Study of different machine learning methods in welded seam width prediction
Year: 2015
Journal of Information and Computing Science, Vol. 10 (2015), Iss. 2 : pp. 154–160
Abstract
As an important new laser processing technique, the high-power disk laser welding has been increasingly widely used in the manufacturing area. Aiming at the strong coupling multi-variable and real- time feedback requirements of the welding process, a new method using support vector machine is proposed to predict the width of the molten pools. The performance of this model is validated by the test data. Meanwhile, analysis and comparison between the support vector machines and the BP neural network are conducted. Experiment results show that the support vector machine and the BP neural network both have a good predictive ability. However, in comparison with the BP neural network, the support vector machine is more suitable for high-power disk laser welding process.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22558
Journal of Information and Computing Science, Vol. 10 (2015), Iss. 2 : pp. 154–160
Published online: 2015-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 7