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Effect of shielding gas flow on welding process of laser-arc hybrid welding and MIG welding
摘要： The influence of shielding gas on welding process of laser-arc hybrid welding (LAHW) and metal inert-gas welding (MIG) was investigated by the computational fluid dynamics analysis (CFD) and high-speed photography. The results show that the process stability of MIG under high gas flow rate is poorer than that of LAHW. And the force of gas flow Fg can hinder the droplet transfer, whether MIG or LAHW. But the vaporization-induced recoil force Fv in LAHW helps to reduce this kind of hindrance and keep the process stability. Next, it can be found that the shielded gas flow mode in the main welding area cannot be changed significantly by increasing the shielding gas flow rate, while high gas flow rate can increase the area of high argon concentration and benefit the spread of molten metal.
关键词： Welding process,Computational fluid dynamics analysis,Laser-arc hybrid welding,MIG welding
更新于2025-11-28 14:24:20
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Neural networks based prediction modelling of hybrid laser beam welding process parameters with sensitivity analysis
摘要： Present paper attempted to model complex relationship between CO2 laser–MIG hybrid welding parameters and it has been completed using different algorithms of artificial neural networks (ANN). Input parameters for the study include laser power, welding speeds and wires feed rate and tensile strength of the joint is considered as output. A full factorial experimental dataset is used for the purpose. Variants of back propagation neural networks (BPNN) and Radial Basis Function Networks have been used as training algorithm. Altogether 65 different ANN architecture have been trained and tested using 6 different training algorithms to find out ANN with best prediction capability. 3-11-1 ANN architecture trained using BPNN with Bayesian regularization shows best prediction capability (mean square error 3.24E ? 04) and considered as Best ANN. That ANN will be useful for determining required value of welding process parameters to yield a specific welding strength and suitable for online process monitoring and control. Finally, a sensitivity analysis has been conducted and it is found that, maximum welding strength can be obtained with low wire feed rate (4 m/min), low welding speed (2 m/min) and high laser power (3 kW).
关键词： Sensitivity analysis,Hybrid CO2 laser-MIG welding,Artificial neural networks
更新于2025-09-16 10:30:52