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Eingeladener Vortrag
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That human factors (HF) affect the reliability of NDT is not novelty. Still, when it comes to reliability assessments, the role of people is often neglected. Reliability is typically expressed in terms of POD curves, and the effects of human and organisational factors on the inspection are typically tackled by the regulations, procedures and by the qualification and training of the inspection personnel. However, studies have shown that even the most experienced personnel can make mistakes and that the reliability in the field is never as high as the reliability measured in the POD experiments. Generally, HF are considered too unpredictable and too uncontrollable to model. If that is the fact, then what can we do? The engineering perspective to this problem has often been to find ways to automate inspections and, recently, to make use of artificial intelligence tools to decrease the direct effect of people on the inspection results and improve the overall efficiency and reliability. However, despite automation and AI, people remain the key players, though their tasks change. The contemporary approach to HF is not to engineer them out of the system but to design human-machine systems that make the best use of both. In this talk, ways of tackling HF in the design of systems and processes will be presented.
To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and costintensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases.
Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm.
A joint project of partners from industry and research institutions for the research and construction of an analysis system for an automated, sensor-supported sorting of construction and demolition waste will be presented. This is intended to supplement or replace the previously practiced manual sorting, which harbors many risks and dangers for the staff and only enables obvious, visually detectable differences for separation. The method of laser-induced breakdown spectroscopy is to be used in combination with hyperspectral sensors. Due to the jointly processed information (data fusion), this should lead to a significant improvement in the separation of types. In addition to the sorting of different materials (concrete, main masonry building materials, organic components, glass, etc.), impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.) could also be detected and separated.
The subsequent recycling and sales opportunities are examined, such as the use of recycled aggregates in concrete, the recycling of building materials containing sulphate as a gypsum substitute for the cement industry or the agglomeration of synthetic lightweight aggregates for lightweight concrete or as a substrate for green roofs. At the same time, it is investigated whether soluble components (sulfates, heavy metals, etc.) can be detected by LIBS without a wet chemical analysis and what impact the recycling materials have on the environment.
The entire value chain is examined using the example of the Berlin location in order to minimize economic / technological barriers and obstacles on a cluster level and to sustainably increase the recovery and recycling rates.
Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm.
Alkali-activated binders (AAB) can provide a clean alternative to conventional cement in terms of CO2 emissions. However, as yet there are no sufficiently accurate material models to effectively predict the AAB properties, thus making optimal mix design highly costly and reducing the attractiveness of such binders. This work adopts sequential learning (SL) in high-dimensional material spaces (consisting of composition and processing data) to find AABs that exhibit desired properties. The SL approach combines machine learning models and feedback from real experiments. For this purpose, 131 data points were collected from different publications. The data sources are described in detail, and the differences between the binders are discussed. The sought-after target property is the compressive strength of the binders after 28 days. The success is benchmarked in terms of the number of experiments required to find materials with the desired strength. The influence of some constraints was systematically analyzed, e.g., the possibility to parallelize the experiments, the influence of the chosen algorithm and the size of the training data set. The results show the advantage of SL, i.e., the amount of data required can potentially be reduced by at least one order of magnitude compared to traditional machine learning models, while at the same time exploiting highly complex information. This brings applications in laboratory practice within reach.
Оперативная характеристика обнаружения как метод оценки достоверности неразрушающего контроля
(2021)
Оперативные характеристики обнаружения в течение многих лет успешно применяют-ся при оценке достоверности неразрушающего контроля. Основными проблемами для их использования, как и при применении любого из методов оценки достоверности, яв-ляются отсутствие информации о действительной дефектной ситуации и ограниченное количество дефектов в образцах объектов контроля. Дополнительной проблемой постро-ения оперативной характеристики обнаружения является отсутствие информации о раз-мерах дефектов и отсутствие универсального размера для различных типов дефектов.
В статье обобщён опыт построения оперативных характеристик по результатам ультра-звукового контроля.
Novel Technique for On-Line Monitoring of the Curing Process of Fiber Reinforced Polymer Composites
(2021)
A specially developed experimental set up has been integrated into a commercially available FT IR Spectrometer to study the curing of Epoxy Systems. MIR and FIR spectra measured during the curing process at different temperatures of an epoxy system will be presented in dependency of the curing time. The experiments and the selected set up are discussed to demonstrate its potential for future monitoring and ageing control applications during a manufacturing process of polymer composites.
The development of prevention methods and the detection of moisture related damages in buildings and transport infrastructure at an early stage are current issues
in the field of non-destructive testing in civil engineering. Especially the subject of partial saturation requires further research since it is more likely to occur than full saturation of the material. In fact, partial saturation in porous media is even more complicated because both fully and partly saturated pores (i.e. pores in which the surfaces are covered with thin water layers) are present.
As the non-destructive method nuclear magnetic resonance
(NMR) enables the measurement and quantification of relative low moisture contents, it is suitable for the investigation of partly saturated porous building materials. Nevertheless, the differentiation between partly and fully saturated pores is still a challenge. Therefore, in this study, we investigate two sandstones types (Bozanov and Schönbrunner sandstone) at various defined saturation states by using NMR. Furthermore, we measure the relative humidities within the samples and compute the water layer thicknesses (WLT) along the pore walls of all pore sizes to calculate the corresponding degree of pore saturation. To finally assign the NMR signals to pore sizes and to differentiate between partly and fully saturated pores, the water content distribution obtained from the WLT calculation
is used for calibration of the relaxation-time distribution.
The development of prevention methods and the detection of moisture related damages in buildings and transport infrastructure at an early stage are current issues in the field of non-destructive testing in civil engineering.
Especially the subject of partial saturation requires further research since it is more likely to occur than full saturation of the material. In fact, partial saturation in porous media is even more complicated because both fully and partly saturated pores (i.e. pores in which the surfaces are covered with thin water layers) are present.
As the non-destructive method nuclear magnetic resonance (NMR) enables the measurement and quantification of relative low moisture contents, it is suitable for the investigation of partly saturated porous building materials. Nevertheless, the differentiation between partly and fully saturated pores is still a challenge. Therefore, in this study, we investigate two sandstones types (Bozanov and Schönbrunner sandstone) at various defined saturation states by using NMR. Furthermore, we measure the relative humidities within the samples and compute the water layer thicknesses (WLT) along the pore walls of all pore sizes to calculate the corresponding degree of pore saturation. To finally assign the NMR signals to pore sizes and to differentiate between partly and fully saturated pores, the water content distribution obtained from the WLT calculation is used for calibration of the relaxation-time distribution. In this extended abstract, selected results only for Schönbrunner sandstone are presented.
Im Rahmen des Themenfeldprojektes „Process Monitoring of AM“ (ProMoAM) evaluiert die Bundesanstalt für Materialforschung und -Prüfung (BAM) gegenwärtig die Anwendbarkeit verschiedenster ZfP-Verfahren zur in-situ Prozessüberwachung in der additiven Fertigung (AM) von Metallen in Hinblick auf die Qualitätssicherung.
Einige der wichtigsten Messgrößen sind hierbei die Temperatur des Schmelzbades und die Abkühlrate, welche starken Einfluss auf das Gefüge und die Eigenspannung haben. Aufgrund der Zugänglichkeit zum Werkstück während des Bauprozesses bieten sich optische Verfahren zu Temperaturbestimmung an. Hierbei stellen jedoch u. a. die hohe Bandbreite der zu messenden Temperaturen, die Bestimmung der Emissivität und ihre Änderung bei Phasenübergängen der verwendeten Legierung große experimentelle Herausforderungen dar. Eine weitere Herausforderung stellt für die IR-Spektroskopie die Absorption durch das Schutzgas und weitere optische Elemente dar. Um diese auch in einem industriellen Umfeld kompensieren zu können, wurde eine Methode entwickelt, die das gemessene Spektrum bei der Verfestigung des Werkstoffes als Referenz nutzt. In diesem Beitrag wird die Anwendung dieser Methode für die IR-Spektrometrie als auch Thermografische Messungen beim Laser-Pulver-Auftragschweißen von 316L gezeigt, wobei beide Methoden weiterhin in Hinblick auf ihre individuellen Vor- und
Nachteile miteinander verglichen werden.
An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering
(2021)
Although measurement data from the civil engineering sector are an important basis for scientific analyses in the field of non-destructive testing (NDT), there is still no uniform representation of these data. An analysis of data sets across different test objects or test types is therefore associated with a high manual effort. Ontologies and the semantic web are technologies already used in numerous intelligent systems such as material cyberinfrastructures or research databases. This contribution demonstrates the application of these technologies to the case of the 1H nuclear magnetic resonance relaxometry, which is commonly used to characterize water content and porosity distri-bution in solids. The methodology implemented for this purpose was developed specifically to be applied to materials science (MS) tests. The aim of this paper is to analyze such a methodology from the perspective of data interoperability using ontologies. Three benefits are expected from this ap-proach to the study of the implementation of interoperability in the NDT domain: First, expanding knowledge of how the intrinsic characteristics of the NDT domain determine the application of semantic technologies. Second, to determine which aspects of such an implementation can be improved and in what ways. Finally, the baselines of future research in the field of data integration for NDT are drawn.
Undetected and undesired microstructural variations in components produced by laser powder bed fusion are a major challenge, especially for safety-critical components. In this study, an in-depth analysis of the microstructural features of 316L specimens produced by laser powder bed fusion at different levels of volumetric energy density and different levels of inter layer time is reported. The study has been conducted on specimens with an application relevant build height
(>100 mm). Furthermore, the evolution of the intrinsic preheating temperature during the build-up of specimens was monitored using a thermographic in-situ monitoring set-up. By applying recently determined emissivity values of 316L powder layers, real temperatures could be quantified. Heat accumulation led to preheating temperatures of up to about 600 °C. Significant differences in the preheating temperatures were discussed with respect to the individual process parameter combinations, including the build height. A strong effect of the inter layer time on the heat accumulation was observed. A shorter inter layer time resulted in an increase of the preheating temperature by more than a factor of 2 in the upper part of the specimens compared to longer inter layer times. This, in turn, resulted in heterogeneity of the microstructure and differences in material properties within individual specimens. The resulting differences in the microstructure were analyzed using electron back scatter diffraction and scanning electron microscopy. Results from chemical analysis as well as electron back scatter diffraction measurements indicated stable conditions in terms of chemical alloy composition and austenite phase content for the used set of parameter combinations. However, an increase of the average grain size by more than a factor of 2.5 could be revealed within individual specimens. Additionally, differences in feature size of the solidification cellular substructure were examined and a trend of increasing cell sizes was observed. This trend was attributed to differences in solidification rate and thermal gradients induced by differences in scanning velocity and preheating temperature. A change of the thermal history due to intrinsic preheating could be identified as the main cause of this heterogeneity. It was induced by critical combinations of the energy input and differences in heat transfer conditions by variations of the inter layer time. The microstructural variations were directly correlated to differences in hardness.
In vielen Umgebungen, besonders bei hohen Temperaturen, korrosiven Umgebungen oder auf bewegten oder schlecht zugänglichen Flächen, kann die Temperatur nicht oder nur mit nicht akzeptablem Aufwand mit Berührungsthermometern gemessen werden. Diese Umgebungsbedingungen sind unter anderem in der chemischen Industrie, der Lebensmittel-, Metall-, Glas-, Kunststoff- und Papierherstellung sowie bei der Lacktrocknung anzutreffen. In diesen Bereichen kommen Strahlungsthermometer zum Einsatz. Der VDI-Statusreport zeigt typische Anwendungsfelder von nicht radiometrisch kalibrierten Wärmebildkameras und von radiometrisch kalibrierten Thermografiekameras. Um verlässlich mit spezifizierten Messunsicherheiten berührungslos Temperaturen zu messen, müssen die Strahlungsthermometer und Thermografiekameras nicht nur kalibriert, sondern radiometrisch und strahlungsthermometrisch umfassend charakterisiert werden. Auch die optische Materialeigenschaft, der spektrale Emissionsgrad und die Gesamtstrahlungsbilanz (Strahlung des Messobjekts und der Umgebung) sind bei der industriellen Temperaturmessung von großer Bedeutung. In den letzten Jahrzehnten ist dazu ein umfassendes technisches Regelwerk entstanden, das wir Ihnen mit diesem VDI-Statusreport vorstellen. Manche in den Richtlinien beschriebenen Kennwerte mögen abstrakt wirken. In diesem Statusreport zeigen wir an konkreten Beispielen, was diese Kenngrößen für die berührungslose Temperaturmessung bedeuten. Beispiele von Anwendungen zeigen, wo temperaturmessende Thermografiekameras und ausschließlich bildgebende Wärmebildkameras in der Praxis eingesetzt werden. Mit einer Analyse, welche Themen und Anwendungen derzeit besonders intensiv diskutiert werden, versuchen wir Trends für zukünftige Entwicklungen herauszuarbeiten.
Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 µm) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.
The photoacoustic measurement technique is a powerful yet underrepresented method to characterize the thermal transport properties of thin films. For the case of isotropic low thermal diffusivity samples, such as glasses or polymers, we demonstrate a general approach to extract the thermal conductivity with a high degree of significance. We discuss in particular the influence of thermal effusivity, thermal diffusivity, and sample layer thickness on the significance and accuracy of this measurement technique. These fundamental thermal properties guide sample and substrate selection to allow for a feasible thermal transport characterization. Furthermore, our data evaluation allows us to directly extract the thermal conductivity from this transient technique, without separate determination of the volumetric heat capacity, when appropriate boundary conditions are fulfilled.
Using silica, poly(methyl methacrylate) (PMMA) thin films, and various substrates (quartz, steel, and silicon), we verify the quantitative correctness of our analytical approach.
In this chapter, the current state-of-the-art of in situ monitoring and in situ NDE methods in additive manufacturing is summarized. The focus is set on methods, which are suitable for making statements about the quality and usability of a component currently being manufactured. This includes methods which can be used to determine state properties like temperature or density, other physical properties like electrical or thermal conductivity, the microstructure, the chemical composition, the actual geometry, or which enable the direct detection of defects like cracks, voids, delaminations, or inclusions. Thus, optical, thermographic, acoustic, and electromagnetic methods, as well as methods being suitable for investigating particle and fume emission are presented. The requirements of in situ monitoring methods with a focus on thermographic methods are discussed by considering different additive manufacturing processes like laser powder bed fusion (PBF-LB/M) and direct energy deposition (DED-LB/M). Examples of the successful implementation and applications of such monitoring methods at BAM are given. The in situ monitoring and NDE methods are compared against post-process NDE methods. The advantages and challenges of in situ methods concerning real-time data analysis and the application of AI algorithms are addressed and discussed.
An unusual microstructure, inherent residual stresses and void formation are the three key aspects to control when assessing metallic parts made by LPBF. This talk explains an experiment to unravel the interlinked influence of the two mechanisms for the formation of residual stresses in LPBF: the temperature gradient mechanism and constricted solidification shrinkage. The impact of each mechanism on the shape and magnitudes of the residual stress distribution is described. Combined results from neutron diffraction, X-ray diffraction, computed tomography and in-situ thermography are presented.
Also, influence of scan strategies as well as surface roughness of subjacent layers on void formation is shown. Results from computed tomography and in-situ thermography of a specimen dedicated to study the interaction of the melt pool with layers of powder underneath the currently illuminated surface are presented.
Die thermografische ZfP basiert auf der Wechselwirkung von thermischen Wellen mit Inhomogenitäten. Die Ausbreitung von thermischen Wellen von der Wärmequelle zur Inhomogenität und zur Detektionsoberfläche entsprechend der thermischen Diffusionsgleichung führt dazu, dass zwei eng beieinander liegende Defekte fälschlicherweise als ein Defekt im gemessenen Thermogramm erkannt werden können. Um diese räumliche Auflösungsgrenze zu durchbrechen, also eine Super Resolution zu realisieren, kann die Kombination von räumlich strukturierter Erwärmung und numerischen Verfahren des Compressed Sensings verwendet werden.
Für unsere Arbeiten benutzen wir Hochleistungs-Laser im Kilowatt-Bereich um die Probe entweder hochaufgelöst entlang einer Linie (1D) abzurastern oder strukturiert zu erwärmen. Die Verbesserung des räumlichen Auflösungsvermögens zur Defekterkennung hängt dann im klassischen Sinne direkt von der Anzahl der Messungen ab. Mithilfe des Compressed Sensings und Vorkenntnissen über das System ist es jedoch möglich die Anzahl der Messungen zu reduzieren und trotzdem Super Resolution zu erzielen. Wie viele Messungen notwendig sind und wie groß der Auflösungsgewinn gegenüber der konventionellen thermografischen Prüfung mit flächiger Erwärmung ist, hängt von einer Reihe von Messparametern, der Messstrategie, Probeneigenschaften und den verwendeten Rekonstruktionsalgorithmen ab.
Unsere Studien befassen sich mit dem Einfluss der experimentellen Parameter, wie z.B. der Pulslänge der Laserbeleuchtung und der Größe des Laserspots. Weiterhin haben wir uns mit der Wahl der Parameter in der Rekonstruktion auseinandergesetzt, die einen Einfluss auf das im Compressed Sensing zugrundeliegende Minimierungsproblem haben. Für jeden getesteten Parametersatz wurde eine Rekonstruktionsqualität berechnet. Schließlich wurden die Defektrekonstruktionen basierend auf den Parameternsätzen verglichen, sodass eine Parameterwahl für hohe Rekonstruktionsqualitäten mit thermografischer Super Resolution
empfohlen werden kann.
The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
Die thermografische ZfP basiert auf der Wechselwirkung von thermischen Wellen mit Inhomogenitäten. Die Ausbreitung von thermischen Wellen von der Wärmequelle zur Inhomogenität und zur Detektionsoberfläche entsprechend der thermischen Diffusionsgleichung führt dazu, dass zwei eng beieinander liegende Defekte fälschlicherweise als ein Defekt im gemessenen Thermogramm erkannt werden können. Um diese räumliche Auflösungsgrenze zu durchbrechen, also eine Super Resolution zu realisieren, kann die Kombination von räumlich strukturierter Erwärmung und numerischen Verfahren des Compressed Sensings verwendet werden.
Für unsere Arbeiten benutzen wir Hochleistungs-Laser im Kilowatt-Bereich um die Probe entweder hochaufgelöst entlang einer Linie (1D) abzurastern oder strukturiert zu erwärmen. Die Verbesserung des räumlichen Auflösungsvermögens zur Defekterkennung hängt dann im klassischen Sinne direkt von der Anzahl der Messungen ab. Mithilfe des Compressed Sensings und Vorkenntnissen über das System ist es jedoch möglich die Anzahl der Messungen zu reduzieren und trotzdem Super Resolution zu erzielen. Wie viele Messungen notwendig sind und wie groß der Auflösungsgewinn gegenüber der konventionellen thermografischen Prüfung mit flächiger Erwärmung ist, hängt von einer Reihe von Messparametern, der Messstrategie, Probeneigenschaften und den verwendeten Rekonstruktionsalgorithmen ab.
Unsere Studien befassen sich mit dem Einfluss der experimentellen Parameter, wie z.B. der Pulslänge der Laserbeleuchtung und der Größe des Laserspots. Weiterhin haben wir uns mit der Wahl der Parameter in der Rekonstruktion auseinandergesetzt, die einen Einfluss auf das im Compressed Sensing zugrundeliegende Minimierungsproblem haben. Für jeden getesteten Parametersatz wurde eine Rekonstruktionsqualität berechnet. Schließlich wurden die Defektrekonstruktionen basierend auf den Parameternsätzen verglichen, sodass eine Parameterwahl für hohe Rekonstruktionsqualitäten mit thermografischer Super Resolution empfohlen werden kann.
The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
Das pulverbettbasierte selektive Laserstrahlschmelzen (engl. laser powder bed fusion, L-PBF) ist die am weitesten verbreitete additive Fertigungstechnologie für die Herstellung metallischer Komponenten. Unter der Vielzahl an Einflussfaktoren auf die Qualität und die mechanischen Eigenschaften von L PBF-Bauteilen hat die Zwischenlagenzeit (engl. inter layer time, ILT) bisher kaum Beachtung in der wissenschaftlichen Literatur gefunden, obwohl sie je nach Bauraumausnutzungsgrad stark variieren kann. In diesem Vortrag werden Ergebnisse einer Studie präsentiert, die den Einfluss der ILT in Kombination mit der Bauteilhöhe und unter Berücksichtigung verschiedener Volumenenergiedichten am Beispiel der austenitischen Stahllegierung AISI 316L untersucht. Die Fertigungsprozesse wurden in situ mittels Thermographiekamera überwacht, sodass Informationen über das Abkühlverhalten der Bauteile während des Prozesses gewonnen werden konnten. Es wurden signifikante Effekte der ILT und der Bauteilhöhe auf Wärmeakkumulation, Mikrostruktur, Schmelzbadgeometrie und Härte festgestellt. Ferner konnte ein Anstieg von Defektdichten bei einem gegenseitigen Wechselspiel aus Bauteilhöhe und ILT aufgezeigt werden. Die Zwischenlagenzeit wurde somit als kritischer Faktor für die L-PBF-Fertigung von Realbauteilen identifiziert.
Einer der aussichtsreichsten Ansätze, die Qualität und Sicherheit der gefertigten Teile in der metallbasierten additiven Fertigung (AM) zu erhöhen und die Notwendigkeit aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen (ZfP) nach der Fertigung zu verringern, liegt in dem Einsatz von in-situ Prozessüberwachungstechniken. Viele wichtige Prozessgrößen bei der additiven Fertigung sind thermischer Natur, wie z.B. die Temperatur des Schmelzbades. Aufgrund der Zugänglichkeit zum Werkstück während des Bauprozesses bieten sich optische Verfahren zur Temperaturbestimmung an. Für die Thermografie und Optische Emissionsspektrometrie im IR-Bereich, welche für die in-situ Anwendung prinzipiell als geeignet angesehen werden können, gibt es allerdings noch wenig konkrete praktische Umsetzungen, da die Möglichkeiten und individuellen Grenzen dieser Methoden, angewendet auf AM, noch nicht ausreichend erforscht sind. Aus diesem Grund verfolgt die BAM mit dem Projekt „Process Monitoring of AM“ (ProMoAM) im Themenfeld Material das Ziel, Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Metallbauteile weiterzuentwickeln.
Im Beitrag wird der Fokus auf eine Versuchsserie gelegt, bei der Aufbau von Probekörpern aus dem austenitischen Edelstahl 316L mittels Laser-Pulver-Auftragschweißen (LPA) durch od. mit Hilfe von IR-Spektrometrie und Thermografie in-situ überwacht wurde. Hierbei stellen u.a. die hohe Bandbreite der zu messenden Temperaturen, die Bestimmung der Emissivität und ihre Änderung bei Phasenübergängen des Metalls große experimentelle Herausforderungen dar, wobei jede Methode individuelle Vor- und Nachteile aufweist, welche verglichen werden.
Im Europäischen EMPIR-Projekt „NanoXSpot“ (Measurement of the focal spot size of Xray tubes with spot sizes down to 100 nm) werden neue Messmethoden für Brennflecke von Röntgenröhren entwickelt. Teil des Projektes ist die Entwicklung eines zur Lochkameramethode äquivalenten Messverfahrens für kleine Brennflecke. ASTM E 1165-20, Annex A, beschreibt die Bestimmung von Brennfleckgrößen aus Kantenprofilen von Lochaufnahmen für Röntgenröhren mit Brennflecken > 50 μm. Es wurde bereits vorgeschlagen über die Analyse der richtungsabhängigen Kantenunschärfe einer Lochblende und anschließender CT-Rekonstruktion die Intensitätsverteilung des Brennflecks äquivalent zur Lochkameraaufnahme zu berechnen. Die Lochkameramethode, wie in EN 12543-2 und ASTM E 1165-20 beschrieben, ist im unteren Größenbereich für Mikrofokusröhren nicht geeignet, da Pinholes < 10 μm schwer zu fertigen sind und lange Belichtungszeiten erwartet werden. Mit Hilfe exakt gefertigter Lochblenden sowie strukturierter Targets mit konvergierenden Strukturen wird der Bereich mit der Single-Shot-CT-Methode auf die Messung von Mikrofokusröhren, alternativ zur Vermessung von Kanten oder Strichgruppenkörpern, erweitert. Die rekonstruierten Brennfleckformen werden mit Kanten und Lochkameraaufnahmen quantitativ verglichen, um die Messgenauigkeit zu bewerten. Außerdem werden CNR und Messzeit bestimmt, um die Wirtschaftlichkeit der Verfahren zu bewerten.
Thermografische Super Resolution ermöglicht die Auflösung von Defekten/Inhomogenitäten unterhalb des klassischen Limits, welches durch die Diffusionseigenschaften der thermischen Wellenausbreitung bestimmt wird. Basierend auf einer Kombination aus der Anwendung spezieller Abtaststrategien und einer anschließenden numerischen Optimierungsschritt bei der Datenauswertung hat sich die thermografische Super Resolution bereits bei der Detektion von 1D-Defekten gegenüber den Standard-Thermografieverfahren als überlegen erwiesen. In unserer Arbeit erweitern wir die Möglichkeiten der Methode zur effizienten Detektion und Auflösung von Defektquerschnitten mit einer vollständig 2D-strukturierten Erwärmung.
Der experimentelle Ansatz basiert auf einer wiederholten räumlich strukturierten Erwärmung durch einen Hochleistungslaser. In einem zweiten Nachbearbeitungsschritt werden mehrere kohärente Messungen mittels mathematischer Optimierung und unter Ausnutzung der (Joint-) Sparsity der Defekte innerhalb des Prüfkörpers kombiniert. Als Ergebnis kann eine 2D-sparse Defekt-/ Inhomogenitätskarte erhalten werden. Da die Kombination von räumlich strukturierter Erwärmung und anschließender numerischer Kombination mehrerer kohärenter Messungen nicht nur die Auflösung verbessert, sondern auch die Messkomplexität drastisch erhöht, werden verschiedene Scanstrategien untersucht. Abschließend werden die erhaltenen Ergebnisse mit denen konventioneller thermografischer Prüfverfahren verglichen.
Thermographic super resolution techniques allow the spatial resolution of defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. In this work, we re-port on the extension of this approach towards a full frame 2D super resolution technique. The approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample.
Thermographic super resolution techniques allow the spatial resolution of defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. In this work, we report on the extension of this approach towards a full frame 2D super resolution technique. The approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample
Laser powder bed fusion is used to create near net shape metal parts with a high degree of freedom in geometry design. When it comes to the production of safety critical components, a strict quality assurance is mandatory. An alternative to cost-intensive non-destructive testing of the produced parts is the utilization of in-situ process monitoring techniques. The formation of defects is linked to deviations of the local thermal history of the part from standard conditions. Therefore, one of the most promising monitoring techniques in additive manufacturing is thermography. In this study, features extracted from thermographic data are utilized to investigate the thermal history of cylindrical metal parts. The influence of process parameters, part geometry and scan strategy on the local heat distribution and on the resulting part porosity are presented. The suitability of the extracted features for in-situ process monitoring is discussed.
The quality of additively manufactured components is significantly influenced by the process parameters used during production. Thus, sensors and measuring systems are already commercially available for process monitoring, at least in metal-based additive manufacturing. However, it is not yet possible to detect defects and inhomogeneities directly or indirectly during the building process. The aim of the project ProMoAM is to develop spectroscopic and non-destructive testing methods for the in-situ evaluation of the quality of additively manufactured metal components in laser- or arc-based AM processes. In addition to passive and active methods of thermography, this includes optical tomography, optical emission spectroscopy, eddy current testing, laminography (radiography), X-ray backscattering, particle emission spectroscopy and photoacoustic methods.
This paper presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super resolution (SR) imaging. Photothermal imaging is a well-known technique in active thermography for nondestructive inspection of defects in materials such as metals or composites. A grand challenge of active thermography is to overcome the spatial resolution limitation imposed by heat diffusion in order to accurately resolve each defect. The photothermal SR approach enables to extract high-frequency spatial components based on the deconvolution with the thermal point spread function. However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, hand-crafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, Photothermal-SR-Net is proposed in this paper, which performs deconvolution by deep unfolding considering the underlying physics. This enables to super resolve 2D thermal images for nondestructive testing with a substantially improved convergence rate. Since defects appear sparsely in materials, Photothermal-SR-Net applies trained blocksparsity thresholding to the acquired thermal images in each convolutional layer. The performance of the proposed approach is evaluated and discussed using various deep unfolding and thresholding approaches applied to 2D thermal images. Subsequently, studies are conducted on how to increase the reconstruction quality and the computational performance of Photothermal-SR-Net is evaluated.
Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
Laser powder bed fusion is used to create near net shape metal parts with a high degree of freedom in geometry design. When it comes to the production of safety critical components, a strict quality assurance is mandatory. An alternative to cost-intensive non-destructive testing of the produced parts is the utilization of in-situ process monitoring techniques. The formation of defects is linked to deviations of the local thermal history of the part from standard conditions. Therefore, one of the most promising monitoring techniques in additive manufacturing is thermography. In this study, features extracted from thermographic data are utilized to investigate the thermal history of cylindrical metal parts. The influence of process parameters, part geometry and scan strategy on the local heat distribution and on the resulting part porosity are presented. The suitability of the extracted features for in-situ process monitoring is discussed.
In 2019, 3.1 billion Euro of damage was caused by piped water, accounting for the largest share (53%) of building insurance claims in Germany. In the event of damage, the accurate determination and localization of water ingress is essential to plan for and perform efficient renovations. Neutron probes are already applied successfully on building floors to localize the source of damage and other affected areas. However, additional information about the depth of moisture penetration can only be obtained by the destructive extraction of drilling cores, which is a time- and cost-intensive procedure. With its high sensitivity to water and fast measurement procedure, Ground Penetrating Radar (GPR) can serve as a suitable extension to the neutron probe, enabling more precise characterization of common forms of moisture damage.
In this research project, we study the influence of common types of moisture damage in differing floor constructions using GPR and a neutron probe. A measurement setup with interchangeable layers is used to vary the screed material (cement or anhydrite) and insulation material (Styrofoam, Styrodur, glass wool, perlite), as well as the respective layer thickness. Every configuration is measured for the following main cases: 1) dry state; 2) with a damaged insulation layer and 3) a damaged screed layer.
The evaluation is focused on the extraction of distinctive signal features for GPR, which can be used to classify the underlying case of damage. Furthermore, possible combinations of these features are investigated using multivariate data analysis and machine learning in order to evaluate the influence of different floor constructions.
To validate the developed methods, practical measurements on real damage cases in Germany are carried out and compared to reference data obtained from drilling cores.
We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wavebased inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution.
Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination.
Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination.
Due to the rapid thermal cycles involved in additive manufacturing of metals, high internal stresses and peculiar microstructures occur, which influence the parts mechanical properties. To systematically examine their formation, in-process measurements of the temperature are needed. Since the part emissivity is strongly inhomogeneous and rapidly changing in the process, the applicability of thermography for the determination of thermodynamic temperatures is limited. Measuring the thermal radiation in different wavelengths simultaneously, temperature and emissivity can be separated. Here, we present results of a preliminary study using multispectral thermography to obtain real temperatures and emissivities in directed energy deposition (DED) processes.
Due to the rapid thermal cycles involved in additive manufacturing of metals, high internal stresses and peculiar microstructures occur, which influence the parts mechanical properties. To systematically examine their formation, in-process measurements of the temperature are needed. Since the part emissivity is strongly inhomogeneous and rapidly changing in the process, the applicability of thermography for the determination of thermodynamic temperatures is limited. Measuring the thermal radiation in different wavelengths simultaneously, temperature and emissivity can be separated. Here, we present results of a preliminary study using multispectral thermography to obtain real temperatures and emissivities in directed energy deposition (DED) processes.
Additive manufacturing of metals offers the opportunity to build parts with a high degree of complexity without additional costs, opening a new space for design optimization. However, the processes are highly complex and due to the rapid thermal cycles involved, high internal stresses and peculiar microstructures occur, which influence the parts mechanical properties. To systematically examine the formation of internal stresses and the microstructure, in-process spatially resolved measurements of the part temperature are needed. If the emissivity of the inspected part is known, its thermodynamic temperature can be reconstructed by a suited radiometric model. However, in additive manufacturing of metals, the emissivity of the part surface is strongly inhomogeneous and rapidly changing due to variations of, e.g., the degree of oxidation, the material state and temperature. Thus, here, the applicability of thermography in the determination of thermodynamic temperatures is limited. However, measuring the process thermal radiation at different wavelengths simultaneously enables one to separate temperature and emissivity spatially resolved to obtain further insight into the process. Here, we present results of an initial study using multispectral thermography to obtain real temperatures and emissivities in the powderfree LMD process.
Introduction to ProMoAM
(2021)
Classification of Spot-Welded Joints in Laser Thermography Data Using Convolutional Neural Networks
(2021)
Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this article, we propose an approach for quality inspection of spot weldings using images from laser thermography data. We propose data preparation approaches based on the underlying physics of spot-welded joints, heated with pulsed laser thermography by analyzing the intensity over time and derive dedicated data filters to generate training datasets. Subsequently, we utilize convolutional neural networks to classify weld quality and compare the performance of different models against each other. We achieve competitive results in terms of classifying the different welding quality classes compared to traditional approaches, reaching an accuracy of more than 95 percent. Finally, we explore the effect of different augmentation methods.
The literature has shown that the application of laminography provides advantages as 3D radiographic imaging with depth information for in house and mobile testing. This permits to distinguish between overlapping indications, measure the extension along radiation direction and classify indications as surface open or subsurface
ones as required in critical engineering assessment. This work provides a comparative study and measurements of the three techniques Digital Radiography (DR) with Digital Detector Arrays (DDA), Coplanar Translational Laminography (CTL) and Computed Tomography (CT), applied for composite pipeline inspection. It is demonstrated that CTL and CT provide advantages for the evaluation of pipe-to-pipe connections and the evaluation of adhesive applications. They show indications of discontinuities with higher contrast sensitivity than radiography.
Beyond it, two specimen, namely Phantom 1 and Phantom 2, were developed and manufactured by additive manufacturing to analyze the preferential detection sensitivity and the direction of features and depth information for laminographic measurements. Another goal was to show the laminographic capabilities to distinguish between overlapping discontinuities. CTL is especially suitable for mobile inspection. Special glass fiber reinforced polymer samples (GRP) were manufactured for further analysis and comparisons between the abovementioned techniques. Finally, Phantoms 1 and 2 show the capability of laminography to detect overlapping indications and also show that discontinuities oriented perpendicular to the scan direction have the highest contrast sensitivity for laminographic measurements.
Es wird über die neuen Anforderungen ausgewählter Normen bzw. Normrevisionen informiert und insbesondere auch über die veränderten Parameter, die bei der Prüfpraxis, der Qualitätssicherung in der digitalen Radiographie und bei der Klassifizierung zu berücksichtigen sind. Das wichtigste Projekt ist die Revision der DIN EN ISO 17636-1, -2, RT von Schweißverbindungen, in ISO TC 44 SC 5 WG 1. Hauptaktivität bei ASTM ist gegenwärtig die Überarbeitung der CT-Standards und die Berücksichtigung der Anforderungen an das dimensionelle Messen. Der „Standard Guide for Computed Tomography“, ASTM E 1441, zur Bestimmung von MTF, Kontrast-Detail-Funktion (CDF) und Kontrast-Diskrimination-Diagramm (CDD) wurde revidiert und veröffentlicht. Die Mehrzahl der Hersteller von CT-Anlagen bietet entsprechende Software-Tools an. Weiterhin werden neue Festkörperentwürfe zur Charakterisierung von CT-Anlagen vorgestellt. Die folgenden Revisionen sind bei ASTM derzeit in Bearbeitung: ASTM E 2445, „CR Long Term Stability“ nach einem Round Robin-Test und für DDAs der Standard zur System-Charakterisierung, ASTM E2597/E2597M−14, und zur „DDA Long Term Stability“. Das Spider-Net-Diagramm zur Klassifizierung von DDAs wird um die Position „ISO Material Thickness limit“ erweitert. Der Standard EN 12679 zur Messung der Größe von Gammastrahlern wurde nach Revision unter Berücksichtigung von digitalen Messverfahren veröffentlicht. Die Revision der Standardserie EN 12543 zur Messung der Brennfleckgröße ist mit Verzögerung in Überarbeitung, um die digitalen Detektoren und Messmöglichkeiten mit Bildverarbeitungsprogrammen zu berücksichtigen. Die Messprozedur für Lochkameras wurde grundlegend revidiert und ist harmonisiert mit ASTM E 1165-12(2017). Die gemessenen Brennflecke unterscheiden sich und passen besser zu den Unschärfe-Messungen
mit Doppeldraht BPKs (ISO 19232-5:2018) bei Vergrößerung. Ein Entwurf zur Messung der Brennfleckgröße von nano-Fokusröhren und Mikro-Fokusröhren (< 5 µm) wird derzeit vom Europäischen Metrologie-Programm EMPIR gefördert. Es wird über erste Ergebnisse
informiert.
Composites made up of microparticles embedded in a polymeric matrix have attracted increasing attention due to the possibility of tailoring their physical properties by adding the adequate quantity of fillers. As the concentration of these fillers increases, their connectivity changes drastically at a given threshold and therefore the electrical, thermal and optical properties of these composites are expected to exhibit a percolation effect. In this work, the thermal and electrical conductivities along with the emissivity of Composites composed of carbonyl-iron microparticles randomly distributed in a polyester resin matrix are measured, for volume fractions ranging from 0 to 0.55. It is shown that both the thermal and electrical conductivities increase with the particles’ concentration, such that their percolation threshold appears at volume fractions of 0.46 and 0.38, respectively.
The emissivity, on the other hand, decreases as the fillers’ concentration increases, such that it exhibits a substantial decay at a volume fraction of 0.41. The percolation threshold of the emissivity is thus higher than that of the thermal conductivity, but lower than the electrical conductivity one. This dispersion on the percolation concentration is justified by the different physical mechanisms required to activate the electrical, thermal, and optical
responses of the considered composites. The obtained results thus show that the percolation phenomenon can efficiently be used to enhance or reduce the physical properties of particulate composites.
Die zerstörungsfreie Ermittlung der Materialfeuchte in Baustoffen ist für das Bauwesen von großer Bedeutung, denn ein erhöhter Feuchteeintrag kann zu Schimmelbildung, Alkali-Kieselsäure-Reaktionen, Korrosion etc. führen und somit ein hohes Schadenspotential mit sich bringen. Auch wenn zur qualitativen Lokalisierung möglicher Schad- und Risikostellen bereits zahlreiche zerstörungsfreie Verfahren in der Praxis Anwendung finden, besteht ein Mangel an quantitativen Verfahren, die auch bei niedrigen Feuchtegehalten sensitiv sind. Eine Methode zur zerstörungsfreien und quantitativen Bestimmung des Feuchtegehaltes und der effektiven Porosität ist die 1H-Kernspinresonzanzmethode (NMR). Da NMR sensitiv für die molekulare Beweglichkeit von Wasserstoffprotonen ist, lassen sich Informationen über die Bindungsform und -stärke sowie der Umgebung (Porengröße und Mineralzusammensetzung) der Wasserstoffprotonen gewinnen. Obwohl es bereits seit über 20 Jahren mobile NMR-Messeräte gibt, wird NMR heutzutage immer noch weitestgehend im Labor eingesetzt. Dies liegt daran, dass sie aufgrund der verwendeten Permanentmagnete schwer sind und nur äußerst geringe Eindringtiefen ermöglichen. In einer derzeit laufenden Forschungsarbeit wird deshalb ein speziell für Bohrkerne entworfener NMR-Tomograph eingesetzt. Mit seiner minimalen Echozeit von 50 µs lässt sich (abhängig von der Oberflächenrelaxivität) Wasser bis in nanometergroßen Poren erfassen. Um die Sensitivität von NMR bei Teilsättigung zu untersuchen, wurden verschiedene Sandsteinproben in Exsikkatoren mit relativen Luftfeuchten im Bereich von 33 % bis 96 % gelagert. Als Referenzen dienen zum einen das NMR-Signal bei Vollsättigung und zum anderen die Porengrößenverteilung aus Quecksilberporosimetriemessungen (MIP). Um die NMR-Sensitivität zu bewerten, wird die Korrelation der NMR-Amplitude mit den gravimetrisch ermittelten Feuchtegehalten sowie ein Vergleich der Porosität aus NMR und MIP betrachtet. Zu beachten ist in diesem Zusammenhang, dass sowohl die Reduzierung der Wasserfilmdicke als auch die Verkleinerung von Porengrößen zu einer ähnlichen Verkürzung der T2-Relaxationszeit führt. Als Ausblick wird ein Lösungsansatz vorgestellt, bei dem die NMR-Signale mit der Wasserfilmdickenberechnung basierend auf der relativen Luftfeuchte im Material korreliert werden.
Nach Auftreten eines Feuchteschadens in Fußbodenaufbauten sind sowohl die zeitnahe Feststellung als auch Eingrenzung betroffener Bereiche von besonderer Bedeutung. So können erforderliche Renovierungsmaßnahmen effizient geplant und mögliche Folgeschäden vermieden werden. Zur messtechnischen Beantwortung dieser Fragestellungen werden bereits seit vielen Jahren Neutronensonden eingesetzt, welche allerdings keine Tiefenzuordnung des schadensträchtigen Flüssigwassers zulassen. Hierzu müssen mit hohem zeitlichem und finanziellem Aufwand zerstörende Sondierungsbohrungen vorgenommen werden, welche zukünftig durch den parallelen Einsatz des Radarverfahrens vermieden werden könnten. In systematischen Laborstudien wurden gängige Feuchteschäden an häufig anzutreffenden Fußbodenaufbauten simuliert und deren Einfluss auf das Messsignal untersucht. Hierbei kamen Zementund Anhydritestriche, sowie die Dämmmaterialen Styropor, Styrodur, Glaswolle und Perlite-Schüttung mit variierenden Schichtdicken zum Einsatz, um die vielfältigen Konfigurationen der Praxis abzubilden. Für den gewonnenen Datensatz konnten geeignete Signalmerkmale extrahiert werden, welche mithilfe multivariater Datenauswertung eine Klassifizierung des vorliegenden Schadenfalls zulassen. Zum Ende des Forschungsvorhabens steht besonders die Anwendbarkeit der entwickelten Methoden für die Praxis im Fokus. Hierzu wurden Messungen an realen Schadensfällen durchgeführt und deren Ergebnisse mit den Laboruntersuchungen verglichen. Hierbei stellten sich variierende Schichtdicken, sowie vorkommende Fußbodenheizungen und Armierungsgitter als mögliche Fehlerquellen für eine vollständig automatisierte Auswertung heraus.