ISSN:
1662-9752
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
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 clusteringalgorithm 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
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/02/11/transtech_doi~10.4028%252Fwww.scientific.net%252FMSF.505-507.541.pdf
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