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Estimation of heat flux parameters during static gas tungsten arc welding spot under argon shielding
(2017)
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.
The aim of this work is to illustrate the contribution of signal processing techniques in the field of Non-Destructive Evaluation. A component’s life evaluation is inevitably related to the presence of flaws in it. The detection and characterization of cracks prior to damage is a technologically and economically significant task and is of very importance when it comes to safety-relevant measures. The Laser Thermography is the most effective and advanced thermography method for Non-Destructive Evaluation. High capability for the detection of surface cracks and for the characterization of the geometry of artificial surface flaws in metallic samples of laser thermography is particularly encouraging. This is one of the non- contacting, fast and real time detection method. The presence of a vertical surface breaking crack will disturb the thermal footprint. The data processing method plays vital role in fast detection of the surface and sub-surface cracks.
Currently in laser thermographic inspection lacks a compromising data processing algorithm which is necessary for the fast crack detection and also the analysis of data is done as part of post processing. In this work we introduced a raw data based image processing algorithm which results precise, better and fast crack detection. The algorithm we developed gives better results in both experimental and modeling data. By applying this algorithm we carried out a detailed investigation Variation of thermal contrast with crack parameters like depth and width. The algorithm we developed is applied for various surface temperature data from the 2D scanning model and also validated credibility of algorithm with experimental data.