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- Additive Manufacturing (9)
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- Joint sparsity (3)
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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 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 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.
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.
Despite of the significant advances in additive manufacturing (AM) process optimization there is still a lack of experimental results and understanding regarding the mechanical behavior and its relationship with the microstructural features of AM-parts, especially in loading conditions typical for safety-relevant applications. Within the scope of the presented ongoing investigations, a basic microstructural characterization, tensile tests at room and elevated temperature (400°C) as well as a characterization of the fatigue behavior of additively manufactured Ti-6Al-4V in the low cycle fatigue regime are carried out in the as-built state. After failure, different techniques are used to describe the failure mechanisms of the specimens. The AM-Specimens are provided by the Fraunhofer institute for production systems and design technology and investigated at the BAM following the philosophy of the TF-Project AGIL.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements.
Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold.
Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users.
The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively).
First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments.
Four materials were investigated in pH 13 solution for 14 days
- 3D-Printer-Polymer was completely resolved
- PVC has no noticeable decrease in weight
- (VitaPro) glass filter for the sensor protector, has weight loss 2.7 %
- The epoxy resin has increased by 1.8 % due to moisture expansion
Different concrete samples were prepared for the validation of the systems.
RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring.
Der Fokus des Arbeitsfelds ist die messtechnisch fundierte Anwendung der 3D-Verfahrenskombination zur Lösung vielfältiger Messaufgaben mit optimaler Datenqualität für interne und externe Kunden.
Das setzt insbesondere eine jeweils problembezogene Messmethodik voraus. Dazu setzen wir kameragestützte 3D-Koordinatenmessverfahren ein, die auf dem fotogrammetrischen Prinzip der Bildtriangulation beruhen. Darunter fallen folgende miteinander flexibel kombinierbare Verfahrensmodifikationen: Mehrbildfotogrammetrie, Messadapter für Geometriemerkmale, Streifenprojektionsverfahren, statische bis hochdynamische Stereofotogrammetrie auf Punktebasis oder aufgabenangepasster Oberflächenmuster und mechanisch-optische Taster.
KonSens (Kommunizierende Sensorsysteme für die Bauteil- und Umweltüberwachung) - Projektergebnisse
(2019)
Im Projekt KonSens werden für die Anwendungsbeispiele bauteilintegrierte Sensorik für Betonkomponenten und mobile Multigassensorik Sensorsysteme in Form von Funktionsmustern entwickelt, validiert und angewendet. Schwerpunkte liegen einerseits in der Detektion und Bewertung von Korrosionsprozessen in Beton und andererseits in der Detektion und Quantifizierung sehr geringer Konzentrationen toxischer Gase in der Luft. Dabei ist die Adaption der sensorischen Methoden aus dem Labor in reale Messumgebungen inklusive geeigneter Kommunikationstechnik ein wichtiger Aspekt.