thermography is a nondestructive testing method that allows the in-situ determination of the thermal history of the produced part which is connected to the mechanical properties and the formation of defects [1]. A wide range of commercial thermographic camera systems working in different spectral ranges is available on the market. The understanding of the applicability of these cameras for qualitative and quantitative in-situ measurements in L-PBF is of vital importance [2]. In this study, the building process of a cylindrical specimen (Inconel 718) is monitored by three camera systems simultaniously. These camera systems are sensitive in various spectral bandwidths providing information in different temperature ranges. The performance of each camera system is explored in the context of the extraction of image features for the detection of defects. It is shown that the high temporal and thermal process dynamics are limiting factors on this matter. The combination of different spectral camera systems promises the potential of an improved defect detection by data fusion. T2 - LASER SYMPOSIUM & ISAM 2021 CY - Online meeting DA - 07.12.2021 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Defect detection PY - 2021 AN - OPUS4-54141 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Becker, Tina T1 - Multi measurand in-situ monitoring of the laser powder bed fusion process by means of multispectral optical tomography N2 - Laser Powder Bed Fusion (L-PBF), as one of the most promising production process in the field of metal additive manufacturing, enables traditional constructive solutions to be rethought and the manufacturing of optimized components according to the "form follows function" principle. The most significant obstacle for a broad industrial application of the L-PBF process is the inadequate quality assurance during the manufacturing process so far, leading to high production costs. Although several mainly camera based commercial in-process monitoring systems are already available, a deep understanding of the interpretation of the monitored data and correlation with actual defects is still lacking. One reason for this is the reduction of the complex process signature to just one measurement value. The focus of this contribution is the presentation of the multispectral optical tomography as alternative to single measurand in-situ monitoring systems. The potential of this approach is hereby shown on L-PBF printed samples with induced process instabilities. Beyond that, an in-house developed L-PBF printer for further testing of multi-sensor in-situ monitoring systems is presented. T2 - ICAM2021 CY - Online meeting DA - 01.11.2021 KW - In-situ monitoring KW - L-PBF KW - Optical tomography KW - 3d printing KW - Thermography PY - 2021 AN - OPUS4-54388 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon T1 - Measurement of real temperatures in metal powder bed fusion: Hyperspectral thermography N2 - Detailed knowledge about the physics of the PBF-LB/M process is still lacking, and the simulation of the fast and small-scale process is challenging. Especially the experimental validation of complex simulations lacks a suitable measurement technique for temperature distributions at high speeds and spatial resolution. The complicated process physics, specifically the rapidly changing emissivity in and around the meltpool, pose a severe challenge for usual thermographic approaches. Here, we present first results of a hyperspectral measurement approach to reconstruct temperature and emissivity maps during the PBF-LB/M process in a custom manufacturing machine. The camera setup measures the thermal radiation of the process along a line at a rate of 20 kHz, spectrally resolved between 1 µm and 1.6 µm. When the meltpool travels perpendicularly across this line, a typical meltpool can be reconstructed by pointwise fitting for temperature emissivity separation, based on typical spectral emissivities from reference measurements. T2 - Lasers in Manufacturing Conference - LiM CY - Munich, Germany DA - 23.06.2025 KW - PBF-LB/M KW - In situ monitoring KW - Thermography KW - Additive Manufacturing KW - Process monitoring KW - Hyperspectral PY - 2025 AN - OPUS4-63564 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, 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 - CONF A1 - Altenburg, Simon T1 - Machine Learning and Thermography as Tools for Local Porosity Prediction in AM of Metals N2 - Quality assurance of metal additive manufacturing (PBF-LB/M) is still a challenge. Offering deep process insights, thermography is a well-suited monitoring technique. Here, we show how machine learning based on thermographic data enables a local part porosity prediction. T2 - Laser Applications Conference (LAC) CY - Prague, Czech Republic DA - 19.10.2025 KW - PBF-LB/M KW - In situ monitoring KW - Thermography KW - Additive Manufacturing KW - Process monitoring KW - Porosity prediction KW - Machine Learning KW - Feature extraction PY - 2025 AN - OPUS4-64669 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -