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A smart system to determine and control for the process parameters in pipeline welding

Jeong, Y-J. and Kim, H-H. and Chand, Reenal R. and Na, H-H. and Lee, J-H. and Kim, I-S. (2014) A smart system to determine and control for the process parameters in pipeline welding. Materials Science Forum, 773-77 . pp. 758-766. ISSN 1662-9752

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Determination of the optimal welding parameters to achieve specific weldments on a new material is usually an expensive and time consuming. To determine the welding parameters using Artificial Intelligence (AI) technologies, one must consider many factors including productivity, thermal input, defect formation, and process robustness. Determination of the welding parameters for pipeline welding is based on a skilled welder’s long-term experience rather than on a theoretical and analytical technique. In this paper, a smart system develops which determines welding parameters and position for each weld pass in pipeline welding based on one database and FEM model, two BP neural network models and a C-NN model. The preliminary test of the system has indicated that the system could determine the welding parameters for pipeline welding quickly, from which good weldments can be produced without experienced welding personnel. Experiments using the predicted welding parameters from the developed system proved the feasibility of interface standards and intelligent control technology to increase productivity, improve quality, and reduce the cost of system integration.

Item Type: Journal Article
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Ronal Chand
Date Deposited: 24 Feb 2014 23:49
Last Modified: 12 Sep 2016 02:30

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