scholarly journals Effects of Filler Wire Intervention on Gas Tungsten Arc: Part II - Dynamic Behaviors of Liquid Droplets

2020 ◽  
Vol 99 (10) ◽  
pp. 271s-279s
Author(s):  
SHUANGYANG ZOU ◽  
◽  
ZHIJIANG WANG ◽  
SHENG-SUN HU ◽  
GUANCHENG ZHAO ◽  
...  
Keyword(s):  
Liquid Droplet ◽  
Welding Process ◽  
Filler Wire ◽  
Weld Quality ◽  
Tungsten Electrode ◽  
Dynamic Behaviors ◽  
Time Frequency ◽  
Gas Tungsten Arc ◽  
Probe Voltage ◽  
Gas Tungsten

In gas tungsten arc welding (GTAW), the filler wire in-creases the deposition efficiency and influences the welding stability. Its interactions with the gas tungsten arc (GTA) are significant to better understand the welding process and to monitor and control weld quality. In view of this, the first part of the work, Effects of Filler Wire Intervention on Gas Tungsten Arc: Part I — Mechanism, explained the inter-action mechanisms between the filler wire and the gas tungsten arc based on the proposed arc-sensing method of detecting probe voltage (i.e., the voltage signal between the filler wire and the tungsten electrode/workpiece). In this second part of the work, experiments were designed to make the filler wire melt in different areas of the arc to study the dynamic behaviors of the droplet and its effect on the arc. Typical metal transfer modes are discussed, and droplet oscillation is geometrically characterized through image processing and then analyzed in the time domain and time-frequency domain. The results show that the liquid droplet affects the arc through its transfer to the weld pool, its oscillation, and occupying the arc space. Information about these dynamic behaviors can be easily reflected in the probe voltage, which would be a valuable signal to monitor the process stability in GTAW with filler wire. This work shows the potential of the proposed sensing method for monitoring and controlling weld quality in all welding positions, GTA-based additive manufacturing, etc.

scholarly journals Effects of Filler Wire Intervention on Gas Tungsten Arc: Part I - Mechanism

2020 ◽  
Vol 99 (9) ◽  
pp. 246s-254s
Author(s):  
SHUANGYANG ZOU ◽  
◽  
ZHIJIANG WANG ◽  
SHENG-SUN HU ◽  
GUANCHENG ZHAO ◽  
...  
Keyword(s):  
Thermal Inertia ◽  
Filler Wire ◽  
Tungsten Electrode ◽  
Arc Voltage ◽  
Gas Tungsten Arc ◽  
Probe Voltage ◽  
Gtaw Process ◽  
New Ideas ◽  
Gas Tungsten ◽  
The Stability

For gas tungsten arc welding (GTAW), the effects of filler wire on the GTA are worth being clarified, which will help deepen the understanding of arc characteristics and in-spire new ideas for the real-time monitoring of weld quality. To this end, this work proposed a novel sensing method of detecting probe voltages (i.e., the voltage signals between a filler wire and tungsten electrode/workpiece). Based on this method, in this first part of the work, a tungsten probe was used to replace the filler wire and to interact with the arc in the specific experiments to elucidate the static and dynamic interaction mechanisms between the GTA and filler wire. The results showed that the filler wire intervention deflects the arc to various degrees and will change the volt-age signals. As a metal conductor, the filler wire will in-crease the arc voltage by increasing the average electric field strength. However, its effects on the different areas of the arc are not always consistent, which makes the change trend of the probe voltages not always the same. Moreover, due to thermal inertia, the probe voltage does not strictly change synchronously with the arc voltage under the dynamic disturbance. This work lays a theoretical foundation for monitoring the stability of the GTAW process.

A Neural Network Model for Predicting Two Observable Parameters of the Welded Cross Section in Case of Robotic Gas Tungsten Arc Welding Process

2012 ◽  
Vol 162 ◽  
pp. 531-536
Author(s):  
Gabriel Gorghiu ◽  
Paul Ciprian Patic ◽  
Dorin Cârstoiu
Keyword(s):  
Neural Network ◽  
Arc Welding ◽  
Welding Process ◽  
Gas Tungsten Arc Welding ◽  
Gas Tungsten Arc ◽  
Proposed Model ◽  
Input Layer ◽  
Gas Tungsten ◽  
Arc Welding Process ◽  
Observable Parameter

The paper presents a model of using the artificial neural networks when determining the relations of dependency between the observable parameters and the controllable ones in the case of RoboticGas Tungsten Arc Welding. The proposed model is based on the direct observation of welded joints, emphasizing on the process variables which have been arranged in the nodes of a neural network. The design of the network intended to achieve an architecture that contains four nodes in the input layer (all of them being controllable parameters) and two nodes in the output layer (one for each observable parameter).

Influence of filler wire addition on weld pool oscillation during gas tungsten arc welding

2004 ◽  
Vol 9 (2) ◽  
pp. 163-168 ◽  
Author(s):  
B. Y. B. Yudodibroto ◽  
M. J. M. Hermans ◽  
Y. Hirata ◽  
G. den Ouden
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Gas Tungsten Arc Welding ◽  
Filler Wire ◽  
Gas Tungsten Arc ◽  
Gas Tungsten

Coupled Field Analysis of a Gas Tungsten Arc Welded Butt Joint—Part I: Improved Modeling

2013 ◽  
Vol 5 (1) ◽  
Author(s):  
D. Sen ◽  
M. A. Pierson ◽  
K. S. Ball
Keyword(s):  
Weld Pool ◽  
Welding Process ◽  
Butt Joint ◽  
Accurate Estimation ◽  
Mathematical Framework ◽  
Welded Structures ◽  
Thermally Induced ◽  
Gas Tungsten Arc ◽  
Welded Structure ◽  
Gas Tungsten

Thermally induced residual stresses due to welding can significantly impair the performance and reliability of welded structures. From a structural integrity perspective of welded structures, it is necessary to have an accurate spatial and temporal thermal distribution in the welded structure before stress analysis is performed. Existing research has ignored the effect of fluid flow in the weld pool on the temperature field of the welded joint. Previous research has established that the weld pool depth/width (D/W) ratio and heat affected zone (HAZ) are significantly altered by the weld pool dynamics. Hence, for a more accurate estimation of the thermally induced stresses it is desired to incorporate the weld pool dynamics into the analysis. Moreover, the effects of microstructure evolution in the HAZ on the mechanical behavior of the structure need to be included in the analysis for better mechanical response prediction. In this study, a three-dimensional numerical model for the thermomechanical analysis of gas tungsten arc (GTA) welding of thin stainless steel butt-joint plates has been developed. The model incorporates the effects of thermal energy redistribution through weld pool dynamics into the structural behavior calculations. Through material modeling the effects of microstructure change/phase transformation are indirectly included in the model. The developed weld pool dynamics model includes the effects of current, arc length, and electrode angle on the heat flux and current density distributions. All the major weld pool driving forces are included, namely surface tension gradient induced convection, plasma induced drag force, electromagnetic force, and buoyancy. The weld D/W predictions are validated with experimental results. They agree well. The workpiece deformation and stress distributions are also highlighted. The mathematical framework developed here serves as a robust tool for better quantification of thermally induced stress evolution and distribution in a welded structure by coupling the different fields in a welding process.

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