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 - THES A1 - Klewe, Tim T1 - Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar N2 - In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed. First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations. Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter. An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data. For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research. Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases. KW - NDT KW - Moisture measurement KW - Ground penetrating radar KW - Building floor PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-591044 DO - https://doi.org/10.14279/depositonce-19306 SP - 1 EP - 146 PB - Technische Universität Berlin CY - Berlin AN - OPUS4-59104 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Mishurova, Tatiana T1 - Influence of residual stress and microstructure on mechanical performance of LPBF TI-6AL-4V N2 - Additive manufacturing technologies provide unique possibilities in the production of topologically optimized, near-net shape components. The main limiting factors affecting the structural integrity of Laser Powder Bed Fusion (LPBF) parts are manufacturing defects and residual stress (RS) because both of them are virtually inevitable. Taking into account the complex thermal history of LPBF materials, a prediction of the material behavior is not possible without experimental data on the microstructure, defect distribution, and RS fields. Therefore, this thesis aims to understand the factors that influence the LPBF Ti-6Al-4V material performance the most, covering both the production and the post-processing steps of manufacturing. Indeed, a parametric study on the influence of manufacturing process and post-processing on RS, defects and microstructure was performed. It was found that the volumetric energy Density (EV), commonly used for the LPBF process optimization, does neither consider the pore shapes and distribution, nor the influence of individual parameters on the volume fraction of pores. Therefore, it was recommended not to use EV without great care. It was shown that the Position on the base plate has a great impact on the amount of RS in the part. The micromechanical behavior of LPBF Ti-6Al-4V was also studied using in-situ Synchrotron X-ray diffraction during tensile and compression tests. Diffraction elastic constants (DEC), connecting macroscopic stress and (micro) strain, of the LPBF Ti-6Al-4V showed a difference from the DEC of conventionally manufactured alloy. This fact was attributed to the peculiar microstructure and crystallographic texture. It was therefore recommended to determine experimentally DECs whenever possible. Low Cycle Fatigue (LCF) tests at a chosen operating temperature were performed to evaluate the effect of post-treatment on the mechanical performance. Through the information on the microstructure, the mesostructure, and the RS, the LCF behavior was (indirectly) correlated to the process parameters. It was found that the fatigue performance of LPBF samples subjected to hot isostatic pressing is similar to that of hot-formed Ti-6Al-4V. The tensile RS found at the surface of LPBF as-built samples decreased the fatigue life compared to the heat-treated samples. The modification of the microstructure (by heat treatment) did not affect the Fatigue performance in the elastic regime. This shows that in the absence of tensile RS, the manufacturing defects solely control the failure of LPBF components and densification has the strongest effect on the improvement of the mechanical performance. KW - Additive manufacturing KW - Ti-6Al-4V KW - Residual stress KW - Computed tomography PY - 2021 SP - 1 EP - 143 CY - RWTH Aachen AN - OPUS4-54389 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Laquai, René T1 - Extending synchrotron X-ray refraction imaging techniques to the quantitative analysis of metallic materials N2 - In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials. SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size. So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray Transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified. For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3% can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible. N2 - In der vorliegenden Arbeit werden die zwei, auf Refraktion basierende, Röntgenbildgebungsverfahren Synchrotron Röntgen-Refraktions Radiographie (engl.: SXRR) und Synchrotron Röntgen-Refraktions Computertomographie (engl.: SXRCT) für die quantitative Analyse von Rissen und Porosität in metallischenWerkstoffen angewandt. SXRR und SXRCT nutzen die Refraktion von Röntgenstrahlen an inneren Oberflächen des Materials, z.B. die Oberflächen von Rissen und Poren, zur Bildgebung. Beide Methoden sind daher empfindlich gegenüber kleineren Defekten als ihre auf Röntgenabsorption basierenden Gegenstücke, Röntgenradiographie und Röntgen-Computertomographie. Sie sind in der Lage Defekte von nanometrischer Größe zu detektieren. Bislang wurden die Methoden für die Analyse von keramischen Werkstoffen und faserverstärkten Kunststoffen eingesetzt. Die Analyse von metallischenWerkstoffen benötigt höhere Photonenenergien benötigt werden um eine ausreichende Transmission zu erreichen. Dies hat kleinere Refraktionswinkel, und damit geringeren Bildkontrast, zur Folge, da der Brechungsindex von der Photonenenergie abhängt. Hier wird erstmals eine umfassende Studie vorgelegt, welche die Möglichkeiten zur Untersuchung metallischer Werkstoffe mittels SXRR und SXRCT untersucht. Es wird gezeigt, dass der geringere Kontrast, verursacht durch die kleineren Refraktionswinkel, überwunden werden kann. Somit ist die einzig verbleibende Beschränkung die erreichbare Transmission, die alle Röntgenbildgebungsverfahren gemeinsam haben. Darüber hinaus wird ein Modell für die quantitative Auswertung der inneren Oberflächen präsentiert und verifiziert. Zu diesem Zweck werden vier Fallstudien durchgeführt, wobei jede eine spezifische Herausforderung darstellt. In Fallstudie A werden Risse in einer Probe aus einer Aluminiumschweißnaht untersucht. Diese Fallstudie dient hauptsächlich dazu das Modell für die quantitative Analyse zu verifizieren und die Empfindlichkeit gegenüber Strukturen unterhalb des Auflösungsvermögens zu beweisen. In Fallstudie B wird die Entwicklung der Schädigung in einem aluminiumbasierten partikelverstärktem Metall-Matrix Komposit untersucht. Dabei wird die Genauigkeit und Wiederholbarkeit der SXRR Messungen analysiert und es wird gezeigt das Messfehler kleiner 3% erreicht werden können. Darüber hinaus wird in Fallstudie B erstmals SXRR in Kombination mit in-situ Zugbelastung eingesetzt. Fallstudie C ist aus dem hochaktuellen Bereich der additive Fertigung. Hier wird Porosität in additiv gefertigtem Ti-Al6-V4 analysiert mit besonderem Augenmerk auf der Morphologie der Poren. Es wurde ein Verfahren zur Klassifizierung, basierend auf SXRR Messungen, erfunden, welches Bindefehler und Poren voneinander unterscheiden kann auch wenn die Defekte nicht räumlich aufgelöst werden können. In Fallstudie D wird SXRCT zur Analyse von wasserstoffunterstützter Rissbildung in Stahl angewandt. Wegen der hohen Röntgenschwächung des Stahls muss hier mit 50 keV eine vergleichsweise hohe Photonenenergie genutzt werden. Dadurch zeigen die Daten ein erhöhtes Rauschen und geringeren Kontrast verglichen mit den anderen Fallstudien. Allerdings ist es, trotz der geringeren Datenqualität, möglich das Auftreten von Rissen in Abhängigkeit der Wasserstoffkonzentration und mechanischen Belastung zu untersuchen. KW - Synchrotron X-ray refraction computed tomography KW - Lean duplex steel X2CrMnNiN21-5-1 KW - hydrogen embrittlement KW - Metal-matrix composite KW - Al6061 KW - Ti-Al6-V4 KW - In-situ tensile test PY - 2022 SP - 1 EP - 71 AN - OPUS4-54385 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Lugovtsova, Yevgeniya T1 - Damage detection in multi-layered plates using ultrasonic guided waves N2 - This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time. KW - Lamb waves KW - Composites KW - Structural Health Monitoring KW - Inverse procedure KW - Scaled Boundary Finite Element Method PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:bsz:291--ds-382863 DO - https://doi.org/10.22028/D291-38286 SP - 1 EP - 131 PB - SciDok - Der Wissenschaftsserver der Universität des Saarlandes CY - Saarbrücken, Germany AN - OPUS4-57058 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Breese, Philipp Peter T1 - Additive Manufacturing with In-situ Measurement and Closed-loop Control for the Powder Flow in Laser Metal Deposition N2 - The powder mass flow rate is one of the three main factors directly influencing geometry and quality in the Additive Manufacturing (AM; also 3D printing) process of Laser Metal Deposition (LMD), also known as Directed Energy Deposition (DED-LB/M). However, the pneumatic transport of the metal powder lacks stability, repeatability, and traceability. There is currently no reliable in-situ measurement of the mass flow rate available in industry. As a result, time-consuming powder flow measurements before the manufacturing are typical while no recording or feedback takes place during the manufacturing. Based on this problem statement, this thesis introduces a holistic approach for in-situ measurement and closed-loop control of pneumatic powder flows. For the in-situ measurement, a widely available nonintrusive optoelectronic sensor was used. Found mathematical dependencies reliably convert the sensor output into a powder mass flow rate dependent on powder parameters and feeding conditions. Therefore, the model is usable with various powder types while achieving a Mean Relative Error (MRE) of less than 4% at 125 Hz. Similarly, a model was introduced for the powder velocity using a second sensor further downstream. This provided insight into the powder’s movement while the model achieved an MRE of less than 3%. As a second main research endeavor, the sensor output was used to implement and investigate a closed-loop powder flow control on a vibration feeder. PID controller gains were calculated empirically at set operating points for the nonlinear system. Again, a usage with various metal powders is possible as the influences of powder parameters and feeding conditions were investigated and incorporated into the model. In addition, the dependence on the previous powder flow (memory effect) was factored in as well. With this, faster recovery from blockages and a reduction in standard deviation during steady state feeding by more than 20% were demonstrated. Complementary numerical CFD simulations investigated the effect of the carrier gas flow rates on powder flow homogeneity and powder particle size separations. A second modeling approach demonstrated the use of machine learning with the optoelectronic sensor output. A 1D convolutional neural network (CNN) was shown to be able to predict the powder flow with a Weighted Absolute Percentage Error (WAPE) of less than 4% compared to the actual flow. With this, the model’s capability to detect slightly elevated moisture (at <0.4wt%) in the powder as well as differences in particle size distribution was proven on in-situ data from powder feeding. Finally, the methods were validated on the LMD process by additively manufacturing test components. The active closed-loop powder flow control shows a significant improvement in repeatability for LMD. The in-situ measurement allows a monitoring of the powder mass flow rate with the recorded data throughout the entire AM process. In addition, Scanning Electron Microscopy (SEM) images showed potential benefits at the microscopic level like reduced defects. With this, the whole chain for a powder flow improvement method was investigated, implemented, and validated in the context of Laser Metal Deposition. Furthermore, a high potential for retrofitting is given while at low cost. This lays the foundation for a more traceable and digital AM process in industry leading to repeatable and safe products. KW - Pneumatic powder flow KW - Direct Energy Deposition KW - DED-LB/M KW - 3D printing KW - In-situ monitoring PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-650261 DO - https://doi.org/10.14279/depositonce-23032 SP - 1 EP - 198 PB - TU Berlin CY - Berlin AN - OPUS4-65026 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -