A multi-physics modelling of a static Gas Tungsten Arc Welding (GTAW) operation has been established in order to estimate the heat flux exchanged between the arc plasma and the work-piece. The heat flux was described with a Gaussian function where two parameters required to be estimated: process efficiency and radial distribution. An inverse heat transfer problem (ihtp) has been developed in the aim to estimate these parameters from experimental data. Levenberg-Marquardt algorithm was used as the regularization method in addition to an iterative process. The experiment consisted in a static spot weld with GTAW process. The weld spot was on for 5 s under Argon shielding gas, 2.4 mm pure tungsten electrode on a SS304L disc. Temperatures were measured with thermocouples and weld pool growth monitored with a high speed camera. The experimental data were used to solve the ihtp what led to values such as 0.7 for process efficiency and average radial distribution of 1.8 mm.
Zusammenfassung
In diesem Beitrag werden zerstörungsfreie Untersuchungen mittels aktiver Thermografie an Probekörpern aus CFK und GFK mit
unterschiedlichen künstlichen Fehlstellen vorgestellt. Dabei wird die zeitliche und örtliche Temperaturverteilung nach der
Erwärmung mit Blitzlampen oder mit einem Infrarot-Strahler mit einer Infrarot-Kamera erfasst. Zur späteren Rekonstruktion
der Messdaten wurde ein numerisches Modell entwickelt. Dazu war die Bestimmung der thermophysikalischen und optischen
Materialeigenschaften erforderlich, was in diesem Beitrag ebenfalls beschrieben wird. Die Ergebnisse der numerischen
Modellierung werden mit den experimentellen Untersuchungen der aktiven Thermografie verglichen. Weiterhin werden die
experimentellen Untersuchungen hinsichtlich der beiden Materialsysteme CFK und GFK und
unter Berücksichtigung der Teiltransparenz des GFK-Materials sowie der unterschiedlichen Anregungsquellen bewertet.
Online (passive) thermographic inspection of overlap joints of aluminium and zinc coated steel sheets made by cold metal transfer weld brazing process was explored. Different experimental trials were conducted for demonstrating the feasibility of thermographic inspection to detect the porosities, improper weld bead and to differentiate the pre weld temperature. The whole process was monitored using infrared cameras in different wavelength region. Image analysis algorithms were developed to reconstruct the thermal images that contain the signatures of the weld defects and to extract the pre weld temperature and its evolution with distance from the centre of the weld torch. Post-weld radiography lends strong support to the observations
Particle reinforced polymer matrix composites (PMC) are widely used in the military aviation industry as a stealth coating for incident radar attenuation. These coatings are made up of many layers of different materials with varying thicknesses. In this study, we used terahertz (THz) spectral range by means of time-domain spectroscopy (TDS) to examine the thickness of iron particle reinforced polyurethane Radar Absorbing Paint (FE-PU-RAP) composite coatings non-destructively. For accurate estimation of the individual layer thickness in multi-layer coatings, precise knowledge of the material properties of the individual layers is a prerequisite. Hence, standalone samples of the individual layers have been initially employed to extract the material properties, such as the refractive index, absorption coefficient, etc. Then, the accurate thickness estimation by the time-of-flight measurement principle has been carried out using the reflected THz pulses. Further, since the individual reflected pulses from the multi-layered sample are overlapping in nature due to the optically thin coating thickness, a sparse deconvolution technique has been utilized for extracting each individual reflected time instant. The scattering from the iron particles also provides a challenge to the identification of the interface signals. This was addressed by optimizing the regularization parameter in the sparse deconvolution algorithm. With this technique, accurate estimation of each of the individual layers in the multi-layer sample has been accomplished, otherwise difficult non-destructively.
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