The geometry of the weld pool contains accurate, instantaneous information about welding quality. Thus, weld pool sensing and control plays a significant role in automated arc welding. Previous studies have focused on inferring penetration through models and controlling penetration by various methods, such as adaptive control, model based fuzzy logic, etc. In the present work, a weld pool imaging system employing a LaserStrobe (tradename) high shutter speed camera is used to obtain contrasting images and eliminate arcing interference. Two image processing tools based on edge detection and connectivity analysis extract online information about the weld pool length and width. A neurofuzzy control system elicited from both human experience and experimental results has been developed to control the welding current and welding speed in real time based on changes in weld pool dimensions. Closed loop control of welding speed is used to achieve desirable weld pool geometry.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.