QUT ePrints

Prediction of welding parameters for pipeline welding using an intelligent system

Kim, Ill-Soo, Jeong, Y. J., Yarlagadda, Prasad K., & Lee, C.W (2003) Prediction of welding parameters for pipeline welding using an intelligent system. The International Journal of Advanced Manufacturing Technology, 22(9-10), pp. 713-719.

View at publisher

Abstract

The determination of the welding parameters for pipeline welding is based on a skilled welder’s know-how and long-term experiences rather than on theoretical and analytical techniques. In this paper, an intelligent system for the determination of welding parameters for each pass and welding position, for pipeline welding based on one database and a finite element method (FEM) model, and on two back-propagation (BP) neural network models and a corrective neural network (CNN) model was developed and validated. 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.

Impact and interest:

38 citations in Scopus
Search Google Scholar™
28 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 6381
Item Type: Journal Article
Additional Information: For more information please refer to the publisher's website (link above) or contact the author: y.prasad@qut.edu.au
DOI: 10.1007/s00170-003-1589-y
ISSN: 1433-3015
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MANUFACTURING ENGINEERING (091000) > Manufacturing Processes and Technologies (excl. Textiles) (091006)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2003 Springer
Copyright Statement: The original publication is available at SpringerLink http://www.springerlink.com
Deposited On: 07 Mar 2007
Last Modified: 29 Feb 2012 23:00

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page