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Estimation of Weld Bead Shape and the Compensation of Welding Parameters using a hybrid intelligent System  

Kim Gwan-Hyung (동명정보대학교 컴퓨터공학과)
Kang Sung-In (동명정보대학교 컴퓨터공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.9, no.6, 2005 , pp. 1379-1386 More about this Journal
Abstract
For efficient welding it is necessary to maintain stability of the welding process and control the shape of the welding bead. The welding quality can be controlled by monitoring important parameters, such as, the Arc Voltage, Welding Current and Welding Speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using fuzzy logic and neural networks for improving welding qualify and maintaining the desired weld bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and remove the welding detects.
Keywords
Fuzzy control; Neural network; Weld bead shape; Hybrid intelligent system;
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