Prediction of mechanical properties for 2219 aluminum alloy friction stir weld joints based on force signals

Friction stir welding (FSW) is an advanced solid-state welding technique for joining aluminum alloys. The complicated thermomechanical process during the welding process determines the final performance of weld joints. This study focuses on the relationship between force signals and the mechanical properties of weld joints. The characteristics and variations of force signals (traverse force Fx\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_x}$$\end{document}, lateral force Fy\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_y}$$\end{document} and plunge force Fz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_z}$$\end{document}) obtained under extensive welding parameters were analyzed. The mean values of Fx\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_x}$$\end{document}, Fy\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_y}$$\end{document}, and Fz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{F_z}$$\end{document} are positively correlated with the ultimate tensile strength (UTS) of weld joints. Gauss process regression (GPR) models for predicting the UTS of joints were constructed with force features as input, and the correlation coefficients between the predicted and measured UTS were 0.98 and 0.90 for the training and testing sets, respectively. Meanwhile, the coupling relationship among welding thermal cycle, weld temperature in different zones, and welding force, as well as their influences on material flow and precipitate evolution, was analyzed to elucidate the response mechanism of welding force to weld formation. The insights gained from this research provide a theoretical basis for developing a real-time evaluation method for monitoring weld joint quality in future industrial applications.