8.3 Thermografische Verfahren
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Since laser powder bed fusion (PBF-LB/M) is prone to the formation of defects during the building process, a fundamental requirement for widespread application is to find ways to assure safety and reliability of the additively manufactured parts. A possible solution for this problem lies in the usage of in-situ thermographic monitoring for defect detection. In this contribution we investigate possibilities and limitations of the VIS/NIR wavelength range for defect detection. A VIS/NIR camera can be based on conventional silicon-based sensors which typically have much higher spatial and temporal resolution in the same price range but are more limited in the detectable temperature range than infrared sensors designed for longer wavelengths. To investigate the influence, we compared the thermographic signatures during the creation of artificially provoked defects by local parameter variations in test specimens made of a nickel alloy (UNS N07208) for two different wavelength ranges (~980 nm and ~1600 nm).
Many laboratories have been working about Active Thermography
as a Non Destructive Testing method for many
years. This method can be applied on metallic or composites
materials for surface or subsurface defects. Thus, many
different configurations can be encountered to measure the
heat distribution and generate heat flow into the part. Signal
processing is also widely used to improve the performance
of detection.
After encouraging results, aerospace, automotive and energy
industries are now involved into industrialization of the
technology to apply it for production or maintenance applications.
Good practices and common wording are often
required by end-user to qualify the process.
Since the beginning of the 2000s, a working group was
founded within CEN/TC138 'Non-destructive Testing' to define standards in thermography, in the European Committee
for Standardization (CEN). Some other actors have also produced
standards (ISO, IEC, ASTM...).
This paper aims to list the standards currently available about
thermography and the associatd vocabulary. It describes
the generic terms to be used in active and passive thermography
(operating modes, reference blocks, reporting…) and
also more specific elements about laser and induction thermography
for example.
It will also put in perspective the further works to be done
in the next few years to take into account the new trends in
active thermography and how to qualify for industrial applications.
Mit der zunehmenden Relevanz der additiven Fertigung in Fertigungsbereiche mit hohen Anforderungen an Bauteilqualität, wird eine gute Prozessüberwachung unausweichlich. Eine Methode, die bereits gute Korrelation mit Bauteilfehlern gezeigt hat, ist die Temperaturüberwachung mithilfe von thermografischen Methoden. Allerdings unterliegt die Bestimmung der Realtemperaturen vielen unterschiedlichen Problemen. Ein Ansatz mit den Herausforderungen umzugehen, stellt der multispektrale Ansatz dar, der im Projekt QT-LPA untersucht und hier vorgestellt wird.
Robotic-assisted 3D scanning and laser thermography for crack inspection on complex components
(2024)
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.
Many laboratories have been working about Active Thermography as a Non Destructive Testing method for many years. This method can be applied on metallic or composites materials for surface or subsurface defects. Thus, many different configurations can be encountered to measure the heat distribution and generate heat flow into the part. Signal processing is also widely used to improve the performance of detection. After encouraging results, aerospace, automotive and energy industries are now involved into industrialization of the technology to apply it for production or maintenance applications. Good practices and common wording are often required by end-user to qualify the process. Since the beginning of the 2000s, European Committee for Standardization (CEN) has launched a Working Group within CEN/TC138 to define standards in thermography. Some other actors have also produced standards (ISO, IEC, ASTM,..). This goal of this presentation is to present a status of the standard currently available about thermography and the associated vocabulary. It describes the generic terms to be used in active and passive thermography (operating modes, reference blocks, reporting,…) and also more specific elements about laser and induction thermography for example. It will also put in perspective the further works to be done in the next few years to take into account the new trends in active thermography and how to qualify for industrial applications.
Infrared thermography (IRT) using a focused laser is effective for surface defect detection. Nevertheless, testing complex‐shaped components remains a challenging task. The state‐of‐the‐art focuses on testing a limited region of interest rather than the full sample. Thus, detection and location of surface defects has been less researched. Most attempts require a manual scan of the full sample, which makes it hard to reconstruct the full scanned surface. Here, we introduce a reliable workflow for crack detection and semi‐automated inspection of complex‐shaped components using IRT excited with a laser line. A 6‐axis robot arm is used for moving the sample in front of the setup. This approach has been tested on a section of a rail and a gear, both containing defects due to heavy use. Crack detection is based on the segmentation of thermograms obtained by Fourier transform of sorted temperatures. Moreover, texture mapping is used to visualize a reconstructed thermogram on the 3D model of the sample. Our approach illustrates a reliable process towards the digitalization of thermographic testing.
Additive manufacturing (AM, also known as 3D printing) of metals is becoming increasingly important in industrial applications. Reasons for this include the ability to realize complex component designs and the use of novel materials. This distinguishes AM from conventional manufacturing methods such as subtractive manufacturing (turning, milling, etc.). The most widely used AM process for metals is laser powder bed fusion (PBF-LB/M, also known as selective laser melting SLM). Currently, it has the highest degree of industrialization and the largest number of machines in use. In PBF-LB/M, the feedstock is present as metal powder in an inert gas atmosphere inside a process chamber where a laser melts it locally. By repeatedly lowering the build platform, applying a new layer of powder, and then selectively melting it with the laser, a component is built up layer by layer. The local temperature distributions that occur during this process determine not only the properties of the finished component, but also the possible formation of defects such as pores and cracks. Due to the high relevance of the thermal history for precise geometries and defect formation, a temporally and spatially resolved measurement of quantitative (or real/actual) temperatures would be optimal. Quantitative values would ensure comparability and repeatability of the AM process which would also positively affect the quality and safety of the manufactured component. Furthermore, it would also contribute to the validation of simulations and to a deeper understanding of the manufacturing process itself.
At present, however, only qualitative monitoring of the thermal radiation is performed (e.g., by monitoring the melt pool using a photodiode), and safety-relevant components must be inspected ex situ afterwards which is time-consuming and costly. A reason for the lack of quantitative temperature data from the process are the challenging conditions of the PBF-LB/M process with high scanning speeds and a small laser spot diameter. Furthermore, the emissivity of the surface changes at high dynamics (temporally/spatially) as well as with temperature and wavelength. This specifically makes contactless temperature determination based on emitted infrared radiation challenging for PBF-LB/M. Although classical thermography offers very good qualitative insights, it is not sufficient for a reliable quantitative temperature determination without a complex temperature calibration including image segmentation and assignment of previously determined emissivities.
For this reason, this publication presents the hyperspectral thermography approach for the PBF-LB/M process: The emitted infrared radiation is measured simultaneously at many adjacent wavelengths. In this study, this is realized via a fast hyperspectral line camera that operates in the short-wave infrared range. The thermal radiation of a line on the target is spectrally dispersed and detected to measure the radiant exitance along that line. If the melt pool of the PBF-LB/M process moves through this line at a sufficient frame rate, a spatial reconstruction of an effective melt pool is possible.
One approach to determine the desired emissivities and the quantitative temperature from this hyperspectral data are temperature-emissivity separation (TES) methods. A major problem is that n spectral measurements are available, but n+1 parameters are required for each image pixel (n emissivity values + one temperature value). TES methods offer the possibility to approximate this mathematically underconstrained problem in a reliable and traceable way by analytically parameterizing the spectral emissivity with a few degrees of freedom. Using this approach, setup and method are applied to a research machine for PBF-LB/M, called SAMMIE (Sensor-based Additive Manufacturing Machine). First results under AM process conditions are shown which form the basis for the determination of quantitative temperatures in the PBFLB/M process. This marks an important contribution to improving the comparability and repeatability of production, validating simulations, and understanding the process itself. When fully developed and validated, the presented method can also provide reference measurements to evaluate and optimize other, more practical monitoring methods, such as melt pool monitoring or optical tomography. In the long run, this will help to increase confidence in the safety of AM products.
Die additive Fertigung (Additive Manufacturing AM, auch als 3D Druck bekannt) von Metallen nimmt einen stetig wachsenden Stellenwert in industriellen Anwendungen ein. Gründe dafür sind u.a. die Möglichkeit der Umsetzung komplexer Bauteildesigns und die Nutzung neuartiger Werkstoffe. Damit hebt sich AM von konventionellen Fertigungsmethoden wie der subtraktiven Fertigung (Drehen, Fräsen, etc.) ab. Das für Metalle am weitesten verbreitete AM-Verfahren ist das Laser-Pulverbettschweißen (Laser Powder Bed Fusion PBF-LB/M, auch als Selective Laser Melting SLM bekannt). Es besitzt aktuell den höchsten Industrialisierungsgrad und die größte Anzahl an eingesetzten Maschinen. Bei PBF-LB/M liegt der metallische Ausgangswerkstoff unter Inertgasatmosphäre innerhalb einer Prozesskammer in einem Bett als Pulver vor und ein Laser schmilzt dieses lokal auf. Durch wiederholtes Auftragen einer neuen Pulverschicht und anschließendes selektives Schmelzen mit Hilfe des Lasers findet der lagenweise Aufbau eines Bauteils statt. Die dabei auftretenden lokalen Temperaturverteilungen bestimmen sowohl die Eigenschaften des gefertigten Bauteils als auch das mögliche Auftreten von Defekten wie Poren oder Risse. Durch diese Relevanz der thermischen Historie wäre die Aufzeichnung der auftretenden Realtemperaturen in zeitlicher und räumlicher Abhängigkeit optimal. Mit quantitativen Werten wären Vergleichbarkeit und Wiederholbarkeit des AM-Prozesses gegeben, was sich auch positiv auf Qualität und Sicherheit des gefertigten Bauteils auswirkt. Außerdem wäre ein Beitrag zur Validierung von Simulationen sowie zur Gewinnung eines tieferen Verständnisses des Fertigungsprozesses gegeben.
Jedoch findet aktuell lediglich ein qualitatives Monitoring statt (bspw. mittels Überwachung des Schweißbades durch eine Photodiode) und sicherheitsrelevante Bauteile müssen zeit- und kostenaufwändig im Nachgang ex-situ geprüft werden. Grund dafür sind auch die herausfordernden Bedingungen des PBF-LB/M-Prozesses mit hohen Scangeschwindigkeiten bei geringem Durchmesser des Laserspots. Des Weiteren erschweren die auftretenden Emissionsgradänderungen mit hoher Dynamik (zeitlich, räumlich) und den gegebenen Abhängigkeiten (temperatur-/wellenlängenabhängig) eine berührungslose Temperaturbestimmung basierend auf emittierter Infrarotstrahlung deutlich. Klassische Thermografie bietet zwar sehr gute qualitative Einblicke, ist dabei jedoch ohne eine aufwändige Temperaturkalibrierung inklusive Bildsegmentierung und Zuweisung von vorher ermittelten Emissionsgraden für eine verlässliche Bestimmung der Realtemperatur nicht ausreichend. Aus diesem Grund wird in dieser Veröffentlichung der Ansatz der hyperspektralen Thermografie für den PBF-LB/M Prozess vorgestellt: Die emittierte Infrarotstrahlung wird gleichzeitig bei einer Vielzahl von benachbarten Wellenlängenbereichen gemessen. Dies wird in dieser Untersuchung mittels einer selbst zusammengestellten hyperspektralen Linienkamera, die im kurzwelligen Infrarotbereich arbeitet, realisiert. Hierbei wird die thermische Strahlung einer Linie auf dem Messobjekt spektral aufgespalten und detektiert, sodass die spektrale spezifische Ausstrahlung entlang dieser Linie vermessen werden kann. Bewegt sich das Schmelzbad des PBF-LB/M Prozesses bei ausreichender Bildfrequenz durch diese Linie, ist eine räumliche Rekonstruktion eines effektiven Schmelzbades möglich.
Ein Ansatz, um aus diesen hyperspektralen Daten die gesuchten Emissionsgrade sowie die Realtemperatur zu ermitteln, sind Methoden der Temperatur-Emissionsgrad-Separation (TES). Ein Hauptproblem besteht darin, dass n spektrale Messungen verfügbar sind, jedoch n+1 Kenngrößen für jeden Bildpixel gesucht werden (n Emissionsgrade + eine Temperatur). TES-Methoden liefern die Möglichkeit, dieses mathematisch unterbestimmte Problem verlässlich und nachvollziehbar zu approximieren, indem der spektrale Emissionsgrad mit wenigen Freiheitsgraden analytisch parametriert wird. Mit Hilfe dieses Ansatzes werden Setup und Methoden an SAMMIE (Sensor-based Additive Manufacturing Machine), einer Forschungsmaschine für PBF-LB/M, angewendet. Erste Ergebnisse unter AM-Prozessbedingungen werden gezeigt, welche die Grundlage für die Bestimmung von Realtemperaturen im PBF-LB/M-Prozess bilden. Dies leistet einen wichtigen Beitrag zur verbesserten Vergleichbarkeit und Wiederholbarkeit der Fertigung, zur Validierung von Simulationen sowie zum Verständnis des Prozesses selbst. Das unterstützt langfristig dabei das Vertrauen in die Sicherheit von AM-Produkten zu stärken.
In this work, we continue to develop and investigate the Thermal Shock Response Spectrum (TSRS) method as an alternative data processing method for infrared thermography (IRT). We focus on improving the current TSRS algorithm and present an optimization methodology for finding the optimal thermal Q-factor and characteristic frequency pair, which is based on the widely applied random sampling method. We show the qualitative relationship between the determined optimal characteristic frequency and the corresponding maximum difference in diffusion length between reference and defective models, as calculated by selecting a specific one-dimensional thermal N-layer model. The investigations were performed on an inhomogeneous plate made of carbon fiber reinforced polymer (CFRP) with artificial square defects at different depths. Furthermore, two different heat sources were used: a xenon flash lamp and a laser. These sources are not only distinct by their underlying physics but also generate inherently different pulse shapes. To quantitatively estimate the contrast between defect and non-defect areas, and to compare these results with commonly used infrared thermography (IRT) data post-processing methods such as Pulse Phase Thermography (PPT) and Thermographic Signal Reconstruction (TSR), the Tanimoto criterion (TC) and signal-tonoise ratio (SNR) were used.
Welded steel structures used in the offshore wind industry are exposed to harsh marine environments, which can result in corrosion-induced fatigue damage. Of particular concern is the heat affected zone (HAZ) of welded joints, a region known for its altered microstructure and mechanical properties, which can significantly influence the initiation and propagation of fatigue cracks. This study investigates the short and long fatigue crack growth rates, and the effect of seawater exposure, for the HAZ in S355 steel weldments. Single-edge notch bend (SENB) specimens are used, with a shallow notch in the HAZ. A series of specimens is immersed in synthetic seawater that is continuously circulated at a controlled temperature to assess the synergistic effects of corrosion and fatigue. The experimental method integrates a novel application of front face strain compliance for monitoring short cracks, alongside an extended back-face strain compliance approach for monitoring long crack propagation. It is concluded that the short fatigue crack growth rate of the HAZ is 2.7 to 3.5 times higher in seawater as compared to air. As the crack propagates and enters into the long crack regime, the ratio decreases to 2.2 times at the transition point of the two-stage crack growth curve and further decreases to 1.5 times when the notch advances towards fracture. The findings indicate that the fatigue crack growth rates documented in standards tend to be on the conservative side. This study significantly enriches the fatigue crack growth data available in literature, which will contribute to a more accurate lifetime assessment offshore wind turbine structures.
Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel and composite structures exposed to cyclic loads during their service life. Commonly used non-destructive techniques such as strain gauges, clip gauges, ultrasound, etc. used for detection and monitoring of fatigue damage are contact-based and perform local measurements. In addition, complex full-field techniques are commonly investigated, such as digital image correlation (DIC) and infrared thermography (IRT). In this work, a specific implementation of IRT, called lock-in IRT, is implemented for fatigue damage detection. This technique evaluates the thermal stress response of test specimens, specifically focusing or “locking-in” on the frequency of applied cyclic loads. Three different test scenarios are presented.
First, a section of a wind turbine rotor blade made of a glass fibre reinforced plastic (GFRP) shell structure under cyclic load was examined with Lock-In IRT along with DIC. The primary advantage of Lock-In IRT in this test setup was that it required no sample preparation, as compared to the painting and speckle pattern required for DIC. In the frequency domain, specifically the frequency of applied cyclic load, it was possible to extract local directional inhomogeneous loading within the shell structure due to progressive damage, confirmed with the deformation obtained from DIC results.
Second, thick welded specimens made of structural steel S355 were subjected to multiple NDT methods such as strain gauges, crack luminescence penetration (developed specifically at BAM), ultrasound, and IRT, with the aim of investigating the ability of each technique to detect fatigue damage initiation as early as possible in the total fatigue life of the specimen. Amongst the range of implemented techniques, Lock-In IRT provided the first indication of fatigue crack initiation at the weld toe of the specimens. This was validated with the other techniques as well as fractography.
Third, steel S355 specimens used to manufacture offshore wind turbine monopiles were tested. The specimens were extracted from a plate that was submerged in a marine environment, resulting in a corroded surface with corrosion pits. These specimens were subjected to cyclic tensile loads without removing the corrosion pits. The fatigue tests were monitored using IRT in a special full-field capturing setup that enables both sides of the specimen to be examined with one IRT camera. This allowed the entire pitted surface to be monitored for fatigue damage initiation at the same time. With the implementation of Lock In IRT, the surface stress distribution could be captured (the stress concentration at the pits), and fatigue crack initiation could be detected and linked with specific corrosion pits.
Passive infrared thermography as an inspection tool for operational wind turbine rotor blades
(2024)
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.
Anisotropy investigation of a single crystal superalloy using laser-spot infrared thermography
(2024)
Thermal property investigation of anisotropic materials such as single crystal superalloys are still in interest of practical and fundamental reasons but remains challenging using conventional testing methods. In this study, a single crystal superalloy is tested using laser-spot thermography, and its thermal anisotropy is investigated. Determining anisotropic thermal conductivity at microscopic scales is challenging, as it appears isotropic at the macroscopic scale. Infrared thermography is one of the best-known techniques for measuring material heat transfer properties and facilitating visualization of temperature distribution through the specimen. The proposed study uses the active thermography method of laser-spot infrared thermography, in which a laser spot is focused onto the sample surface and the thermal response is captured from the surface of the specimen with an infrared camera. A detailed analysis of temperature gradients and heat diffusion patterns aids in the measurement of thermal conductivity values along the sample's different crystallographic directions. The directional bonding characteristics and inherent crystallographic structure of the alloy account for the in-plane thermal conductivities calculated from experimental thermal measurements. The laser-spot thermography method has proven to be an effective tool for mapping the material's thermal conductivity anisotropy with high sensitivity and high spatial and temporal resolution. The investigation into the anisotropy of the material provides an insight into heat flow in the structure and helps in optimizing the design and overall performance of the material system.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a nondestructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. We study our proposed testing method along experiments carried out on a custom research PBF-LB/M machine using infrared (IR) cameras.
Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
Additive manufacturing is one of the most promising techniques for industrial production and maintenance, but the specifics of the layered structure must be considered. The Direct Energy Deposition-Arc process enables relatively high deposition rates, which is favourable for larger components. For this study, specimens with different orientations were prepared from one AISI316 steel block – parallel and orthogonal to the deposition plane. Quasistatic tensile loading tests were carried out, monitored by an infrared camera. The obtained surface temperature maps revealed structural differences between both orientations. The consideration of surface temperature transients yields more details about the behaviour of the material under tensile loading than the conventional stress-strain-curve. These preliminary investigations were supplemented by thermographic fatigue trials. Although the anisotropy was also observed during fatigue loading the fatigue behaviour in general was the same, at least for both inspected specimens. The presented results demonstrate the abilities and the potential of thermographic techniques for tensile tests.
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.
Die Integration von Automation und Robotik in die Prüfprozesse ermöglicht die
Untersuchung komplexer Bauteile. Diese Studie präsentiert die robotergestützte
Laserthermografie, um Risse in solchen Bauteilen zu identifizieren und analysieren. Diese Technik ermöglicht die automatisierte Rissprüfung welche im Vergleich zur Farbeindringprüfung auf viele, meist manuelle, Arbeitsschritte sowie die notwendigen Chemikalien verzichtet.
Zusätzlich wird ein automatisiertes Einscannen der Bauteile mithilfe eines
Linienscanners vorgestellt. Dieser Schritt ermöglicht eine detaillierte 3D-Rekonstruktion der Bauteilgeometrie und ermöglicht eine einfache Korrektur von Abweichungen in der Bauteilaufnahme und eröffnet Möglichkeiten zur adaptiven Bahnplanung bei Bauteilverformungen.
Die Rückprojektion der gefundenen Risse auf die Oberfläche des Bauteils kann
automatisiert erfolgen. Dieser Schritt erlaubt nicht nur die Identifikation der Risse, sondern auch eine genauere Analyse ihrer Geometrie und Lage am Bauteil.
Die Kombination von robotergestützter Laserthermografie, automatisiertem 3DScanning und Rückprojektion der Risse auf die Bauteiloberfläche eröffnet neue
Möglichkeiten in der zerstörungsfreien Prüfung von komplexen Bauteilen und erweitert damit mögliche Anwendungsfelder.
The aim of the ZIKA research project, funded by the BMBF funding program FORKA (FKZ:15S9446 A-C), is the automated detection of internal corrosion of radioactive drums using non-destructive testing (NDT). The newly gained findings will be combined with research results from the previous project EMOS (FKZ:15S9420), which dealt with the external damage of drums. Using NDT, internal corrosion and possible internal sources of damage can be identified before they become a safety-relevant issue. However, if internally sourced damages can be seen externally, the integrity of the damaged drum is no longer guaranteed, which has significant consequences. Therefore, early detection before integrity failure is of particular importance for interim storage facilities with low- and medium-level radioactive waste drums.
Metallbasierte additive Fertigungsverfahren werden zunehmend industriell zur Anfertigung von komplex geformten Komponenten eingesetzt. In diesem Zusammenhang ist das Laser-Pulverbettschweißen von Metall (PBF-LB/M) ist ein weitläufig genutztes Verfahren. Im PBF-LB/M-Prozess werden lagenweise aufgetragene Metallpulverschichten selektiv mittels eines Lasers aufgeschmolzen. Die Entstehung von internen Fehlstellen (bspw. Porosität, Lunker oder Risse) während des Fertigungsvorgangs stellt ein ernstzunehmendes Risiko für die Bauteilsicherheit und somit für die weitere industrielle Etablierung des Verfahrens dar. Die Entstehung von Fehlstellen hängt eng mit lokalen Änderungen der thermischen Historie des Bauteils zusammen. Mit Hilfe von thermografischen Kameras zur Prozessüberwachung kann die thermische Historie bereits während der Fertigung erfasst werden. Damit eröffnet sich die Möglichkeit, die Entstehung von Fehlstellen anhand der thermografischen Daten vorherzusagen und somit potenziell Kosten für eine nachgelagerte Qualitätssicherung einzusparen.
In diesem Beitrag soll die Modellierung der Fehlstellenvorhersage anhand thermografischer Prozessdaten diskutiert werden. Hierbei liegt ein Schwerpunkt auf der Fragestellung, mit welcher Genauigkeit unterschiedliche Formen von Fehlstellen, im speziellen Anbindungsfehler und Keyhole-Porosität, auf lokaler Bauteilebene vorhergesagt werden können. Weiterhin werden verschiedenen Modelltypen aus dem Bereich des Maschinellen Lernens auf ihre Eignung für die Fehlstellenvorhersage verglichen. Ein weiterer zentraler Aspekt in diesem Zusammenhang ist die Untersuchung der Eingangsdaten des Modells auf ihre Relevanz für das Vorhersageergebnis.
Als Datengrundlage für die durchgeführten Untersuchungen dienen die Fertigungsprozesse von zwei identischen Haynes-282-Bauteilen (Nickel-Basislegierung), welche mit Hilfe einer im kurzwelligen Infrarotbereich arbeitenden Thermografiekamera überwacht wurden. Das Bauteildesign umfasste lokale Bereiche, in denen mit Hilfe einer Parametervariation die Entstehung von Fehlstellen forciert wurde. Um die Position und Größe der entstandenen Defekte zu quantifizieren, wurden beide Bauteile nach erfolgter Fertigung mittels Computertomografie (CT) geprüft. Im Rahmen der Datenvorbereitung für die Modellierung erfolgte eine Reduzierung der erhobenen Thermogramme zu physikalisch-interpretierbaren Merkmalen (bspw. Schmelzbadfläche oder Zeit-über-Schwellwert). Weiterhin erfolgte eine Registrierung der thermografischen Daten mit den Fehlstellen-Referenzdaten der CT, um eine exakte örtliche Überlagerung von thermischer Information und lokalem Fehlstellenbild zu erzielen. Zur Ermöglichung einer lokalen Fehlstellenvorhersage wurden die thermografischen Daten schichtweise in kleinteiligen Volumina angeordnet, welche als Eingangsgröße für die genutzten ML-Algorithmen dienten.
Die Ergebnisse der Untersuchungen zeigen, dass sich die Porosität auf Bauteilschichtebene mit einer hohen Genauigkeit vorhersagen lässt. Eine Vorhersage der Porosität auf lokaler Bauteilebene erweist sich noch als herausfordernd. Die erprobten ML-Algorithmen zeigen vergleichbare Ergebnisse, obwohl ihnen unterschiedliche Modellierungsannahmen zugrunde liegen und sie variierende Komplexität aufweisen. Mit Hilfe der erzielten Erkenntnisse eröffnet sich die Möglichkeit, Rückschlüsse auf die gewählte Prozessüberwachungshardware und Datenvorverarbeitung zu ziehen und somit langfristig die Leistungsfähigkeit von Modellen zur Fehlstellenvorhersage zu verbessern.
Development of representative test specimens by thermal history transfer in laser powder bed fusion
(2024)
The use of components manufactured by laser powder bed fusion (PBF LB/M) and subjected to fatigue loading is still hampered by the uncertainty about the homogeneity of the process results. Numerous influencing factors including the component’s geometry contribute to the risk of process instability and resulting inhomogeneity of properties. This drastically limits the comparability of different built parts and requires expensive full component testing. The thermal history as the spatiotemporal temperature distribution has been identified as a major cause for flaw formation. Therefore, it can be hypothesized that a similar thermal history between components and test specimens enhances their comparability. Following this assumption, a strategy is developed to transfer the intrinsic preheating temperature as a measure of comparability of thermal histories from a region of interest of a complex component to a simple test specimen. This transfer concept has been successfully proved by the use of FEM-based macroscale thermal simulations, validated by calibrated infrared thermography. An adoption of the specimen manufacturing process by the adjustment of the inter layer times was established to manufacture specimens which are representatives of a specific region of a large-scale component in terms of the thermal history similarity criterion. The concept is schematically illustrated in Figure 1 and was demonstrated using a pressure vessel geometry from the chemical industry.
Die metallische additive Fertigung hat in den letzten Jahren in der industriellen Fertigung zunehmend an Bedeutung gewonnen. Hierbei dominiert das Laser-Pulverbettschweißen von Metallen (PBF/LB-M) die Fertigung von kleinformatigen Bauteilen mit hoher Oberflächengüte. Die anspruchsvolle und kostspielige Qualitätssicherung stellt aber weiterhin ein Hindernis für eine breitere und kostengünstigere Anwendung der additiven Fertigung dar. Dies resultiert teilweise aus fehlenden zuverlässigen In-situ-Monitoringsystemen. Belastbarere Prozessüberwachungsdaten würden eine oft erforderliche teure nachgelagerte Prüfung mittels Computertomografie entbehrlich machen. Die Aufzeichnung der thermischen Signaturen des Aufbauprozess mittels Thermografie-Kameras zeigen hier vielversprechende Ergebnisse. Eine Korrelation zu auftretender Porosität, Delaminationen und Deformationen scheinen möglich. Die geringe räumliche Auflösung und die hohen Anschaffungskosten für thermografische Kamerasysteme stehen jedoch einer größeren industriellen Nutzung im Wege.
Ein bereits industriell angewendeter Ansatz zur in-Situ Überwachung des PBF-LB/M Prozesses ist die Optische Tomografie (OT). Hierbei wird die emittierte Prozessstrahlung jeder Bauteilschicht mittels einer hochauflösenden günstigen Kamera für den sichtbaren Wellenlängenbereich in einer Langzeitbelichtung dokumentiert. Die zeitliche Information der emittierten Strahlung geht hierbei verloren. Der gesamte Bauprozess kann jedoch in einem vergleichsweise kleinen Datensatz dokumentiert werden (ein Bild pro Schicht). Eine direkte Korrelation zu auftretenden Defekten gestaltet sich aufgrund der reduzierten thermischen Informationsdichte jedoch schwierig.
In diesem Beitrag soll deshalb das Prinzip der Multispektralen Optischen Tomografie (MOT) vorgestellt und erste Messergebnisse an der Forschungsanlage SAMMIE diskutiert werden. Bei der MOT handelt es sich um eine Übertragung des Prinzips der Quotientenpyrometrie auf das etablierte Verfahren der Optischen Tomografie. Die auftretende Prozessstrahlung wird in mehreren Wellenlängenbereichen ortsaufgelöst über die gesamte Bauplattform erfasst und zeitlich in einer Langzeitbelichtung integriert. Hierbei kommen günstige Kamerasysteme für den sichtbaren Wellenlängenbereich zum Einsatz.
Das erfasste Signal I jedes Bildpixels für jeden separat erfassten Wellenlängenbereich kann als Maß für das zeitliche Integral der spezifischen Ausstrahlung M des Schmelzbades in diesem Wellenlängenbereich gesehen werden. Nach dem Stefan-Boltzmann-Gesetz hängt die abgestrahlte thermische Leistung P eines idealen Schwarzen Körpers in der vierten Potenz von dessen absoluten Temperatur T ab. Wird nur, wie z.B. bei der klassischen OT angewendet, der nahinfrarote Wellenlängenbereich betrachtet, lässt sich mit dem Planck’schen Strahlungsgesetz sogar eine Proportionalität zur siebten Potenz der Temperatur zeigen. Deshalb liegt ein starker Einfluss der maximal auftretenden Oberflächentemperatur Tmax auf das erfasste Messsignal vor.
Das erfasste Signal I wird aber auch durch die spektrale Transmission τ der verwendeten optischen Komponenten des Kamera-Setups, z.B. Filter und Objektive, durch die spektrale Sensitivität S der verwendeten Kamera-Sensoren und den nur sehr schwer zu bestimmenden Emissionsgrad ε der emittierenden (flüssigen) Oberfläche beeinflusst.
In einer ersten Näherung wird das Schmelzbad hier als Graukörper, also ein Körper mit wellenlängenunabhängigem Emissionsgrad ε, betrachtet. Basierend auf dieser Annahme und vermessenen optischen Eigenschaften des verwendeten Systems ist es möglich, eine erste Schätzung der maximalen Oberflächentemperatur Tmax vorzunehmen, selbst ohne genaue Kenntnis des tatsächlichen Emissionsgrades ε. Dies wird durch die Anwendung des Planck‘schen Strahlungsgesetzes und die Quotienten Bildung aus den einzelnen erfassten Signalen I ermöglicht.
Auch bei diesem Verfahren geht die zeitliche Information einer Schicht, also das Aufwärm- und Abkühlverhalten des Schmelzbades, verloren. Zudem sind die Messergebnisse in Hinblick auf tatsächlich gemessene „maximal auftretende Oberflächentemperatur“ mit gebotener Zurückhaltung zu interpretieren. Trotzdem konnten erste Ergebnisse bereits zeigen, dass die MOT-Daten auch in Bereichen mit Doppelbelichtungen (das teilweise notwendige mehrfache Scannen eines Bereiches mittels des Fertigungslasers) im Gegensatz zur klassischen OT erwartbare Maximaltemperaturen liefern. Abbildung 1 zeigt das erfasste Messergebnis für drei aufeinanderfolgende Schichten eines Bauteils einmal mit MOT (links) und einmal mit einfacher OT (rechts). Deutlich zu erkennen ist das durch die doppelte Belichtung hohe Signal bei der OT. Die Daten der MOT zeigen hier keine erhöhten Werte.
Um die ermittelten Temperaturwerte mittels MOT besser einordnen zu können, sind u.a. vergleichende Messungen an Referenzmaterialien geplant. Um die Auswertung der gemessenen Daten zu verbessern, wird zudem der Zeitverlauf des Abkühlens und Aufheizens des Schmelzbades sowie die Einflüsse von Prozessbeiprodukten wie Schmauch und Spritzer näher untersucht. Auch werden Messungen zum Emissionsgrad ε an additiv gefertigten Proben und Metallschmelzen vorgenommen.
Im additiven Fertigungsprozess Laser-Pulverbettschweißen wird Metallpulver lagenweise mittels eines Lasers aufgeschmolzen, um Bauteile zu generieren. Hierbei werden die Eigenschaften der Bauteile zu einem großen Teil durch die im Verlauf des Prozesses vorliegenden Temperaturen bestimmt. Dies beinhaltet unter anderem Materialeigenschaften wie Mikrostruktur, Härte, thermische und elektrische Leitfähigkeiten sowie die Ausbildung von Defekten wie z.B. Anbindungsfehler, Keyhole-Porosität (Gaseinschlüsse) oder auch die Ausbildung von Rissen. Zur Überwachung bzw. Vorhersage dieser Eigenschaften sowie zum Abgleich von Simulationen ist eine orts- und zeitaufgelöste Messung der Temperaturverteilung im Prozess daher von herausragender Bedeutung. In der Industrie kommen optische Verfahren, die auf der Messung der thermischen Strahlung basieren, regelmäßig zum Einsatz. Allerdings dienen diese bislang nur der statistischen Auswertung und der Identifikation von Abweichungen vom Normalprozess. Der quantitativen Auswertung zur Temperaturbestimmung stehen aktuell noch eine Vielzahl von Herausforderungen entgegen. Einerseits stellt der Prozess an sich hohe Anforderungen an die Datenerfassung und -auswertung: der Emissionsgrad verändert sich dynamisch im Prozess und lokale Schmauchbildung sorgt für potenzielle Absorption oder Streuung der thermischen Strahlung oder auch des Fertigungslasers. Weiterhin stellt der hochdynamische Prozess hohe Anforderungen an Orts- und Zeitauflösung der eingesetzten Sensorik (z.B. Kameratechnik). Andererseits erschweren an üblichen kommerziell erhältlichen Fertigungsanlagen praktische Hindernisse wie eine eingeschränkte optische Zugänglichkeit und der fehlende Zugriff auf die Anlagensteuerung sowie fehlende Möglichkeiten der Synchronisation der Messtechnik mit dem Prozess eine eingehende Untersuchung dieser Effekte.
Um letztere Hindernisse zu umgehen, wurde an der BAM die Forschungsanlage SAMMIE (sensor-based additive manufacturing machine) entwickelt. Einerseits bietet das System alle Möglichkeiten, die auch übliche kommerzielle Systeme bieten. Dies beinhaltet die Fertigung ganzer Bauteile (maximale Größe ca. 65mm x 45 mm x 30 mm) und den Einsatz einer Inertgasatmosphäre inkl. gefiltertem Schutzgasstrom. Andererseits bietet es aber auch einen besonders kompakten Bauraum, um die Sensorik möglichst nah an den Prozess führen zu können, sechs optische Fenster zur Prozessbeobachtung aus unterschiedlichen Winkeln und die Möglichkeit der Prozessbeobachtung koaxial zum Fertigungslaser. Des Weiteren besteht eine einfache Austauschbarkeit aller Fenster, Spiegel und Strahlteiler, um den gesamten optischen Pfad der aktuellen Messaufgabe flexibel anzupassen. Die komplette Anlagensteuerung ist eine Eigenentwicklung und bietet daher auch völlige Anpassbarkeit. Eine synchrone und frei konfigurierbare Triggerung diverser Sensoriken und synchrone Datenerfassung bieten maximale Kontrolle über die Sensorsteuerung.
Dieser Beitrag gibt einen Überblick über die Fertigungsanlage SAMMIE. Wissenschaftliche Ergebnisse sowie laufende Arbeiten an der Anlage werden in weiteren Beiträgen vorgestellt.
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.
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.
In this paper, we investigate the influence of different heat source pulse shapes by Infrared impulse thermography (IRT) on the results of the thermal shock response spectrum (TSRS) methodology. TSRS is a new alternative approach for evaluating impulse thermography (IRT) data based on an analogy to Shock Response Spectrum (SRS) analysis (ISO 18431) for mechanical systems. It allows processing the entire recorded signal without truncating the saturated thermogram, as in pulse-phase thermography (PPT) or thermal signal reconstruction (TSR). For this purpose, we use a widespread halogen lamp as heat source as well as laser spot. The laser source enables not only to generate a precise shape of the pulse, but also to heat a specific area of the sample uniformly. This makes it possible to suppress influences of lateral fluxes due to uneven distribution of the excitation source on the surface of the specimen and leads to improved results. In order to quantitatively compare the results and to investigate the possible influence of the source shape on the TSRS, the Tanimoto criterion and the signal-to-noise ratio (SNR) were applied to the region of interest (ROI) of the carbon fiber reinforced polymer (CFRP) laminate with artificial defects as defect detectability criterion.
Die additive Fertigung von Metallen hat inzwischen einen Reifegrad erreicht, der einen Einsatz in vielen Industriezweigen ermöglicht oder in greifbare Nähe rückt. Die Vorteile liegen vor allem in der Möglichkeit der Fertigung komplexer Bauteile, die sich konventionell nicht oder nur sehr aufwändig produzieren lassen, sowie in der Fertigung von hochindividualisierten Bauteilen in kleinen Stückzahlen. Allerdings ist der additive Fertigungsprozess hoch komplex und fehleranfällig. Um eine insbesondere für sicherheitsrelevante Bauteile notwendige Qualitätskontrolle zu gewährleisten, ist aktuell aufwändige nachgelagerte ZfP der einzelnen Bauteile notwendig. Alternativen könnten die In-situ-Prozessüberwachung und -prüfung bieten, die aktuell aber noch keinen ausreichenden Entwicklungsstand erreicht haben. Industrielle Fertigungsanlagen bieten keine oder nur geringe Flexibilität und Zugänglichkeit, um umfangreiche Untersuchungen auf diesem Gebiet zu ermöglichen. Daher haben wir an der BAM ein System für den Prozess des selektiven Laserschmelzens (PBF-LB/M) entwickelt, genannt SAMMIE. Es bietet eine komplett offene Systemarchitektur mit voller Kontrolle über den Prozess und flexiblem Zugang zur Baukammer, z.B. optisch sowohl direkt als auch koaxial zum Fertigungslaser. In diesem Beitrag stellen wir das System vor und zeigen erste experimentelle Ergebnisse der In-situ-Überwachung und -prüfung: Thermografische Schmelzbadüberwachung, optische Tomografie und In-situ-Laserthermografie. SAMMIE ermöglicht uns grundlegende Untersuchungen, die helfen werden, die In-situ-Prozessüberwachung und -prüfung weiterzuentwickeln, neue Erkenntnisse über die additive Fertigung zu gewinnen und die Sicherheit und Zuverlässigkeit des Prozesses zu verbessern.
For a deep process understanding of the laser powder bed fusion process (PBF-LB/M), recording of the occurring surface temperatures is of utmost interest and would help to pave the way for reliable process monitoring and quality assurance. A notable number of approaches for in-process monitoring of the PBF-LB/M process focus on the monitoring of thermal process signatures. However, due to the elaborate calibration effort and the lack of knowledge about the occurring spectral directional emissivity, only a few approaches attempt to measure real temperatures. In this study, to gain initial insights into occurring in the PBF-LB/M process, measurements on PBF-LB/M specimens and metal powder specimens were performed for higher temperatures up to T = 1290 °C by means of the emissivity measurement apparatus (EMMA) of the Center for Applied Energy Research (CAE, Wuerzburg, Germany). Also, measurements at ambient temperatures were performed with a suitable measurement setup. Two different materials—stainless steel 316L and aluminum AlSi10Mg—were examined. The investigated wavelength λ ranges from the visible range (λ-VIS = 0.40–0.75 µm) up to the infrared, λ = 20 µm. The influence of the following factors were investigated: azimuth angle φ, specimen temperature TS, surface texture as for PBF-LB/M surfaces with different scan angles α, and powder surfaces with different layer thicknesses t.
Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel structures exposed to cyclic loads during their service life. Observation of welded connections is especially of high relevance due to their higher susceptibility to fatigue damage. The aim of this contribution was to monitor fatigue crack growth in thick welded specimens during fatigue tests as holistically as possible, by implementing multiple NDT methods simultaneously in order to record the crack initiation and propagation until the final fracture. In addition to well-known methods such as strain gauges, thermography, and ultrasound, the crack luminescence method developed at the Bundesanstalt für Materialforschung und -prüfung (BAM), which makes cracks on the surface particularly visible, was also used. For data acquisition, a first data fusion concept was developed and applied in order to synchronize the data of the different methods and to evaluate them to a large extent automatically. The resulting database can ultimately also be used to access, view, and analyze the experimental data for various NDT methods. During the conducted fatigue tests, the simultaneous measurements of the same cracking process enabled a comprehensive comparison of the methods, highlighting their individual strengths and limitations. More importantly, they showed how a synergetic combination of different NDT methods can be beneficial for implementation in large-scale fatigue testing but also in monitoring and inspection programs of in-service structures - such as the support structures of offshore wind turbines.
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.
Der vorliegende Vortrag gibt einen Überblick über die geleisteten Arbeiten in diesem Gebiet im Rahmen der hier mit dem Wissenschaftspreis der DGZfP 2024 prämierten Arbeit.
Aktive thermografische Prüfung ist ein vielseitiges Instrument in der Familie der zerstörungsfreien Prüfverfahren. Der Einzug moderner Lasertechnologie hat hier bedeutende neue Anwendungsfelder eröffnet. In Kombination mit Industrierobotik können nun beispielsweise beliebig komplex geformte Bauteile großflächig vollautomatisiert auf Oberflächenrisse überprüft werden. Der hier vorliegende Vortrag gibt einen Überblick über die Grundlagen der Laserthermografie, zeigt unsere Anstrengungen am Fachbereich im Bereich der automatisierten thermografischen Detektion von Oberflächenrissen und gibt ein Ausblick über neue moderne Thermografieverfahren aus der Forschung.
The properties of laser radiation result in a wide range of applications, making laser technologies indispensable in areas such as industry, science and medicine. The possible areas of application for thermography in this context are just as diverse. Thermography is used in laser applications when permanent monitoring and control of thermal development is necessary. Among others, this is the case in additive manufacturing, laser-based measuring devices and non-destructive testing. Furthermore, thermography is ideally suited as a testing method when it comes to ensuring the quality of the laser itself. In this talk it is outlined, how lasers can be used as a heat source in active thermographic testing. Furthermore, two special variants (spatial & temporal structured heating) are described, for which lasers are highly suitable.
Die Thermografie ist trotz ihrer ausgereiften wissenschaftlichen und technologischen Grundlagen ein noch relativ junges Mitglied in der Familie der zerstörungsfreien Prüfverfahren. Sie erschließt sich aufgrund einer Reihe von Vorzügen eine wachsende Anwendungsgemeinde. Für eine weitere Verbreitung insbesondere im industriellen Kontext spielen Normen, Standards und technische Regeln eine wichtige Rolle. In diesem Beitrag wird der aktuelle Stand der Normung in Deutschland vorgestellt. Wir zeigen, welche Normen und technischen Regeln es für die Thermografie in Deutschland und international gibt und wir wagen einen Blick in die Zukunft. Darüber hinaus lebt auch die Normierungsarbeit von der Beteiligung durch interessierte Kreise. Dies können industrielle und akademische Anwender*innen, Hersteller*innen von Geräten, Forschungseinrichtungen oder Dienstleistungsunternehmen sein. Sie können gern Ihre Bedarfe bezüglich Normierungsprojekten mitbringen und/oder direkt an die Autoren senden.
Die Thermografie ist trotz ihrer ausgereiften wissenschaftlichen und technologischen Grundlagen ein noch relativ junges Mitglied in der Familie der zerstörungsfreien Prüfverfahren. Sie erschließt sich aufgrund einer Reihe von Vorzügen eine wachsende Anwendungsgemeinde. Für eine weitere Verbreitung insbesondere im industriellen Kontext spielen Normen, Standards und technische Regeln eine wichtige Rolle. In diesem Beitrag wird der aktuelle Stand der Normung in Deutschland vorgestellt. Wir zeigen, welche Normen und technischen Regeln es für die Thermografie in Deutschland und international gibt und wir wagen einen Blick in die Zukunft. Darüber hinaus lebt auch die Normierungsarbeit von der Beteiligung durch interessierte Kreise. Dies können industrielle und akademische Anwender*innen, Hersteller*innen von Geräten, Forschungseinrichtungen oder Dienstleistungsunternehmen sein. Sie können gern Ihre Bedarfe bezüglich Normierungsprojekten mitbringen und/oder direkt an die Autoren senden.
Laser powder bed fusion of metallic components (PBF-LB/M) is gaining acceptance in industry. However, the high costs and lengthy qualification processes required for printed components create the need for more effective in-situ monitoring and testing methods. This article proposes multispectral Optical Tomography (OT) as a new approach for monitoring the PBF-LB/M process. Compared to other methods, OT is a low-cost process monitoring method that uses long-time exposure imaging to observe the build process. However, it lacks time resolution compared to expensive thermographic sensor systems. Monochromatic OT (1C-OT) is already commercially available and observes the building process layer-wise using a single wavelength window in the NIR range. Multispectral OT (nC-OT) utilizes a similar setup but can measure multiple wavelength ranges per location simultaneously. By comparing the classical 1C-OT and nC-OT approaches, this article examines the advantages of nC-OT (two channel OT and RGB-OT) in reducing the false positive rate for process deviations and approximating maximum temperatures for a better comparison between different build processes and materials. This could ultimately reduce costs and time for part qualification. The main goal of this contribution is to assess the advantages of nC-OT compared to 1C-OT for in-situ process monitoring of PBF-LB/M.
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.
Asphalt is one of the most common materials used in road construction. It is subject to both chemical and structural aging processes during use. At least to our knowledge, it is not currently known whether these aging processes also lead to a measurable change in the thermal properties of asphalt. If so, these changes could be exploited for non-destructive testing of the aging condition in situ. Photothermal analysis of a component surface involves looking at the time course of the surface temperature during and after pulse-like heating with an expanded laser beam. In the case of concrete surfaces, this method works well under laboratory conditions. It allowed the determination of the thermal effusivity. Now it should be investigated whether the photothermal signal allows conclusions to be made regarding the aging state of the asphalt. Within the scope of this paper, 2 asphalt specimens were investigated: a closed asphalt with 3% void content (SMA 11S) and an open-pore asphalt with 25% void content (PA 8). Both samples were artificially degraded according to a standardized procedure, leaving a portion of the surface unaffected. Subsections from both areas were then separated for photothermal testing. It was found, that the photothermal method is apparently not sensitive enough to detect aging on asphalt in general. However, it is noteworthy that both asphalt types heat up significantly faster than would be expected from the theory of heat conduction, which might be explained by the specific microstructure.
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.
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.
Great complexity characterizes Additive Manufacturing (AM) of metallic components via laser powder bed fusion (PBF-LB/M). Due to this, defects in the printed components (like cracks and pores) are still common. Monitoring methods are commercially used, but the relationship between process data and defect formation is not well understood yet. Furthermore, defects and deformations might develop with a temporal delay to the laser energy input. The component’s actual quality is consequently only determinable after the finished process.
To overcome this drawback, thermographic in-situ testing is introduced. The defocused process laser is utilized for nondestructive testing performed layer by layer throughout the build process. The results of the defect detection via infrared cameras are shown for a research PBF-LB/M machine.
This creates the basis for a shift from in-situ monitoring towards in-situ testing during the AM process. Defects are detected immediately inside the process chamber, and the actual component quality is determined.
Thermography is a widely accepted non-invasive measurement method and is generally used in various areas of the life cycle of infrastructure and machinery. This includes design, production and maintenance. Thermography is particularly suitable for remote inspection of large areas that are difficult to reach.
In this presentation, applications of thermography in the field of wind energy will be shown, touching on three explicit examples from rotor blade inspection.
Experimental testing and validation: Thermography can measure and visualise the stress distribution on the surface during cyclic tests of rotor blades and rotor blade sections. The so-called thermoelastic stress analysis makes use of special evaluation algorithms (Lockin analysis) of the measurement data and the cyclic loading of components. An advantage of the measurement methods compared to other measurement methods such as strain gauges or digital image correlation is that it does not require any extra treatment or sensoring of the components. In the work shown here, repair methods are optimised and evaluated in cyclic tests on shell test specimens.
Operation and maintenance: Rotor blades can be inspected from the ground during operation using passive thermography. Here, the integration of weather forecasts and conditions as input for simulations is crucial and will be demonstrated with some examples from the field. The goal of the ongoing research is to obtain detailed insights into the internal structure of the inspected rotor blades with individual measurements. A specially developed automated measuring system is able to measure a wind turbine (one-sided) within 5 minutes without impacting its operation.
Environmental impact: In cases where less strict time and economic constraints apply than in the maintenance of rotor blades in operation, thermography can also be used to realise other inspection processes that take more time. Examples of this are quality control or the characterisation of rotor blades during dismantling. In the latter case, for example, it can be crucial to know which components such as foam, balsa, belt and spar are present in which parts of the blade when dismantling the rotor blades. Long-term measurements (~1-2 h) under suitable weather conditions can provide good insights into the inner structure of the rotor blades, both during disassembly and during quality control before installation. For this purpose, the sun is used as a heat source, which induces a thermal response of the rotor blades. The thermal behaviour of the rotor blades then allows conclusions to be drawn about the internal structure.
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.
The work shown demonstrates the possibility of measuring the load distribution of complex components such as rotor blades in cyclic tests using thermography. This is confirmed in the experiments presented by comparison with DIC measurements. The advantage of thermography is that it does not require any treatment of the test specimens in the setup shown and the measurement procedure can in principle be scaled to large components. In addition, compared to other imaging methods, the actual loads and not the deformation are measured. With a suitable data evaluation by means of Lockin analysis, small loads can be verified in a formative manner. Using the example of model repairs in shell test specimens made of sandwich glass fibre composite material, it is shown that inhomogeneous load distribution due to internal structures can be detected using thermography.
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.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring), which have not been researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.
A steady increase of wind energy infrastructure brings along a challenge of maintaining and operating wind turbines (WT) with its multiple components. Inspection of wind turbine rotor blades (WTB) is an important part of maintaining the overall health and safety of a WT. It involves visually or mechanically examining the blades for signs of damage or wear that could affect their performance and structural integrity of the entire WT. A WTB is a complex structure due to its ever-increasing scale (going beyond 100 m for a 16 MW WT) as well as multi-material construction. Passive infrared thermography offers an alternative to contact- or proximity-based inspection techniques currently in use such as visual inspection performed by technical personnel (using a lift or a drone) and involves looking for signs of damage on the surface of the blades, and ultrasonic testing to detect internal defects. In contrast to active thermography, passive thermography uses the sun as source of heat, instead of conventional heat lamps, flash, or laser. An inspection technique to (semi-autonomously) inspect the WTBs of an operating WT from the ground has been developed. Given the optimum thermal contrast (weather conditions for field measurements), external as well as internal features of the WTB can be visualised with appropriate post-processing. The work presented here is part of an ongoing multi-partner project titled “EvalTherm”: the evaluation of passive thermography as a non-destructive inspection tool of WTBs in operation. In this work, artificial defects representative of realistic defects in glass fibre reinforced plastic (GFRP) WTBs are introduced in out-of-service WTB pieces. These are scanned using X-ray computed tomography to obtain a three-dimensional reconstruction to be used as input for finite-element based thermal simulation using COMSOL Multiphysics. The simulation data is compared with infrared thermal inspection of the same WTB section, in order to compare the effect of thermal contrast caused in certain weather conditions. In addition, the influence of defect characteristics such as defect size, morphology, and location on detectability is investigated. Validated simulation models are used to predict thermal signatures of defects along with the optimal thermal contrast. Such simulation models in combination with weather forecast data can assist operators of wind turbine infrastructure to plan passive thermography inspection without the need of dangerous inspection procedures and associated shutdown of energy production.
To cope with the increase in the manufacturing and operation of wind turbines, wind farm operators need inspection tools that are able to provide reliable information while keeping the downtime low. Current inspection techniques require to stop the wind turbine. This work presents the current progress in the project EvalTherm, in which passive thermography is evaluated as a possible non-destructive inspection tool for operational wind turbine blades (WTBs). A methodology to obtain thermal images of rotating WTBs has been established in this project. However, the quality of the results is heavily dependent on various aspects such as weather conditions, information on the inspected WTB, damage history, etc. In this work, a section of a used WTB is simulated using finite-element modelling (FEM) as well as experimentally tested for evaluating the accuracy of the model. Such a model will provide insight into the potential thermal response of a certain structure (with specific material properties) in given weather (boundary) conditions. The model is able to provide satisfactory predictions of the thermal response of the structure, as well as indicate what thermal contrast(s) result from artificial defects introduced in the structure.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a non-destructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. The results of the defect detection using infrared cameras are presented for a custom research PBF-LB/M machine. Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
Safety-critical applications of products manufactured by laser powder bed fusion (PBF-LB/M) are still limited to date. This is mainly due to a lack of knowledge regarding the complex relationship between process, structure, and resulting properties. The assurance of homogeneity of the microstructure and homogeneity of the occurrence and distribution of defects within complexly shaped geometries is still challenging. Unexpected and unpredicted local inhomogeneities may cause catastrophic failures. The identification of material specific and machine specific process parameter windows for production of fully dense simple laboratory specimens is state of the art. However, the incorporation of changing thermal conditions that a complexly shaped component can be faced with during the manufacturing process is often neglected at the stage of a process window determination. This study demonstrates the tremendous effect of changing part temperatures on the defect occurrence for the broadly used stainless steel alloy AISI 316L. Process intrinsic variations of the surface temperature are caused by heat accumulation which was measured by use of a temperature adjusted mid-wavelength infrared (MWIR) camera. Heat accumulation was triggered by simple yet effective temporal and geometrical restrictions of heat dissipation. This was realized by a variation of inter layer times and reduced cross section areas of the specimens. Differences in surface temperature of up to 800 K were measured. A severe development of keyhole porosity resulted from these distinct intrinsic preheating temperatures, revealing a shift of the process window towards unstable melting conditions. The presented results may serve as a warning to not solely rely on process parameter optimization without considering the actual process conditions a real component is faced with during the manufacturing process. Additionally, it motivates the development of representative test specimens.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M ) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring) but not researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.