A Study on Fuzzy Logic Theory to Predict the Process Parameters in GMA Welding Process

Abstract

Recently, there has been a rapid development in computer technology, which has in turn led to develop the automated welding system using Artificial Intelligence (AI). However, the automated welding system has not been achieved duo to difficulties of the control and sensor technologies. In this paper, the classification of the optimized bead geometry such as bead width, height, penetration and bead area in the Gas Metal Arc (GMA) welding with fuzzy logic is presented. The Fuzzy C-Means (FCM) algorithm, which is best known an unsupervised fuzzy clustering algorithm is employed here to analysis the specimen of the bead geometry. Then the quality of the GMA welding can be classified by this fuzzy clustering technique, and the optimal bead geometry can also be achieved.