학술논문

Artificial neural network prediction of weld distortion rectification using a travelling induction coil.
Document Type
Article
Source
International Journal of Advanced Manufacturing Technology. Sep2013, Vol. 68 Issue 1-4, p127-140. 14p. 3 Color Photographs, 1 Diagram, 2 Charts, 21 Graphs.
Subject
*ARTIFICIAL neural networks
*LOGICAL prediction
*INDUCTION heating
*WELDING
*INDUCTION coils
*MATHEMATICAL models
*EXISTENCE theorems
Language
ISSN
0268-3768
Abstract
An experimental investigation has been carried out to determine the applicability of an induction heating process with a travelling induction coil for the rectification of angular welding distortion. The results obtained from experimentation have been used to create artificial neural network (ANN) models with the ability to predict the weld-induced distortion and the distortion rectification achieved using a travelling induction coil. The experimental results have shown the ability to reduce the angular distortion for 8- and 10-mm thick DH36 steel plates and effectively eliminate the distortion on 6-mm thick plates. Results for 6-mm plates also show the existence of a critical induction coil travel speed, at which maximum corrective bending occurs. ANNs have demonstrated the ability to predict the final distortion of the plate both after welding and induction heating. The models have also been used as a tool to determine the optimum speed to minimise the resulting distortion of a steel plate after being subjected to both welding and induction heating processes. [ABSTRACT FROM AUTHOR]