A cross-time study has been made on the erosion behaviour of Gas-Tungsten Arc Welding (GTAW) for pure tungsten electrode. Its behaviour during arcing was analyzed and compared from the points of view of metallurgical changes in electrode due to long-term operation. Metallographic studies of the electrodes indicate that the crack formation and grain growth during periodic temperature variations. These observations are discussed theoretically based on the experimental results and the thermal expansion parameters of Tungsten.

Current research and development processes of novel welding consumables constitutes a great cost and requires a lot of time and resources. LNU WML has requested a novel small batch GTAW welding consumables manufacturing process that is cost-, time-, and resource-efficient. The study was conducted in accordance to DFSS, a product developing process under the overarching scientific engineering method “Systems Engineering”. The DFSS process consists of four stages, where stage one and two were completed.  This has resulted in the development of three novel concepts, and key parameters has been established. One novel concept has been selected by the client and an experiment has been conducted that proves the principle functionality of the novel concept.  Recommendations on how to proceed to a finished, usable product is expressed as a recommendation of a continuation of the DFSS-process, a conduction of a secondary experiment and suggestions for key parameters.

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Le développement des structures de grains se formant durant les procédés de soudage par fusion a un large impact sur les propriétés et la résistance mécaniques des assemblages. Des défauts, tels que la fissuration à chaud, sont aussi liés à la texturation de grains propre à l'étape de solidification. La simulation directe du développement tri-dimensionnelle (3D) des structures de grains dans ces procédés, à l'échelle industrielle, est rarement proposée. Dans ce travail, une modélisation couplée 3D Automate Cellulaire (CA) - Eléments Finis (FE) est proposée pour prédire la formation des structures de grains dans les procédés de soudage multipasses GTAW (Gas Metal Arc Welding) et GMAW (Gas Metal Arc Welding). A l'échelle macroscopique, la modélisation FE permet la résolution des équations de conservation de la masse, de l'énergie et de la quantité de mouvement pour l'ensemble du domaine en s'appuyant sur un maillage adaptatif. Pour le procédé GMAW avec apport de matière, le modèle FE est enrichi et développé dans une approche level set (LS) afin de modéliser l'évolution de l'interface métal / air due au développement du cordon de soudure. Le domaine FE contient ainsi la pièce étudiée et l'air environnant dans lequel le cordon se développe. Les calculs FE sont couplés avec l'approche CA utilisée pour modéliser le développement de la structure de grains. Un maillage fixe ('maillage CA') est superposé au maillage adaptatif FE ('maillage FE'). Les champs macroscopiques propres au maillage FE sont ainsi interpolés entre le maillage adaptatif FE et le maillage fixe CA. Une nouvelle stratégie d'allocation / désallocation de la grille de cellules CA est ensuite utilisée basée sur l'allocation / désallocation des éléments du maillage CA. La grille CA est constituée d'un ensemble régulier de cellules cubiques superposées au domaine soudée. A l'échelle micro-, la grille est utilisée afin de simuler les étapes de fusion et solidification, à la frontière entre le domaine pâteux et le bain liquide, durant le processus de soudage. Les évolutions de températures des cellules sont définies par interpolation du maillage CA. Un couplage du modèle avec les chemins de solidification et les évolutions enthalpiques tabulés est aussi implémenté, permettant de suivre la thermique et les évolutions de fractions de phase propre à l'évolution du procédé. Avec de réduire les temps de calcul et la quantité de mémoire informatique nécessaire à ces simulations, une optimisation des maillages FE/CA et des tailles de cellules CA est proposée pour les deux approches FE et CA. La modélisation 3D proposée est appliquée à la simulation de la formation des structures de solidification formées durant le soudage GTAW et GMAW multipasses de pièces d'acier inoxydables de nuances UR 2202. Dans le procédé GTAW, l'influence de l'évolution des structures de grains selon les paramètres procédés est étudiée. L'orientation normale des grains avec l'augmentation de la vitesse de soudage est montrée. Dans le procédé GMAW, la modélisation permet de simuler la refusion et la croissance des grains des couches successives. De manière générale, les structures de grains prédites montrent qualitativement les évolutions attendues présentées dans la littérature.

A microestrutura e a composição química dos aços inoxidáveis duplex são responsáveis pela sua resistência mecânica e sua resistência à corrosão que, geralmente, é superior aos aços inoxidáveis ferríticos e austeníticos convencionais. A soldagem destes materiais causa tanto alteração de microestrutura como de composição química, que podem ser alteradas dependendo dos processos de soldagem, dos parâmetros de soldagem, da utilização ou não de metal de adição e da composição química do gás de proteção, nos processos que utilizam proteção gasosa. No caso dos aços inoxidáveis duplex baixa liga, a solidificação é completamente ferrítica, podendo produzir tamanho de grão exagerado no metal de solda e na ZAC. O objetivo deste trabalho é de avaliar o efeito da freqüência de pulsação do processo TIG autógeno na soldagem de aços inoxidáveis duplex baixa liga. Foram soldadas chapas de aços inoxidáveis duplex baixa liga UNS S32304 e UNS S32101 (lean duplex), sem metal de adição e empregando-se argônio como gás de proteção. A soldagem foi executada com o processo TIG, mantendo-se a energia de soldagem constante, de 340 J/mm, e variando-se a freqüência de pulsação entre 1, 5, 10 e 20 Hz. As microestruturas resultantes tanto no metal de solda, região central e região sem mistura, bem como na zona afetada pelo calor foram caracterizadas através de microscopia ótica. Os resultados mostraram que, na soldagem autógena, independente de ter ou não a pulsação da corrente, ocorre um aumento no tamanho do grão da zona fundida devido a solidificação ferrítica deste aço. Comparando-se os resultados do tamanho do grão e da fração volumétrica de ferrita no metal de solda, notouse um aumento no tamanho de grão e na fração volumétrica da ferrita com o aumento da freqüência de pulsação. / The microstructure and chemical composition of duplex stainless steel are responsible for their mechanical strength and corrosion resistance. The welding of these materials produces a change in the microstructure and chemical composition. These changes depend on: welding processes, welding parameters, the use or absence of filler metal and composition of shielding gas in processes that use shielding gas. In the case of lean duplex stainless steel the solidification is fully ferritic, which may produce an excessive grain size in the weld metal and in the heat affected zone (HAZ). The main goal of this paper is to evaluate the effect of pulse frequency in autogenous TIG welding process of lean duplex stainless steel. In this sense, plates of UNS S32304 and UNS S32101 lean duplex were welded without filler metal and using argon as shielding gas. The welds were made using the GTAW process, keeping the heat input constant at 340 J/mm and varying the pulse frequency between 1,5,10 and 20 Hz. The results showed that, independent of pulse frequency, grain growth in the fusion zone took place since this duplex stainless steel type has a ferritic solidification mode. Comparing the grain size and ferrite volumetric fraction in the weld bead, an increase in the mean value of grain size in the central region and unmixed region of weld beads was related to an increase of pulse frequency.

Este trabalho inova a aplicação de revestimentos duros usando o processo de soldagem SATG (Soldagem ao Arco Tungstênio com Atmosfera Gasosa) utilizando ligas, em forma de pó, incorporadas diretamente à poça de solda. Devido à boa resistência ao desgaste, utilizou-se a liga Stellite 6, no substrato SAE 1020. Dados de microdureza Vickers, taxa de deposição, diluição, análise micrográfica e desgaste foram comparados com resultados do PAT-P (Plasma por Arco Transferido-Pó) e permitiram avaliar a técnica proposta. Os resultados mostraram um revestimento pelo processo SATG-pó livre de poros, sem oxidação na superfície e diluição superior, ao processo PAT-P. Porém, o consumo de gás foi menor, devido à redução da vazão do gás de arraste e da não utilização de gás plasma. A análise microestrutural evidenciou uma microestrutura similar, para ambos os processos, mas o processo PAT-P apresentou uma microestrutura mais refinada. Obteve-se, pelo processo SATG-pó semi-automático, microdurezas entre 400 e 500 HV e uma taxa de diluição de 5%, próximas aos valores do processo PAT-P. Quanto ao desgaste, observaram-se valores também bem próximos para os três processos. / This work innovates the application of hardfacing by using the welding process GTAW (Gas Tungsten Arc Welding) using alloys in the powder form and directly embedded in the weld pool. Due to the good wear resistance it was used Stellite 6 alloy for hardfacing the substrate SAE 1020. Vickers hardness data, deposition rate, dilution, micrographic analysis and wear results were compared with the PTA-P (Plasma Transferred Arc-Powder) in order to evaluate the proposed technique. The results showed a coating produced by the process GTAW-powder free of pores, without surface oxidation and higher dilution in comparison with the PTA-P process. However, gas consumption was lower due to reduced flow of the carrier gas and as it was not used as plasma gas. Microstructural analysis showed a similar microstructure for both processes, but the PTA-P process presented a more refined microstructure. It was obtained, by the semi-automatic GTAW-powder process, micro hardness between 400 and 500HV and rate dilution of 5%, values close to the PTA-P process. As for the wear it was observed values very close too, for the three process.

Weld joint penetration determination is the key factor in welding process control area. Not only has it directly affected the weld joint mechanical properties, like fatigue for example. It also requires much of human intelligence, which either complex modeling or rich of welding experience. Therefore, weld penetration status identification has become the obstacle for intelligent welding system. In this dissertation, an innovative method has been proposed to detect the weld joint penetration status using machine-learning algorithms. A GTAW welding system is firstly built. Project a dot-structured laser pattern onto the weld pool surface during welding process, the reflected laser pattern is captured which contains all the information about the penetration status. An experienced welder is able to determine weld penetration status just based on the reflected laser pattern. However, it is difficult to characterize the images to extract key information that used to determine penetration status. To overcome the challenges in finding right features and accurately processing images to extract key features using conventional machine vision algorithms, we propose using convolutional neural network (CNN) to automatically extract key features and determine penetration status. Data-label pairs are needed to train a CNN. Therefore, an image acquiring system is designed to collect reflected laser pattern and the image of work-piece backside. Data augmentation is performed to enlarge the training data size, which resulting in 270,000 training data, 45,000 validation data and 45,000 test data. A six-layer convolutional neural network (CNN) has been designed and trained using a revised mini-batch gradient descent optimizer. Final test accuracy is 90.7% and using a voting mechanism based on three consequent images further improve the prediction accuracy.

An innovative auxiliary control system is developed to cooperate with an unskilled welder in a manual GTAW in order to obtain a consistent welding performance. In the proposed system, a novel mobile sensing system is developed to non-intrusively monitor a manual GTAW by measuring three-dimensional (3D) weld pool surface. Specifically, a miniature structured-light laser amounted on torch projects a dot matrix pattern on weld pool surface during the process; Reflected by the weld pool surface, the laser pattern is intercepted by and imaged on the helmet glass, and recorded by a compact camera on it. Deformed reflection pattern contains the geometry information of weld pool, thus is utilized to reconstruct its $3$D surface. An innovative image processing algorithm and a reconstruction scheme have been developed for (3D) reconstruction. The real-time spatial relations of the torch and the helmet is formulated during welding. Two miniature wireless inertial measurement units (WIMU) are mounted on the torch and the helmet, respectively, to detect their rotation rates and accelerations. A quaternion based unscented Kalman filter (UKF) has been designed to estimate the helmet/torch orientations based on the data from the WIMUs. The distance between the torch and the helmet is measured using an extra structure-light low power laser pattern. Furthermore, human welder's behavior in welding performance has been studied, e.g., a welder`s adjustments on welding current were modeled as response to characteristic parameters of the three-dimensional weld pool surface. This response model as a controller is implemented both automatic and manual gas tungsten arc welding process to maintain a consistent full penetration.

Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared to the novice welder. Automated welding experiments confirm the effectiveness of the proposed human response model. A virtualized welding system is then developed that enables transferring the human knowledge into a welding robot. The learning of human welder movement (i.e., welding speed) is first realized with Virtual Reality (VR) enhancement using iterative K-means based local ANFIS modeling. As a separate effort, the learning is performed without VR enhancement utilizing a fuzzy classifier to rank the data and only preserve the high ranking “correct” response. The trained supervised ANFIS model is transferred to the welding robot and the performance of the controller is examined. A fuzzy weighting based data fusion approach to combine multiple machine and human intelligent models is proposed. The data fusion model can outperform individual machine-based control algorithm and welder intelligence-based models (with and without VR enhancement). Finally a data-driven approach is proposed to model human welder adjustments in 3D (including welding speed, arc length, and torch orientations). Teleoperated training experiments are conducted in which a human welder tries to adjust the torch movements in 3D based on his observation on the real-time weld pool image feedback. The data is off-line rated by the welder and a welder rating system is synthesized. ANFIS model is then proposed to correlate the 3D weld pool characteristic parameters and welder’s torch movements. A foundation is thus established to rapidly extract human intelligence and transfer such intelligence into welding robots.