Numerical Simulation and Industrial Application of High Speed Tandem TIG Welding

Self-developed high speed tandem TIG welding equipment were adopted to manufacture titanium welded tubes with high efficiency and high quality. The joint made by this high efficient welding process met Chinese standard requirements. A coupled electrode, arc and weld pool numerical model was also developed to investigate temperature and velocity distributions, and energy propagation of this welding process. The numerical results showed that the Marangoni stress was much higher than the arc shear stress, and was mainly positive after leading and trailing arcs in the x and y directions, so the molten metal flowed backward on the top weld pool surface. Previous studies proposed that a “pull-push” flow pattern defined as a backward molten metal flow after the leading arc and a forward molten metal flow before the trailing arc existed on the top weld pool surface in tandem arc welding processes, while it was not observed in this case. The calculated arc efficiency of the high speed tandem TIG welding was about 79.8%.

Automated Recognition of Weld Pool Characteristics from Active Vision Sensing

While penetration occurs underneath the workpiece, the raw information used to detect it during welding must be measurable to a sensor attached to the torch. Challenges are apparent because it is difficult to find such measurable raw information that fundamentally correlates with the phenomena occurring underneath. Additional challenges arise because the welding process is extremely complex such that analytically correlating any raw information to the underneath phenomena is practically impossible; therefore, handcrafted methods to propose features from raw information are human dependent and labor extensive. In this paper, the profile of the weld pool surface was proposed as the raw information. An innovative method was proposed to acquire it by projecting a single laser stripe on the weld pool surface transversely and intercepting its reflection from the mirror-like weld pool surface. To minimize human intervention, which can affect success, a deep-learning-based method was proposed to automatically recognize features from the single-stripe active vision images by fitting a convolutional neural network (CNN). To train the CNN, spot gas tungsten arc welding experiments were designed and conducted to collect the active vision images in pairs with their actual penetration states measured by a camera that views the backside surface of the workpiece. The CNN architecture was optimized by trying different hyperparameters, including kernel number, kernel size, and node number. The accuracy of the optimized model is about 98% and the cycle time in the personal computer is ~ 0.1 s, which fully meets the required engineering application.

Simplified surface heat source distribution for GMAW process simulation based on the EDACC principle

A simplified surface heat source for gas metal arc welding (GMAW) process simulation based on the principle of evaporation determined arc cathode coupling (EDACC) is presented. It allows for a simple implementation in any GMAW weld pool simulation and is dependent on the width of the arc, as well as the weld pool surface temperature, but it can also be applied with the temperature and iron vapor density of the plasma instead of the width of the arc, if available. While it is considered separately from the droplets, it gives the heat flux as well as the current density distribution onto the weld pool surface, which are in general not axis-symmetric. The heat source distribution is normalized and multiplied to the value of any total heat and total current and it allows to calibrate for the maximum weld pool surface temperature. For the ionization and evaporation, only iron atoms are considered, and the shielding gas is assumed as argon. The result is given in graphical form as well as in the form of easy to implement functions for a reasonable range.

The Reconsitution of the Weld Pool Surface in Stationary TIG Welding Process With Filler Wire

In order to study the dynamic characteristics of the weld pool surface during the TIG welding process of the filler wire, an observation test platform for the study of the three-dimensional surface behavior evolution of the TIG weld pool based on the grid structure laser was used to observe the weld pool surface and obtain the reflection grid laser image. The three-dimensional surface evolution of the fixed-point TIG welding pool is accurately restored by the three-dimensional recovery algorithm of the weld pool surface, so as to obtain the three-dimensional surface morphology of the weld pool. The difference between the obtained weld pool height and the experimental results is very small, and the results are basically the same.

Material Flow Behavior on Weld Pool Surface in Plasma Arc Welding Process Considering Dominant Driving Forces

In this study, the effect of oxygen in the shielding gas on the material flow behavior of the weld pool surface was discussed to clarify the dominant driving weld pool force in keyhole plasma arc welding (KPAW). To address this issue, the convection flow on the top surface of weld pool was observed using a high-speed video camera. The temperature distribution on the surface along keyhole wall was measured using the two-color pyrometry method to confirm the Marangoni force activity on the weld pool. The results show that the inclination angle of the keyhole wall (keyhole shape) increased especially near the top surface due to the decrease in the surface tension of weld pool through surface oxidation when a shielding gas of Ar + 0.5% O2 was used. Due to the change in the keyhole shape, the upward and backward shear force compositions created a large inclination angle at the top surface of the keyhole. From the temperature measurement results, the Marangoni force was found to alter the direction when 0.5% O2 was mixed with the shielding gas. The shear force was found to be the strongest force among the four driving forces. The buoyant force and Lorentz force were very weak. The Marangoni force was stronger than the Lorentz force but was weaker than shear force. The interaction of shear force and Marangoni force controlled the behavior and speed of material flow on the weld pool surface. A strong upward and backward flow was observed in the case of mixture shielding gas, whereas a weak upward flow was observed for pure Ar. The heat transportation due to the weld pool convection significantly changed when only a small amount of oxygen was admixed in the shielding gas. The results can be applied to control the penetration ratio in KPAW.

Analysis of Eddy Formation and Heat Transfer Process in Weld Pool during Plasma Keyhole Arc Welding

This investigation aims to discuss the formation process of eddies and the heat transportation in plasma keyhole arc welding. In order to clarify this issue, the measurement of the convection inside the weld pool, the convection on the weld pool surface, also the temperature distribution on the weld pool surface were carried out. The results showed that two eddies were found in the weld pool, which is controlled mainly through the shear force by the plasma flow acting on the weld pool surface. The magnitude, extent and direction of the shear force are thought to be determined primarily by the variation of keyhole profile. The relative shape and strength of each eddy is largely changed depending on the change of the keyhole profile when nozzle diameter changed. These relative strengths of each eddy are considered to decisively govern the heat transport in the weld pool coinciding with the direction of eddies. A larger eddy near the lower part of the keyhole inside the weld pool was found out in the case of 1.6 mm, meanwhile a upward larger eddy was found out near the upper part of the keyhole inside the weld pool in the case of 2.4 mm.