8.3 Thermografische Verfahren
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Thermal waves are solutions of the heat diffusion equation for periodic boundary conditions and can be seen analogously to strongly damped waves. Although the underlying differential equation differs from the wave equation, the essential property for analogy between both equations is linearity such that superposition applies. This linearity is maintained even after a linear transformation, such as the Fourier transform from time to frequency domain. It follows that the temporal superposition principle is already used in active thermography, e.g. in pulsed thermography, as a superposition of many individual frequencies. However, the systematic spatial superposition has not yet been fully exploited, mainly due to a lack of suitable energy sources.
As a first step, we are investigating how thermal wave fields of arbitrary space-time structures can be engineered using structured laser illumination. The proof of principle was shown using a laser coupled projector. Unfortunately, the available optical output power was limited due to the thermal stress limit of the device. That is why we are working towards a more sophisticated moving 1D array of high-power diode lasers. We characterized the novel light source and believe that apart from the benefit of spatial and temporal illumination it can combine the temporal regimes of impulse and lock-in thermography.
In a second step, we investigate moving and oscillating line sources with different line shapes. We use a Green’s Function ansatz to analytically model the thermal wave propagation of structured 1D laser illumination in isotropic materials. Furthermore, we show some methods how they can be implemented. With this technique, we were able to accelerate our detection method firstly presented in for vertical narrow defects by factor three. Generally, we believe that this technique opens up similar opportunities than in other NDE methods. High-resolution ultrasound, for example, is also based on the superposition of single emitters and a recent concept suggests an option to deal with the diffusion wave character of the thermal waves.
Thermographic NDE is based on the interaction of thermal waves with inhomogeneities. These inhomogeneities are related to sample geometry or material composition. Although thermography is suitable for a wide range of inhomogeneities and materials, the fundamental limitation is the diffusive nature of thermal waves and the need to measure their effect radiometrically at the sample surface only. The propagation of the thermal waves from the heat source to the inhomogeneity and to the detection surface results in a degradation in the spatial resolution of the technique. A new concerted ansatz based on a spatially structured heating and a joint sparsity of the signal ensemble allows an improved reconstruction of inhomogeneities. As a first step to establish an improved thermographic NDE method, an experimental setup was built based on structured 1D illumination using a flash lamp behind a mechanical aperture. As a follow-up to this approach, we now use direct structured illumination using a 1D laser array. The individual emitter cells are driven by a random binary pattern and additionally shifted by fractions of the cell period. The repeated measurement of these different configurations with simultaneously constant inhomogeneity allows for a reconstruction that makes use of joint sparsity. With analytical-numerical modelling or numerical FEM simulations, we study the influence of the parameters on the result of non-linear reconstruction. For example, the influence of the illumination pattern as a variable heat flux density and Neumann boundary condition for convolution with the constant Green's function can be studied. These studies can be used to derive optimal conditions for a measurement technique.
Thermographic nondestructive evaluation (NDE) is based on the interaction of thermal waves with inhomogeneities. These inhomogeneities are related to sample geometry or material composition. Although thermography is suitable for a wide range of inhomogeneities and materials, the fundamental limitation is the diffusive nature of thermal waves and the need to measure their effect radiometrically at the sample surface only. The propagation of the thermal waves from the heat source to the inhomogeneity and to the detection surface results in a degradation in the spatial resolution of the technique. A new concerted ansatz based on a spatially structured heating and a joint sparsity of the signal ensemble allows an improved reconstruction of inhomogeneities. As a first step to establish an improved thermographic NDE method, an experimental setup was built based on structured 1D illumination using a flash lamp behind a mechanical aperture. As a follow-up to this approach, we now use direct structured illumination using a 1D laser array. The individual emitter cells are driven by a pseudo-random binary pattern and are additionally shifted by fractions of the cell period. The repeated measurement of these different configurations enables to illuminate each spot of the sample surface in lateral direction. This allows for a reconstruction that makes use of joint sparsity.
The measured data set is processed using super resolution image reconstruction algorithms such as the iterative joint sparsity (IJOSP) algorithm. Using this reconstruction technique and 150 different illumination patterns results in a spatial resolution enhancement of approximately a factor of four compared to the resolution of 5.9 mm for homogenously illuminated thermographic reconstruction.
Further, new data processing techniques have been studied before applying the IJOSP algorithm that are more performant or less prone to errors regarding image reconstruction. The choice of regularization parameters in data processing as well as experimental parameters such as the illumination pattern as a variable heat flux density (i.e., the Neumann boundary condition for convolution with the constant Green's function) have a big influence on the reconstruction goodness. With analytical-numerical modelling and numerical FEM simulations, we studied the influence of the experimental parameters on the result of the non-linear IJOSP reconstruction. This has also been investigated experimentally e.g. using different laser line widths or more measurements per position. These studies are used to derive optimal conditions for a certain measurement image reconstruction technique.
The diffusive nature of heat propagation complicates the separation of two closely spaced defects. This results in a fundamental limitation in spatial resolution. Therefore, super resolution (SR) image reconstruction can be used. SR processing techniques based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern.
This paper presents the results after applying SR algorithms such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Two different data processing strategies are evaluated and discussed regarding their influence on the reconstruction goodness as well as their complexity. Moreover, the degradation of the SR reconstruction by the choice of regularization parameters in data processing is discussed.
The application of both SR techniques that are evaluated in this paper results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects. The fundamental difference between both SR techniques is their complexity.
The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern.
This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown.
The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects.
The separation of two closely located defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows an improved reconstruction of closely located defects. This new technique has also been studied using 1D laser arrays in active thermography.
The post-processing can be roughly described by two steps: 1. Finding a sparse basis representation using a reconstruction algorithm such as the Fourier transform, 2. Application of an iterative joint sparsity (IJOSP) method to the firstly reconstructed data. For this reason, different methods in post-processing can be compared using the same measured data set.
The focus in this work was the variation of reconstruction algorithms in step 1 and its influence on the results from step 2. More precise, the measured thermal waves can be transformed to virtual (ultrasound) waves that can be processed by applying ultrasound reconstruction algorithms and finally the super resolution algorithm. Otherwise, it is also possible to make use of a Fourier transform with a subsequent super resolution routine. These super resolution thermographic image reconstruction techniques in post-processing are discussed and evaluated regarding performance, accuracy and repeatability.
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.
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 separation of two closely located defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used.
The measured thermal waves can be transformed to virtual (ultrasound) waves that can be processed by applying ultrasound reconstruction algorithms and finally the super resolution algorithm. Otherwise, it is also possible to make use of a Fourier transform with a subsequent super resolution routine.
These super resolution thermographic image reconstruction techniques in post-processing are discussed and evaluated regarding performance, accuracy and repeatability.
In this paper we propose super resolution measurement and post-processing strategies that can be applied in thermography using laser line scanning. The implementation of these techniques facilitates the separation of two closely spaced defects and avoids the expected deterioration of spatial resolution due to heat diffusion. The experimental studies were performed using a high-power laser as heat source in combination with pulsed thermography measurements (step scanning) or with continuous heating measurements (continuous scanning). Our work shows that laser line step scanning as well as continuous scanning both can be used within our developed super resolution (SR) techniques. Our SR techniques make use of a compressed sensing based algorithm in post- processing, the so-called iterative joint sparsity (IJOSP) approach. The IJOSP method benefits from both - the sparse nature of defects in space as well as from the similarity of each measurement. In addition, we show further methods to improve the reconstruction quality e.g. by simple manipulations in thermal image processing such as by considering the effect of the scanning motion or by using different optimization algorithms within the IJOSP approach. These super resolution image processing methods are discussed so that the advantages and disadvantages of each method can be extracted. Our contribution thus provides new approaches for the implementation of super resolution techniques in laser line scanning thermography and informs about which experimental and post-processing parameters should be chosen to better separate two closely spaced defects.
This paper presents different super resolution reconstruction techniques to overcome the spatial resolution limits in thermography. Pseudo-random blind structured illumination from a onedimensional laser array is used as heat source for super resolution thermography. Pulsed thermography measurements using an infrared camera with a high frame rate sampling lead to a huge amount of data. To handle this large data set, thermographic reconstruction techniques are an essential step of the overall reconstruction process. Four different thermographic reconstruction techniques are analyzed based on the Fourier transform amplitude, principal component analysis, virtual wave reconstruction and the maximum thermogram. The application of those methods results in a sparse basis representation of the measured data and serves as input for a compressed sensing based algorithm called iterative joint sparsity (IJOSP). Since the thermographic reconstruction techniques have a high influence on the result of the IJOSP algorithm, this paper Highlights their Advantages and disadvantages.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
In this work we focus on our most recent studies to super resolution (SR) laser thermography. The goal of SR nondestructive testing methods is to facilitate the separation of closely spaced defects. We explain how to combine laser scanning with SR techniques. It can be shown that stepwise as well as continuous scanning techniques are applicable. Finally, we discuss the effect of experimental parameters and im-age processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
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.
This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
Laser excited super resolution thermal imaging for nondestructive inspection of internal defects
(2020)
A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple measurement events. This concerted approach of experimental measurement strategy and numerical optimization enables the resolution of internal defects and outperforms conventional thermographic inspection techniques.
Laser excited super resolution thermal imaging for nondestructive inspection of internal defects
(2020)
A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple measurement events. This concerted approach of experimental measurement strategy and numerical optimization enables the resolution of internal defects and outperforms conventional thermographic inspection techniques.
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.
The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern.
This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown.
The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects.
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.
Additive manufacturing (AM) opens the route to a range of novel applications.However, the complexity of the manufacturing process poses a challenge for the production of defect-free parts with a high reliability. Since process dynamics and resulting microstructures of AM parts are strongly influenced by the involved temperature fields, thermography is a valuable tool for process surveillance. The high process temperatures in metal AM processes allow one to use cameras usually operating in the visible spectral range to detect the thermally emitted radiation from the process. In our work, we compare the results of first measurements during the manufacturing processes of a commercial laser metal deposition (LMD) setup and a laser beam melting (LBM) setup using a MWIR camera with those from a VIS high-speed camera with band pass filter in the NIR range.
Additive manufacturing (AM) offers a range of novel applications. However, the manufacturing process is complex and the production of defect-free parts with a high reliability is still a challenge. Thermography is a valuable tool for process surveillance, especially in metal AM processes. The high process temperatures allow one to use cameras usually operating in the visible spectral range. Here, we compare the results of first measurements during the manufacturing process of a commercial laser metal deposition (LMD) setup using a MWIR camera with those from a VIS high-speed camera with band pass filter in the NIR range.
In flash thermography, the temperature transient is strongly influenced by the temporal shape of the heating pulse for samples with high thermal diffusivity or very thin samples. Here, we present a closed phenomenological approximation of the temporal shape of pulses of Xe-flash lamps. It is a non-stitched solution, has a simple Laplace transform and is suitable for different lamps and energy settings. It is demonstrated that simulated temperature transients, based on this approximation, are well consistent with experimental data.
Aktuell werden Prozessmonitoringsysteme in der additiven Fertigung (AM) zur Überwachung der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie zumindest im metallbasierten AM schon kommerziell angeboten. Weitere Verfahren aus den Bereichen der Optik, Spektroskopie und zerstörungsfreien Prüfung werden in der Literatur als geeignet für die in-situ Anwendung bezeichnet, es finden sich aber nur wenige Berichte über konkrete Umsetzungen in die Praxis.
Die Bundesanstalt für Materialforschung und -prüfung hat ein neues Projekt gestartet, dessen Ziel die Entwicklung von Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Bauteile in AM-Prozessen mit Laser- bzw. Lichtbogenquellen ist. Verschiedene Verfahren der zerstörungsfreien Prüfung, wie Thermografie, optische Tomografie, optische Emissionsspektroskopie, Wirbelstromprüfung und Laminografie werden in verschiedenen AM-Prozessen zum Einsatz gebracht und die Ergebnisse fusioniert. Die evaluierten Ergebnisse werden mit Referenzverfahren wie Computertomografie und Ultraschall-Tauchtechnik verglichen. Ziel ist eine deutliche Reduzierung aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen nach der Fertigung des Bauteiles und zugleich eine Verringerung von Ausschussproduktion.
Hier wird das Projekt als Ganzes vorgestellt und der Fokus auf verschiedene Methoden der Temperaturmessung mit Hilfe der Thermografie gelegt. Anforderungen an die Messtechnik für verschiedene AM-Systeme werden diskutiert und erste experimentelle Ergebnisse werden präsentiert.
Aktuell werden Prozessmonitoringsysteme in der additiven Fertigung (AM) zur Überwachung der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie zumindest im metallbasierten AM schon kommerziell angeboten. Weitere Verfahren aus den Bereichen der Optik, Spektroskopie und zerstörungsfreien Prüfung werden in der Literatur als geeignet für die in-situ Anwendung bezeichnet, es finden sich aber nur wenige Berichte über konkrete Umsetzungen in die Praxis.
Die Bundesanstalt für Materialforschung und -prüfung hat ein neues Projekt gestartet, dessen Ziel die Entwicklung von Verfahren des Prozessmonitorings zur in-situ Bewertung der Qualität additiv gefertigter Bauteile in AM-Prozessen mit Laser- bzw. Lichtbogenquellen ist. Verschiedene Verfahren der zerstörungsfreien Prüfung, wie Thermografie, optische Tomografie, optische Emissionsspektroskopie, Wirbelstromprüfung und Laminografie werden in verschiedenen AM-Prozessen zum Einsatz gebracht und die Ergebnisse fusioniert. Die evaluierten Ergebnisse werden mit Referenzverfahren wie Computertomografie und Ultraschall-Tauchtechnik verglichen. Ziel ist eine deutliche Reduzierung aufwändiger und zeitintensiver, zerstörender oder zerstörungsfreier Prüfungen nach der Fertigung des Bauteiles und zugleich eine Verringerung von Ausschussproduktion.
Hier wird das Projekt als Ganzes vorgestellt und der Fokus auf verschiedene Methoden der Temperaturmessung mit Hilfe der Thermografie gelegt. Anforderungen an die Messtechnik für verschiedene AM-Systeme werden diskutiert und erste experimentelle Ergebnisse werden präsentiert.
The project ProMoAM is presented. The goal of the project is to evaluate which NDT techniques or combination of techniques is suited for in-situ quality assurance in additive manufacturing of metals. To this end, also 3d-data fusion and visualization techniques are applied. Additional ex-situ NDT-techniques are used as references for defect detection and quantification. Feasability studies for NDT-techniques that are presently not applicable for in-situ use are performed as well.
The presentation gives a brief overview of the whole project and the different involved NDT-techniques.
For metal-based additive manufacturing, sensors and measuring systems for monitoring of the energy source, the build volume, the melt pool and the component geometry are already commercially available. Further methods of optics, spectroscopy and non-destructive testing are described in the literature as suitable for in-situ application, but there are only a few reports on practical implementations.
Therefore, a new BAM project aims to develop process monitoring methods for the in-situ evaluation of the quality of additively manufactured metal components. In addition to passive and active thermography, this includes optical tomography, optical emission and absorption spectroscopy, eddy current testing, laminography, X-ray backscattering and photoacoustic methods. These methods are used in additive manufacturing systems for selective laser melting, laser metal deposition and wire arc additive manufacturing. To handle the sometimes huge amounts of data, algorithms for efficient preprocessing are developed and characteristics of the in-situ data are extracted and correlated to defects and inhomogeneities, which are determined using reference methods such as computer tomography and metallography. This process monitoring and fusion of data of different measurement techniques should result in a significant reduction of costly and time-consuming, destructive or non-destructive tests after the production of the component and at the same time reduce the production of scrap.
Here, first results of simultaneous measurements of optical emission spectroscopy and thermography during the laser metal deposition process using 316L as building material are presented. Temperature values are extracted from spectroscopic data by fitting of blackbody emission spectra to the experimental data and compared with results from a thermographic camera. Measurements with and without powder flow reveal significant differences between welding at a pristine metal surface and previously melted positions on the build plate, illustrating the significant influence of the partial oxidation of the surface during the first welding process on subsequent welding. The measurement equipment can either be mounted stationary or following the laser path. While first results were obtained in the stationary mode, future applications for online monitoring of the build of whole parts in the mobile mode are planned.
This research was funded by BAM within the focus area Material.
Im Bauwesen werden häufig Polymerbeschichtungen auf Beton eingesetzt um zum einen ein bestimmtes Aussehen zu schaffen und zum anderen das Bauteil vor Alterung, Verschleiß und Schädigung zu schützen. Für die Erfüllung aller genannten Ziele ist das Erreichen einer vom Hersteller festgelegten Sollschichtdicke essentiell. Daher wird die Dicke der Beschichtung nach erfolgtem Schichtauftrag überprüft. Für den in diesem Zusammenhang anspruchsvollen mineralischen Untergrund Beton stehen bislang allerdings nur zerstörende Prüfverfahren zur Verfügung. Aus diesem Grund wurden im Rahmen des Projektes IRKUTSK in Kollaboration mit der IBOS GmbH ein auf aktiver Thermografie basierendes Verfahren sowie ein Gerät für den vor-Ort-Einsatz entwickelt, mit dessen Hilfe eine zerstörungsfreie Schichtdickenbestimmung möglich ist.
Das Poster erläutert das Messverfahren und die Umsetzung in der Praxis. Es werden Messergebnisse sowie der Vergleich mit zerstörend ermittelten Schichtdicken gezeigt. Hierbei konnte eine sehr gute Übereinstimmung nachgewiesen werden. Die notwendigen Erweiterungen des zugrundeliegenden Modells in Bezug auf die einzelnen Parameter werden erläutert und diskutiert.
Die hier vorgestellte Arbeit ist Teil des ZIM-Projektes IRKUTSK mit dem Förderkennzeichen KF2201089AT4 und ist gefördert durch das Bundesministerium für Wirtschaft und Energie aufgrund eines Beschlusses des Deutschen Bundestages.
Additive manufacturing of metals gains increasing relevance in the industrial field for part production. However, especially for safety relevant applications, a suitable quality assurance is needed. A time and cost efficient route to achieve this goal is in-situ monitoring of the build process. Here, the BAM project ProMoAM (Process monitoring in additive manufacturing) is briefly introduced and recent advances of BAM in the field of in-situ monitoring of the L-PBF and the LMD process using thermography are presented.
Results of the project ProMoAM (Process monitoring in additive manufacturing) presented. Results from in-situ eddy current testing, optical emission spectroscopy, thermography, optical tomography as well as particle and gas emission spectroscopy are summarized and correlated to results from computed tomography for future in-situ defect detection.
Introduction to ProMoAM
(2021)
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.
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.
Thermography is one on the most promising techniques for in-situ monitoring for metal additive manufacturing processes. The high process dynamics and the strong focus of the laser beam cause a very complex thermal history within the produced specimens, such as multiple heating cycles within single layer expositions. This complicates data interpretation, e.g., in terms of cooling rates. A quantity that is easily calculated is the time a specific area of the specimen is at a temperature above a chosen threshold value (TOT). Here, we discuss variations occurring in time-over-threshold-maps during manufacturing of a defect free cuboid specimen.
In-situ Prozessüberwachung in der additiven Fertigung von Metallen mittels optischer Verfahren
(2020)
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. Bereits jetzt werden erste Messsysteme zur Kontrolle der Energiequelle, des Bauraums, des Schmelzbades und der Bauteilgeometrie kommerziell angeboten. Weitere ZfP Verfahren, wie z.B. die aktive und passive Thermografie, werden in der Literatur als geeignet für die in-situ Anwendung angesehen, allerdings gibt es 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 zunächst das Projekt vorgestellt und anschließend der Fokus auf eine Messserie gelegt, in der Probekörper aus dem austenitischen Edelstahl 316L mit lokal variierenden Prozessparametern mittels selektiven Laserschmelzen (L-PBF) aufgebaut wurden. Der Bauprozess wurde hierbei durch das maschineneigene, koaxial arbeitende Photodiodensystem (Melt-Pool-Monitoring), einer Mittelwellen-Infrarotkamera und einer optischen Tomografiekamera im sichtbaren Wellenlängenbereich (Langzeitbelichtung für die Dauer eines Lagenaufbaus mit einer CMOS-Kamera mit hoher Ortsauflösung) simultan überwacht. Als Referenz für diese Methoden wurden die Probekörper mittels Computertomografie untersucht. Für die dabei anfallenden teils großen Datenmengen wurden Algorithmen für ein effizientes Preprocessing entwickelt. Es wurden Merkmale der Messdaten in Korrelation zu Fehlern und Inhomogenitäten extrahiert, welche für die einzelnen Methoden vergleichend vorgestellt und diskutiert werden.
Additive manufacturing (AM) opens the route to a range of novel applications. However, the complexity of the manufacturing process poses a challenge to produce defect-free parts with a high reliability. Since process dynamics and resulting microstructures of AM parts are strongly influenced by the involved temperature fields and cooling rates, thermography is a valuable tool for process monitoring. Another approach to monitor the energy input into the part during process is the use of optical tomography.
Common visual camera systems reach much higher spatial resolution than infrared thermography cameras, whereas infrared thermography provides a much higher temperature dynamic. Therefore, the combined application increases the depth of information. Here, we present first measurement results using a laser beam melting setup that allows simultaneous acquisition of thermography and optical tomography from the same point of view using a beam splitter. A high-resolution CMOS camera operating in the visible spectral range is equipped with a near infrared bandpass filter and images of the build plate are recorded with long-term exposure during the whole layer exposing time. Thus, areas that reach higher maximum temperature or are at elevated temperature for an extended period of time appear brighter in the images. The used thermography camera is sensitive to the mid wavelength infrared range and records thermal videos of each layer exposure at an acquisition rate close to 1 kHz.
As a next step, we will use computer tomographic data of the built part as a reference for defect detection.
This research was funded by BAM within the focus area Materials.
The industrial use of additive manufacturing for the production of metallic parts with high geometrical complexity and lot sizes close to one is rapidly increasing as a result of mass individualisation and applied safety relevant constructions. However, due to the high complexity of the production process, it is not yet fully understood and controlled, especially for changing (lot size one) part geometries.
Due to the thermal nature of the Laser-powder bed fusion (L-PBF) process – where parts are built up layer-wise by melting metal powder via laser - the properties of the produced part are strongly governed by its thermal history. Thus, a promising route for process monitoring is the use of thermography. However, the reconstruction of temperature information from thermographic data relies on the knowledge of the surface emissivity at each position on the part. Since the emissivity is strongly changing during the process due to phase changes, great temperature gradients, possible oxidation, and other potential influencing factors, the extraction of real temperature data from thermographic images is challenging. While the temperature development in and around the melt pool, where melting and solidification occur is most important for the development of the part properties. Also, the emissivity changes are most severe in this area, rendering the temperature deduction most challenging.
A possible route to overcome the entanglement of temperature and emissivity in the thermal radiation is the use of hyperspectral imaging in combination with temperature emissivity separation (TES) algorithms. As a first step towards the combined temperature and emissivity determination in the L-PBF process, here, we use a hyperspectral line camera system operating in the short-wave infrared region (0.9 µm to 1.7 µm) to measure the spectral radiance emitted. In this setup, the melt pool of the L-PBF process migrates through the camera’s 1D field of view, so that the radiation intensities are recorded simultaneously for multiple different wavelength ranges in a spatially resolved manner. At sufficiently high acquisition frame rate, an effective melt pool image can be reconstructed. Using the grey body approximation (emissivity is independent of the wavelength), a first, simple TES is performed, and the resulting emissivity and temperature values are compared to literature values. Subsequent work will include reference measurements of the spectral emissivity in different states allowing its analytical parametrisation as well as the adaption and optimisation of the TES algorithms. An illustration of the proposed method is shown in Fig.1.
The investigated method will allow to gain a deeper understanding of the L-PBF process, e.g., by quantitative validation of simulation results. Additionally, the results will provide a data basis for the development of less complex and cheaper sensor technologies for L-PBF in-process monitoring (or for related process), e.g., by using machine learning.
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.
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.
Pulse and flash thermography are experimental techniques which are widely used in the field of non-destructive testing for materials characterization and defect detection. We recently showed that it is possible to determine quantitatively the thickness of semitransparent polymeric solids by fitting of results of an analytical model to experimental flash thermography data, for both transmission and reflection configuration. However, depending on the chosen experimental configuration, different effective optical absorption coefficients had to be used in the model to properly fit the respective experimental data, although the material was always the same. Here, we show that this effect can be explained by the wavelength dependency of the absorption coefficient of the sample material if a polychromatic light source, such as a flash lamp, is used. We present an extension of the analytical model to describe the decay of the heating irradiance by two instead of only one effective absorption coefficient, greatly extending its applicability. We show that using this extended model, the experimental results from both measurement configurations and for different sample thicknesses can be fitted by a single set of parameters. Additionally, the deviations between experimental and modeled surface temperatures are reduced compared to a single optimized effective absorption coefficient.
Im Bauwesen werden Polymerbeschichtungen auf Beton häufig eingesetzt um zum einen, ein bestimmtes Aussehen zu schaffen und zum anderen, das Bauteil vor Alterung, Verschleiß und Schädigung zu schützen. Für praktisch alle Ziele ist die Wirkung von der eigens dafür definierten Schichtdicke der Polymerbeschichtung abhängig. Daher wird die Dicke der Beschichtung nach erfolgtem Schichtauftrag überprüft. Für den in diesem Zusammenhang anspruchsvollen mineralischen Untergrund Beton stehen bislang allerdings nur zerstörende Prüfverfahren zur Verfügung. Aus diesem Grund wurden im Rahmen des Projektes IRKUTSK ein auf aktiver Thermografie basierendes Verfahren sowie ein Gerät für den vor-Ort-Einsatz entwickelt, mit dessen Hilfe eine zerstörungsfreie Schichtdickenbestimmung möglich ist. Hier wird ein kurzer Einblick in das zur Schichtdickenbestimmung entwickelte Thermografieverfahren gegeben. Die Besonderheiten bei der quantitativen Auswertung, die durch die Teiltransparenz der Polymerbeschichtungen auftreten, werden erläutert. Die Funktion des Verfahrens für einlagige Systeme wird anhand von Labormessungen mit verschiedenen optischen Quellen zur thermischen Anregung illustriert.
Additive manufacturing (AM) offers a range of novel applications. However, the manufacturing process is complex and the production of defect-free parts with high reliability and durability is still a challenge. Thermography is a valuable tool for process surveillance, especially in metal AM processes. The high process temperatures allow one to use cameras usually operating in the visible spectral range. Here, we compare the results of measurements during the manufacturing process of a commercial laser metal deposition setup using a mid-wavelength-IR camera with those from a visual spectrum high-speed camera with band pass filter in the near-IR range.
Thermography is one on the most promising techniques for in-situ monitoring of metal additive manufacturing processes. Especially in laser powder bed fusion processes, the high process dynamics and the strong focus of the laser beam cause a very complex thermal history within the produced specimens, such as multiple heating cycles within single layer expositions. This complicates data interpretation, e.g., in terms of cooling rates. A quantity that is easily calculated is the time a specific area of the specimen is at a temperature above a chosen threshold value (TOT). Here, we discuss variations occurring in time-over-threshold-maps during manufacturing of an almost defect free cuboid specimen.
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 offers a range of novel applications. However, the manufacturing process is complex and the production of almost defect-free parts with high reliability and durability is still a challenge. Thermography is a valuable tool for process surveillance, especially in metal additive manufacturing processes. The high process temperatures allow one to use cameras usually operating in the visible spectral range. Here, we compare the results of measurements during the manufacturing process of a commercial laser metal deposition setup using a mid wavelength infrared camera with those from a short wavelength infrared camera and those from a visual spectrum high-speed camera with band pass filter in the near infrared range.
Die Anwendung von Polymerbeschichtungen im Bauwesen hat über die letzten Dekaden stetig zugenommen. Neben ästhetischen Aspekten sind vor allem die Verbesserung der Dauerhaftigkeit des Bauwerks und damit einhergehend die Verlängerung der Nutzungsdauer ausschlaggebende Gründe für die Wahl einer Beschichtung. Um die jeweiligen Bauteile vor Alterung, Verschleiß und Schädigung effektiv und zielsicher schützen zu können ist die Einhaltung der von den Herstellern vorgegebenen Mindestschichtdicken von essenzieller Bedeutung. Aus diesem Grund ist es notwendig die Schichtdicke der Beschichtung nach erfolgter Applikation zu überprüfen. Für den in diesem Zusammenhang anspruchs-vollen mineralischen Untergrund Beton stehen für die Baustelle bislang allerdings nur zerstörende Prüfverfahren zur Verfügung.
Aufbauend auf den Ergebnissen zur photothermischen Schichtdickenbestimmung von Polymerbeschichtungen im Rah-men des Forschungsprojektes IRKUTSK werden derzeit im WIPANO Projekt PHOBOSS weitreichende Untersuchungen durchgeführt, um diese zerstörungsfreie Untersuchungsmethode auf den Baubereich anzuwenden. Ziel des WIPANO Projektes PHOBOSS ist neben der Verfeinerung und Validierung der Mess-und Auswertungsmethodik die Erstellung eines Normenentwurfes welcher Rahmenbedingungen und Anforderungen für Messung und Messgerät enthalten soll.
Im Rahmen dieser Veröffentlichung werden Einblicke in das zur Schichtdickenbestimmung entwickelte Thermografie-verfahren gegeben. Die Funktionsweise des Verfahrens für die Messung von Oberflächenschutzsystemen wird anhand von Labor- und In Situ-Messungen illustriert und der für die Messungen verwendete Prototyp vorgestellt.
Within the perspective of increasing reliability of AM processes, real-time monitoring allows part inspection while it is built and simultaneous defect detection. Further developments of real-time monitoring can also bring to self-regulating process controls. Key points to reach such a goal are the extensive research and knowledge of correlations between sensor signals and their causes in the process.
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.
Laser Powder Bed Fusion (L-PBF), as one of the most promising production process in the field of metal additive manufacturing, enables traditional constructive solutions to be rethought and the manufacturing of optimized components according to the "form follows function" principle. The most significant obstacle for a broad industrial application of the L-PBF process is the inadequate quality assurance during the manufacturing process so far, leading to high production costs. Although several mainly camera based commercial in-process monitoring systems are already available, a deep understanding of the interpretation of the monitored data and correlation with actual defects is still lacking. One reason for this is the reduction of the complex process signature to just one measurement value.
The focus of this contribution is the presentation of the multispectral optical tomography as alternative to single measurand in-situ monitoring systems. The potential of this approach is hereby shown on L-PBF printed samples with induced process instabilities. Beyond that, an in-house developed L-PBF printer for further testing of multi-sensor in-situ monitoring systems is presented.
Since metal additive manufacturing (AM) becomes more and more established in industry, also the cost pressure for AM components increases. One big cost factor is the quality control of the manufactured components. Reliable in-process monitoring systems are a promising route to lower scrap rates and enhance trust in the component and process quality.
The focus of this contribution is the presentation and comparison of two optical tomography based multi measurand in-situ monitoring approaches for the L-PBF process: the bicolor- and the RGB-optical tomography. The classical optical tomography (OT) is one of the most common commercial in-situ monitoring techniques in industrial L-PBF machines. In the OT spatial resolved layer-images of the L-PBF process are taken from an off-axis position in one near infrared wavelength window. In addition to the explanatory powers classical OT, both here presented approaches enable the determination of the maximum surface temperature. In contrast to thermography that may also yield maximum temperature information, the needed equipment is significantly cheaper and offers a higher spatial resolution. Both approaches are implemented at a new in-house developed L-PBF system (Sensor-based additive manufacturing machine - SAMMIE). SAMMIE is specifically designed for the development and characterization of in-situ monitoring systems and is introduced as well.
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.
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.
In-situ monitoring of the Laser Powder Bed Fusion build process via bi- chromatic optical tomography
(2022)
As metal additive manufacturing (AM) is entering industrial serial production of safety relevant components, the need for reliable process qualification is growing continuously. Especially in strictly regulated industries, such as aviation, the use of AM is strongly dependent on ensuring consistent quality of components. Because of its numerous influencing factors, up to now, the metal AM process is not fully controllable. Today, expensive part qualification processes for each single component are common in industry.
This contribution focusses on bi-chromatic optical tomography as a new approach for AM in-situ quality control. In contrast to classical optical tomography, the emitted process radiation is monitored simultaneously with two temperature calibrated cameras at two separate wavelength bands. This approach allows one to estimate the local maximum temperatures during the manufacturing process, thus increases the comparability of monitoring data of different processes. A new process information level at low investment cost is reachable, compared to, e.g., infrared thermography.
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.
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.
Pulsed thermography is a well-known non-destructive testing technique and has proven to be a valuable tool for examination of material defects. Material defects are often simulated by flat-bottom holes (FBH) or grooves. Typically, analytical 1D models are used to determine the defect depth of FBHs, grooves or delaminations. However, these models cannot take into account lateral heat flows, or only to a limited extent (semi-empirical model). They are therefore limited by the FBHs aspect ratio (diameter to remaining wall thickness), to ensure that the heat flow above the defect can still be described one-dimensionally. Here, we present an approach for quantitative determination of the geometry of FBH or grooves. For this purpose, the results of a numerical 2D model are fitted to experimental data, e.g., to determine simultaneously the defect depth of a FBHs or groove and its diameter or width, respectively. The model takes lateral heat flows into account as well as thermal losses. Figure 1 shows the temperature increase of a pulsed thermography measurement at three different locations on the sample. The numerical model is fitted to the experimental data (red lines) to quantify the groove. The numerical simulation matches the experimental data well.
Pulsed thermography is a well-known non-destructive testing technique and has proven to be a valuable tool for evaluation of material defects. Material defects are often simulated by flat-bottom holes (FBH) or grooves. Typically, analytical 1D models are used to determine the defect depth of FBHs, grooves or delaminations. However, these models cannot take into account lateral heat flows, or only to a limited extent (semi-empirical model). Their applicability is therefore limited by the FBHs aspect ratio (diameter to remaining wall thickness), to ensure that the heat flow above the defect can still be described one-dimensionally. Additionally, the surfaces of semi-transparent materials have to be blackened to absorb the radiation energy on the surface of the material. Without surface coatings, these models cannot be used for semi-transparent materials. Available 1D analytical models for determination of sample or layer thicknesses also do not take into account lateral heat flows.
Here, we present an approach for quantitative determination of the geometry of FBHs or grooves in semi-transparent materials by considering lateral heat flow. For this purpose, the results of a numerical 2D model are fitted to experimental data, e.g., to determine simultaneously the defect depth of a FBH or groove and its diameter or width, respectively. The model considers semi-transparency of the sample within the wavelength range of the excitation source as well as of the IR camera and thermal losses at its surfaces. Heat transport by radiation within the sample is neglected. It supports the use of an arbitrary temporal shape of the heating pulse to properly describe the measurement conditions for different heat sources.
Pulsed thermography is a well-known non-destructive testing technique and has proven to be a valuable tool for examination of material defects, to determine thermal material parameters, and the thickness of test specimens through calibration or mathematical models. However, the application to semitransparent materials is quite new and demanding, especially for semitransparent materials like epoxy, polyamide 12, or glass fiber reinforced polymers with epoxy or polyamide matrix.
In order to describe the temporal temperature evolution in such materials, which are recorded with an infrared camera during pulse thermography experiments, much more influences have to be considered, compared to opaque materials:
- The wavelength of the excitation source and the spectral range of the infrared camera
- The angles between the specimen, the excitation source and the infrared camera
- The area behind the specimen
- The roughness of the material surface
- The scattering mechanism within the material
Here, we will consider all these influences and describe how they can be treated mathematically in analytical or numerical models (using COMSOL Multiphysics software). These models describe the temperature development during the pulse thermography experiment in reflection and transmission configuration. By fitting the results of the mathematical models to experimental data it is possible to determine the thickness or the optical and thermal properties of the specimen.
Iterative numerical 2D-modeling for quantification of material defects by pulsed thermography
(2018)
Pulsed thermography is a well-known non-destructive testing technique and has proven to be a valuable tool for examination of material defects. Typically, analytical 1D models are used to determine the defect depth of flat-bottom holes (FBH), grooves or delamination. However, these models cannot take into account lateral heat flows, or only to a limited extent. They are therefore limited by the FBHs aspect ratio (diameter to remaining wall thickness), to ensure that the heat flow above the defect can still be described one-dimensionally. Here, we present an approach for quantitative determination of the geometry for FBH or grooves. For this purpose, the results of a numerical 2D model are fitted to experimental data, e.g., to determine simultaneously the defect depth of a groove or FBH and its diameter of width. The model takes lateral heat flows into account as well as thermal losses. Figure 1 shows the temperature increase of a pulsed thermography measurement at three different locations on the sample. The numerical model is fitted to the experimental data (red lines) to quantify the groove. The numerical simulation matches the experimental data well.
Iterative numerical 2D-modelling for quantification of material defects by pulsed thermography
(2019)
This paper presents a method to quantify the geometry of defects such as flat bottom holes (FBH) and notches in opaque materials by a pulse thermography (PT) experiment and a numerical model. The aim was to precisely describe PT experiments in reflection configuration with a simple and fast numerical model in order to use this model and a fit algorithm to quantify defects within the material. The algorithm minimizes the difference between the time sequence of a line shaped region of interest (ROI) on the surface (above the defect) from the PT experiment and the numerical data. Therefore, the experimental data can be reconstructed with the numerical model. In this way, the defect depth of a notch or FBH and its width or diameter was determined simultaneously. A laser was used for heating which was widened to a top hat spatial profile to ensure homogeneous illumination (rectangular impulse profile in time). The numerical simulation considers heating conditions and takes thermal losses due to convection and radiation into account. We quantified the geometry of FBH and notches in steel and polyvinyl chloride plasticized (PVC-U) materials with an accuracy of < 5 %.
Pulse thermography (PT) has proven to be a valuable non-destructive testing method to identify and quantify defects in fiber-reinforced polymers. To perform a quantitative defect characterization, the heat diffusion within the material as well as the material parameters must be known. The heterogeneous material structure of glass fiber-reinforced polymers (GFRP) as well as the semitransparency of the material for optical excitation sources of PT is still challenging. For homogeneous semitransparent materials, 1D analytical models describing the temperature distribution are available.
Here, we present an analytical approach to model PT for laterally inhomogeneous semitransparent materials.We show the validity of the model by considering different configurations of the optical heating source, the IR camera, and the differently coated GFRP sample. The model considers the lateral inhomogeneity of the semitransparency by an additional absorption coefficient. It includes additional effects such as thermal losses at the samples surfaces, multilayer systems with thermal contact resistance, and a finite duration of the heating pulse. By using a sufficient complexity of the analytical model, similar values of the material parameters were found for all six investigated configurations by numerical fitting.
Material defects in fiber reinforced polymers such as delaminations can rapidly degrade the material properties or can lead to the failure of a component. Pulse thermography (PT) has proven to be a valuable tool to identify and quantify such defects in opaque materials. However, quantification of delaminations within semitransparent materials is extremely challenging. We present an approach to quantify delaminations within materials being semitransparent within the wavelength ranges of the optical excitation sources as well as of the infrared (IR) camera. PT experimental data of a glass fiber reinforced polymer with a real delamination within the material were reconstructed by one dimensional (1D) mathematical models. These models describe the heat diffusion within the material and consider semitransparency to the excitation source as well to the IR camera, thermal losses at the samples surfaces and a thermal contact resistance between the two layers describing the delamination. By fitting the models to the PT data, we were able to determine the depth of the delamination very accurately. Additionally, we analyzed synthetic PT data from a 2D simulation with our 1D-models to show how the thermal contact resistance is influenced by lateral heat flow within the material.
Die zerstörungsfreie Prüfung von metallischen Bauteilen hergestellt mit additiver Fertigung (Additive Manufacturing - AM) gewinnt zunehmend an industrieller Bedeutung. Grund dafür ist die Feststellung von Qualität, Reproduzierbarkeit und damit auch Sicherheit für Bauteile, die mittels AM gefertigt wurden. Jedoch wird noch immer ex-situ geprüft, wobei Defekte (z.B. Poren, Risse etc.) erst nach Prozessabschluss entdeckt werden. Übersteigen Anzahl und/oder Abmessung die vorgegebenen Grenzwerte für diese Defekte, so kommt es zu Ausschuss, was angesichts sehr langer Bauprozessdauern äußerst unrentabel ist. Eine Schwierigkeit ist dabei, dass manche Defekte sich erst zeitverzögert zum eigentlichen Materialauftrag bilden, z.B. durch thermische Spannungen oder Schmelzbadaktivitäten. Dementsprechend sind reine Monitoringansätze zur Detektion ggf. nicht ausreichend.
Daher wird in dieser Arbeit ein Verfahren zur aktiven Thermografie an dem AM-Prozess Laser Powder Bed Fusion (L-PBF) untersucht. Das Bauteil wird mit Hilfe des defokussierten Prozesslasers bei geringer Laserleistung zwischen den einzelnen gefertigten Lagen unabhängig vom eigentlichen Bauprozess erwärmt. Die entstehende Wärmesignatur wird ort- und zeitaufgelöst durch eine Infrarotkamera erfasst. Durch diese der Lagenfertigung nachgelagerte Prüfung werden auch zum Bauprozess zeitversetzte Defektbildungen nachweisbar.
In dieser Arbeit finden die Untersuchungen als Proof-of-Concept, losgelöst vom AM-Prozess, an einem typischen metallischen Testkörper statt. Dieser besitzt eine Nut als oberflächlichen Defekt. Die durchgeführten Messungen finden an einer eigens entwickelten L-PBF-Forschungsanlage innerhalb der Prozesskammer statt. Damit wird ein neuartiger Ansatz zur aktiven Thermografie für L-PBF erforscht, der eine größere Bandbreite an Defektarten auffindbar macht. Der Ansatz wird validiert und Genauigkeit sowie Auflösungsvermögen geprüft. Eine Anwendung am AM-Prozess wird damit direkt forciert und die dafür benötigten Zusammenhänge werden präsentiert.
Die additive Fertigung von metallischen Bauteilen (Additive Manufacturing - AM; auch 3D-Druck genannt) bietet eine Vielzahl an Vorteilen gegenüber konventionellen Fertigungsmethoden. Durch den schichtweisen Auftrag und das selektive Aufschmelzen von Metallpulver im Laser Powder Bed Fusion Prozess (L-PBF) sind u.a. optimierte und flexibel anpassbare Designs und die Nutzung von neuartigen Materialien möglich. Aufgrund der Komplexität des AM-Prozesses und der Menge an Einflussfaktoren ist eine Qualitätssicherung der gefertigten Bauteile unabdingbar. Verschiedene in-situ Monitoringansätze werden bereits angewendet, jedoch findet eine dedizierte Prüfung erst im Nachgang der Fertigung ex-situ statt. Der Grund dafür ist, dass die Entstehung von geometrischen Abweichungen und Defekten auch zeitversetzt zum eigentlichen Materialauftrag und damit auch zum Monitoring stattfinden kann. Die Notwendigkeit geeigneter in-situ Prüfmethoden für L-PBF, um die Erforderlichkeit einer Nacharbeitung frühzeitig festzustellen und Ausschuss zu vermeiden ist angesichts kostenintensiver Ausgangsstoffe und einer oftmals mehrstündigen bis mehrtägigen Prozessdauer besonders hoch.
Daraus motiviert wird im Rahmen des Projektes ATLAMP die Möglichkeit der aktiven Laserthermografie mit Hilfe des defokussierten Fertigungslasers untersucht. Damit ist, bei vergleichsweise geringer Laserleistung, eine zerstörungsfreie Prüfung mittels Flying Spot Thermografie möglich. Diese findet jeweils anschließend an die Fertigung einer Schicht statt, womit der reale Status des Bauteils im Verlauf des AM-Prozesses geprüft wird.
Als Grundlage dafür werden im Rahmen dieser Arbeit mit AM gefertigte, defektbehaftete Probekörper zunächst losgelöst vom Fertigungsprozess untersucht. Damit werden die Grundlagen für den neuartigen Ansatz der aktiven in-situ Laserthermografie im L-PBF-Prozess mittels des Fertigungslasers geschaffen. Auf diese Weise lassen sich auch zeitversetzt auftretende Defekte zerstörungsfrei im Prozessverlauf feststellen und eine aussagekräftige Qualitätssicherung des Ist-Zustands des Bauteils erreichen.
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.
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.
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.
Die zerstörungsfreie Prüfung von metallischen Bauteilen hergestellt mit additiver Fertigung (Additive Manufacturing - AM) gewinnt zunehmend an industrieller Bedeutung. Grund dafür ist die Feststellung von Qualität, Reproduzierbarkeit und damit auch Sicherheit für Bauteile, die mittels AM gefertigt wurden. Jedoch wird noch immer ex-situ geprüft, wobei Defekte (z.B. Poren, Risse etc.) erst nach Prozessabschluss entdeckt werden. Übersteigen Anzahl und/oder Abmessung die vorgegebenen Grenzwerte für diese Defekte, so kommt es zu Ausschuss, was angesichts sehr langer Bauprozessdauern äußerst unrentabel ist. Eine Schwierigkeit ist dabei, dass manche Defekte sich erst zeitverzögert zum eigentlichen Materialauftrag bilden, z.B. durch thermische Spannungen oder Schmelzbadaktivitäten. Dementsprechend sind reine Monitoringansätze zur Detektion ggf. nicht ausreichend.
Daher wird in dieser Arbeit ein Verfahren zur aktiven Thermografie an dem AM-Prozess Laser Powder Bed Fusion (L-PBF) untersucht. Das Bauteil wird mit Hilfe des defokussierten Prozesslasers bei geringer Laserleistung zwischen den einzelnen gefertigten Lagen unabhängig vom eigentlichen Bauprozess erwärmt. Die entstehende Wärmesignatur wird ort- und zeitaufgelöst durch eine Infrarotkamera erfasst. Durch diese der Lagenfertigung nachgelagerte Prüfung werden auch zum Bauprozess zeitversetzte Defektbildungen nachweisbar.
In dieser Arbeit finden die Untersuchungen als Proof-of-Concept, losgelöst vom AM-Prozess, an einem typischen metallischen Testkörper statt. Dieser besitzt eine Nut als oberflächlichen Defekt. Die durchgeführten Messungen finden an einer eigens entwickelten L-PBF-Forschungsanlage innerhalb der Prozesskammer statt. Damit wird ein neuartiger Ansatz zur aktiven Thermografie für L-PBF erforscht, der eine größere Bandbreite an Defektarten auffindbar macht. Der Ansatz wird validiert und Genauigkeit sowie Auflösungsvermögen geprüft. Eine Anwendung am AM-Prozess wird damit direkt forciert und die dafür benötigten Zusammenhänge werden präsentiert.
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.
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 (AM) techniques have risen to prominence in many industrial sectors. This rapid success of AM is due to the freeform design, which offers enormous possibilities to the engineer, and to the reduction of waste material, which has both environmental and economic advantages. Even safety-critical parts are now being produced using AM. This enthusiastic penetration of AM in our daily life is not yet paralleled by a thorough characterization and understanding of the microstructure of materials and of the internal stresses of parts. The same holds for the understanding of the formation of defects during manufacturing. While simulation efforts are sprouting and some experimental techniques for on-line monitoring are available, still little is known about the propagation of defects throughout the life of a component (from powder to operando/service conditions). This Issue was aimed at collecting contributions about the advanced characterization of AM materials and components (especially at large-scale experimental facilities such as Synchrotron and Neutron sources), as well as efforts to liaise on-line process monitoring to the final product, and even to the component during operation. The goal was to give an overview of advances in the understanding of the impacts of microstructure and defects on component performance and life at several length scales of both defects and parts.
Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature increase is measured at the samples surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm.
The main drawback in radiometric imaging is the degradation of the spatial resolution with increasing depth, which results in blurred images for deeper lying structures. We circumvent this degradation with blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. We demonstrate this by imaging a line pattern and a star-shaped structure through a metal sheet with a resolution four times better than the width of the thermal point-spread-function. The ground-breaking concept of super-resolution can be transferred from optics to diffusive imaging by defining a thermal point-spread-function similar to the Abbe limit for a certain optical wavelength.
Using an infrared camera for radiometric imaging allows the contactless temperature measurement of multiple surface pixels simultaneously. From the measured surface data, a sub-surface structure, embedded inside a sample or tissue, can be reconstructed and imaged when heated by an excitation light pulse. The main drawback in radiometric imaging is the degradation of the spatial resolution with increasing depth, which results in blurred images for deeper lying structures. We circumvent this degradation with blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. The ground-breaking concept of super-resolution can be transferred from optics to thermographic imaging.
Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature evolution is measured at the sample’s surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. The structured illumination is realized by parallel laser lines from a vertical-cavity surface-emitting laser (VCSEL) array controlled by a random binary pattern generator. By using 150 different patterns of structured illumination and our iterative joint sparsity algorithm, it was possible to resolve 1 mm thick lines at a distance down to 0.5 mm, which results in a resolution enhancement of approximately a factor of four compared to the resolution of 5.9 mm for homogenous illuminated thermographic reconstruction.
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.
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.
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.
Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades
(2023)
. 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.
A powerful tool to understand, demonstrate and explain the limits of the pulsed technique in terms of detectability and localizability of AM keyhole pores has been assessed by comparing the active thermographic approach (both experimental and FEM simulations) to Computed Tomography results;
✓ µCT results demonstrate that the intended defect geometry is not achieved; indeed a network of voids (microdefects consisting of small sharp-edged hollows with a complicated, almost fractal, inner surface) was found;
✓ both Exp-PT and FEM results explains clearly why no indication of defect related to the thermal contrasts could be found during the investigation of an uncoated surface. However, the application of further data evaluations focusing on the thermal behavior and emissivity evaluation (PPT post data processing) enable the detection of some defects;
✓ coating facilitates a closer inspection of inner defects, but inhomogeneities of the coating could impair the spatial resolution and lead to the emergence of hotspots (the FEM simulation reached its limit with this extreme geometry where a 25 µm thin disc is considered at a 1 cm thick specimen in millisecond time resolution);
✓ both Exp-PT and FEM results allow the conclusion that very short pulses of 200 ms or shorter should be sufficient to detect these defects below, but near the surface; besides a short duration of the thermal phenomenon it should be emphasized, about 0.04 s (high frame rate camera);
Additive manufacturing (AM) technologies, generally called 3D printing, are widely used because their use provides a high added value in manufacturing complex-shaped components and objects. Defects may occur within the components at different time of manufacturing, and in this regard, non-destructive techniques (NDT) represent a key tool for the quality control of AM components in many industrial fields, such as aerospace, oil and gas, and power industries. In this work, the capability of active thermography and eddy current techniques to detect real imposed defects that are representative of the laser powder bed fusion process has been investigated. A 3D complex shape of defects was revealed by a μCT investigation used as reference results for the other NDT methods. The study was focused on two different types of defects: porosities generated in keyhole mode as well as in lack of fusion mode. Different thermographic and eddy current measurements were carried out on AM samples, providing the capability to detect volumetric irregularly shaped defects using non-destructive methods.
Active thermography is a fast, contactless and non-destructive technique that can be used to detect internal defects in different types of material. Volumetric irregularities such as the presence of pores in materials produced by the Additive Manufacturing processes can strongly affect the thermophysical and the mechanical properties of the final component.
In this work, an experimental investigation aimed at detecting different pores in a sample made of stainless AISI 316L produced by Laser Powder Bed Fusion (L-PBF) was carried out using pulsed thermography in reflection mode. The capability of the technique and the adopted setups in terms of geometrical and thermal resolution, acquisition frequency and energy Density of the heating source were assessed to discern two contiguous pores as well as to detect a single pore. Moreover, a quantitative indication about the minimum resolvable pore size among the available and analysed defects was provided. A powerful tool to assess the Limits and the opportunities of the pulsed technique in terms of detectability and localizability was provided by comparing active thermography results to Computed Tomography as well as a related Finite Element Analysis (FEA) to simulate the pulsed heating transfer with Comsol.
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.
Mit additiven Fertigungsverfahren hergestellte Bauteile und Produkte aus Kunststoffen werden zunehmend nicht mehr nur als Prototypen, sondern als voll funktionsfähige Bauteile und Produkte gefertigt. Bedingt durch die Fertigungsprozesse und den schichtweisen Aufbau resultieren physikalische Materialeigenschaften, die stark von den Fertigungsparametern abhängen und zudem anisotrop sind. Von den Fertigungsparametern werden auch die Oberflächeneigenschaften beeinflusst, sodass zu erwarten ist, dass sich die Beständigkeit gegenüber äußeren Umwelteinflüssen bei additiv gefertigten Bauteilen von der konventionell gefertigter unterscheiden kann. Nachfolgend wird daher die Entwicklung eines Qualitätssicherungskonzeptes basierend auf spektroskopischen und zerstörungsfreien Prüfverfahren vorgestellt, in dem der Alterungsprozess von mittels Fused Deposition Modelling (FDM) und mittels Lasersintering (LS) hergestellten Probekörpern untersucht wird.
Mit additiven Fertigungsverfahren hergestellte Bauteile und Produkte aus Kunststoffen werden zunehmend nicht mehr nur als Prototypen, sondern als voll funktionsfähige Bauteile und Produkte gefertigt. Bedingt durch die Fertigungsprozesse und den schichtweisen Aufbau resultieren physikalische Materialeigenschaften, die stark von den Fertigungsparametern abhängen und zudem anisotrop sind. Von den Fertigungsparametern werden auch die Oberflächeneigenschaften beeinflusst, sodass zu erwarten ist, dass sich die Beständigkeit gegenüber äußeren Umwelteinflüssen bei additiv gefertigten Bauteilen von der konventionell gefertigter unterscheiden kann. Nachfolgend wird daher die Entwicklung eines Qualitätssicherungskonzeptes basierend auf spektroskopischen und zerstörungsfreien Prüfverfahren vorgestellt, in dem der Alterungsprozess von mittels Fused Deposition Modelling (FDM) und mittels Lasersintering (LS) hergestellten Probekörpern untersucht wird.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2022)
Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging.
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.
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.
Im weitverbreiteten Fall der thermografischen ZfP sollen Defekte im Probeninneren detektiert werden. Da diese eine Inhomogenität darstellen, genügt jegliche Mess- und Datenverarbeitungstechnik, die diese Inhomogenität als Kontrast in der transienten Temperaturverteilung herausarbeitet. Ein üblicher Ansatz ist eine extrem kurze und intensive Blitzlampenbeleuchtung zusammen mit einer nachträglichen Fourier-Transformation zu verwenden. Für die zusätzliche Tiefenbestimmung werden entweder rein phänomenologische Ansätze, semi-analytische Ansätze mit Kalibrationsmessungen oder Fits an analytische bzw. numerische Modelle verwendet. Ein üblicher semi-analytischer Ansatz ist z.B. die Analyse des Abknickens der transienten Abkühlkurve. Problematisch ist das schnelle Abklingen der Amplitude auf Rauschniveau und damit die inhärente Beschränkung der Tiefenreichweite. Eine äquivalente Beschreibung der Wärmeleitung ist über sehr stark gedämpfte thermische Diffusionswellen möglich. Die Eindringtiefe ist dann gleich der thermischen Diffusionslänge. Der semi-analytische Ansatz über normales Least-Squares-Fitting funktioniert für 1D-Schicht-Systeme sehr gut, versagt aber für höherdimensionale Messprobleme. Genau hier setzt eine seit Kurzem bekannte Transformation der diffusen Temperaturentwicklung (bzw. des Realteils der Diffusionswelle) in eine propagierende virtuelle Temperaturwelle an. Dieses sog. Virtual-Wave-Konzept stellt sich selbst als ein weiteres inverses Problem dar. Der Nutzen dieser in einer linearen virtuellen Zeitdomäne propagierenden Welle überkompensiert den numerischen Mehraufwand jedoch deutlich. Zusammen mit neuen Technologien in der Erwärmung durch Hochleistungs-Laser-Arrays und in der Datenakquisition durch kHz-Kameras erlaubt dieser Ansatz eine signifikante Verbesserung der Tiefenreichweite in der Impuls-Thermografie. Im Beitrag werden experimentelle Ergebnisse an einer additiv hergestellten Metallprobe mit überdeckten Schlitzen vorgestellt, die eine Detektion dieser Defekte bis zu einem Seitenverhältnis von Defektbreite/Defekttiefe ~ 0,25 erlauben, also ca. 4 mal tiefer als die übliche Faustformel.
Zur Gewährleistung der Dauerhaftigkeit von Bauteilen sind regelmäßige Prüfungen notwendig. Für oberflächennahe Risse wurde bereits das Potenzial von Flying-Spot-Untersuchungen gezeigt, bei denen das Messfeld mit einem Laserpunkt, z.B. mittels eines Laserscanners, abgerastert wird. Eine Beschleunigung der Messung durch die Verwendung von Laserlinien ist möglich, wobei die Detektierbarkeit von Rissen u.a. von ihrer Ausrichtung zur Scanrichtung abhängt. Zudem können bei stark gekrümmten Oberflächen, wie z.B. denen von Turbinenschaufeln oder Maschinenteilen mit einem einzelnen stationären Messaufbau nur ein Teil der Oberfläche mit aktiver Thermografie auf Risse untersucht werden da die begrenzte Tiefenschärfe der optischen Systeme (Laser und Kamera)die mechanischen Nachführung innerhalb des Schärfentiefe-Bereichs erforderlich macht.
Um eine vollständige Untersuchung der Oberfläche durchzuführen, sind daher mehrere Perspektiven notwendig. Die hier angewandte Laserthermografie erzeugt dabei die Relativbewegung durch die Manipulation des Prüfobjektes mit einem Roboterarm, welcher es erlaubt, komplexe Oberflächen abzuscannen. Es erfolgt ein systematisches Abfahren mit einer Laserlinie entlang zuvor geplanter Bahnen der gesamten erreichbaren Oberfläche. Da der Roboterarm das Prüfobjekt trägt, sind die eingesetzten Messsysteme unbeeinflusst. Die Bewegung des Prüfobjektes ist dabei mit vielen Freiheitsgraden möglich, was eine Optimierung für das Messproblem erlaubt. Es können unter anderem die Scangeschwindigkeit, Laserleistung, Laserspotgeometrie, Laserwellenlänge, Scanschema und Kamerabildrate variiert werden. Mithilfe der Positionsdaten des Roboterarms kann jedem Punkt auf dem Prüfkörper ein Temperaturverlauf zugeordnet werden, um einen ortsaufgelösten Temperaturverlauf zu erzeugen. Das Ziel ist es, die oberflächennahen Defekte zu detektieren und deren Position auf der Oberfläche des 3D Models positionsgenau darstellen zu können.
In diesem Vortrag werden die Ergebnisse zur robotergestützten Thermografie an unterschiedlichsten Prüfkörpern vorgestellt. Vorteile gegenüber herkömmlichen Methoden werden erläutert und aktuelle Herausforderungen auf der Hard- und Softwareseite für den praktischen Einsatz diskutiert.
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.