Dynamic simulation of short-circuiting transfer in GMAW based on the “mass-spring” model

Wang, Ying; Lu, Xin; Jing, Hongyang

doi:10.1007/s00170-016-8538-z

Cited by 9 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Short circuit and interchangeable transfer modes both show shorter, wider peaks while dropping down to a lower base current with Interchangeable transfer mode's base current value being much higher than short circuit and pulsed. This occurs due to the short circuiting of the welding electrode that occurs in both short circuit and interchangeable transfer modes [23]. In contrast, free flight transfer mode demonstrates a flatter signal with less obvious peaks while being at a significantly higher current value when compared to the other signals.…”

Section: Methodsmentioning

confidence: 99%

Classification of transfer modes in gas metal arc welding using acoustic signal analysis

Cullen

Zhao

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Gas Metal Arc Welding (GMAW) is a welding process in which an electric arc is formed between a wire electrode and a metal work piece alongside a shielding gas to protect the arc from contaminants.There are several ways in which the molten electrode droplet can be transferred to the weld pool known as metal transfer modes. Identifying the metal transfer mode automatically is essential to monitor and control the welding process, especially in automated processes employed in modern Industry 4.0 manufacturing lines. However, limited research on this topic has been found in literature. This paper explores automatic classification of metal transfer modes in GMAW based on machine learning techniques with various signals from the welding process, including acoustics, current, voltage, and gas flow rate signals. Time and frequency domain features are first extracted from these signals and are used in a support vector machine classifier to detect the metal transfer modes. A feature selection algorithm is proposed to improve the prediction rate from 80% to 99% when all the four signals are utilized. When only the non-intrusive acoustic signal is used, the prediction rates with and without the proposed feature selection algorithm are approximately 96% and 81%, respectively.The high prediction rate demonstrates the feasibility and promising accuracy of the acoustic signal based classification method for future smart welding technology with real-time adaptive feedback control of the welding process.

show abstract

Section: Methodsmentioning

confidence: 99%

Classification of transfer modes in gas metal arc welding using acoustic signal analysis

Cullen

Zhao

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…In the literature [15], during the arcing phase of shortcircuit transition, the displacement x, velocity vD, mass mD of the molten droplet, welding current I, voltage U and extended length of welding wire le mainly change according to the following formula:…”

Section: Dynamic Modelmentioning

confidence: 99%

Stability analysis of CO2 gas shielded welding short-circuit transition process based on GMAW dynamic model

Zhao

Wang

Meng

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Based on the arc phase and short-circuit phase and their relationship, the paper considers the changes of the extension length of the welding wire, the arc length, liquid bridge resistance and mass of liquid bridge, combines the improved "mass-spring" model with the loop model of welding power system, puts forward the critical judgment condition of droplet transition, and establishes a more accurate dynamic model for describing the short-circuit transition process. Through the dynamic model, the short-circuit transition frequency, welding current and voltage, contact droplet and residual droplet equivalent radius (including mean and statistical distribution) and the dynamic changes of droplet equivalent radius at different wire feeding speeds were calculated and analyzed, and compared with the experimental results, they were in good agreement. The dynamic changes of droplet displacement, velocity, welding wire extension length and liquid bridge shape are discussed. The results show that the fluctuations of droplet displacement, velocity, and extension length of welding wire is the smallest at the optimal arc point, and the smaller the radius of curvature of the initial liquid bridge is, the better the stability of short-circuit transition is.

show abstract

Effects of heat source configuration on the welding process and joint formation in ultra-high power laser-MAG hybrid welding

Song

Zhu

et al. 2022

Journal of Manufacturing Processes

View full text Add to dashboard Cite

Dynamic simulation of short-circuiting transfer in GMAW based on the “mass-spring” model

Cited by 9 publications

References 17 publications

Classification of transfer modes in gas metal arc welding using acoustic signal analysis

Classification of transfer modes in gas metal arc welding using acoustic signal analysis

Stability analysis of CO2 gas shielded welding short-circuit transition process based on GMAW dynamic model

Effects of heat source configuration on the welding process and joint formation in ultra-high power laser-MAG hybrid welding

Contact Info

Product

Resources

About