Novel approach to improving additive manufacturing precision via bivariate molten pool dimension regulation

Directed energy deposition arc welding (DED-arc) encounters challenges such as low forming precision and compromised process stability during the deposition process owing to its intricate molten pool dynamics. The measurement and control of the molten-pool size are essential to addressing these problems. However, most contemporary research focuses on controlling a single variable (e.g., molten-pool width or height) in either open- or closed-loop configurations. This approach is inherently limited in addressing the dynamic nonlinear characteristics and high-precision requirements of the DED-arc process. To address this challenge, we designed a binocular passive vision sensing system that utilizes an image processing algorithm to facilitate the real-time measurement and size extraction of the molten-pool width and height. A dual fuzzy proportional–integral–derivative controller was also developed to control the width and height of the molten pool by adjusting the arc current and voltage separately. This controller was then compared with open-loop control experiments under constant parameters. The results demonstrate that the proposed bivariate control method can effectively regulate the error range of the actual and detected values of the molten-pool width and height within 0.5 and 0.3 mm, respectively, thereby significantly enhancing the control accuracy and optimizing the forming appearance of thin-walled metal parts.