Dynamic modeling of the gas metal arc welding process

This research develops a dynamic GMAW process model which can be used in high-level nonlinear control methods, such as adaptive control and multivariable control. The model provides a more fundamental understanding of the coupling between mass flow and heat transfer (energy) and the melting process in the electrode extension.; Components of the model are identified as the electrode melting rate, temperature-dependent resistivity of the electrode, and arc voltage. The differential equations describing the dynamic behavior of the electrode extension were derived from the mass continuity and energy relations. The temperature of the electrode extension is shown to be primarily dependent on conductive heat transfer and joule heating. One-dimensional solutions of temperature and heat content were used to obtain the dynamic melting rate equation.; Quantitative analyses, concentrating on the thermal behavior and the electrical characteristics of the arc were performed. The analysis quantifies the complex interrelation among welding parameters that are impossible to measure directly. Melting experiments were structured to explain the relationship between temperature, heat content and resistivity along the electrode extension from electrical signal measurements. Temperature distribution and heat content along the electrode extension were found by combining the resistivity model and the energy balance model.; Several aspects of the dynamic relationships, characteristic of the process, were investigated by using the model developed in this study. Furthermore, a comparison of constant current GMAW and P-GMAW processes was made using the resistivity model. Their temperature-dependent electrical parameters (action and resistivity) were used to compute the electrode voltage drop. The relationship between arc current and droplet frequency was also studied by using a high-speed video camera system. Experiments providing information related to direct measurement of the electrode extension and its dynamic variations were conducted to validate the dynamic model. A comparison of simulation and experimental results shows very good agreement between the model and the real process. The model is applicable to both constant potential and constant current modes (including pulsed current) of the GMAW process.