Collaborative Simulation of Nugget Growth and Process Signals for Resistance Spot Welding

• Published in: Welding in the world Vol. 67; no. 6; pp. 1377 - 1392
• Main Authors: Xia, Yu-Jun, Lv, Tian-Le, Ghassemi-Armaki, Hassan, Li, Yong-Bing, Carlson, Blair E.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023; Springer Nature B.V
• Subjects: Chemistry and Materials Science; Electric contacts; Finite element method; Liquid metals; Materials Science; Mathematical models; Metal sheets; Metallic Materials; Multiple objective analysis; Optimization; Process parameters; Research Paper; Resistance spot welding; Signal processing; Signal quality; Simulation; Solid Mechanics; Theoretical and Applied Mechanics; Thermal conductivity; Welding parameters; Numerical simulation; Process signal; Weld geometry; Labeled data generation; Resistance spot welding
• ISSN: 0043-2288; 1878-6669
• DOI: 10.1007/s40194-023-01489-4

In this work, an electrical–thermal–mechanical coupled finite element (FE) model for resistance spot welding (RSW) process is developed to achieve a simultaneous simulation of not only nugget growth but also process signals including dynamic resistance and electrode displacement. The model entails a multi-objective optimization problem of hard-to-measure physical quantities. During the optimization process, the limitation of adjusting only the interface contact parameters is found and corrected by introducing an enhanced thermal conductivity due to molten metal flow. Experimental validation confirmed simulation accuracy and adaptability to sheet metal thickness and welding process parameter variation. The model can directly generate process signal data with accurate quality indexes, which supports solving the problem of insufficient labeled data in model training for RSW quality prediction.