A SELF-ORGANIZING FUZZY CONTROL APPROACH TO ARC SENSOR FOR WELD JOINT TRACKING IN GAS METAL ARC-WELDING OF BUTT JOINTS

Abstract

For the artificial intelligence (Al) approach to automatic control, the fuzzy rule-based control schemes have been successfully applied to the control of complex processes. The arc welding process is one of the processes due to the fact that it possesses complex and nonlinear characteristics such as a moving distributed heat source, a current path and metal transfer. One possible solution to the design of an effective controller suitable for such a process is to use the fuzzy control scheme. The fuzzy rule-based control can easily realize the heuristic rules obtained from human experiences that cannot be expressed in mathematical form. In this study, an arc sensor, which utilizes the electrical signal obtained from the welding arc itself, was developed for CO2 gas metal arc welding of butt joints using the fuzzy set theory. A simple fuzzy controller without any adaptation was implemented for the weld joint tracking. A set of fixed rules, which was designed based upon the experiments, and a self-organizing fuzzy controller, which could improve the control rules automatically, were examined. Through a series of experiments, the performance and learning action of the proposed self-organizing fuzzy controller were assessed.