Multi-information Fusion and Identification System for Laser Welding

Authors:
Ming Zhou;Wenzhong Liu;Lei Wan
Affiliations:
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China 430074
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

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Abstract

In this paper, we proposed a laser welding quality monitoring system based on vector machine, which uses the light and sound sensors access to the various signals of the welding and Gabor transform features to extract the vector. The basic features of Laser welding is the formation of small holes, pool and photo-induced plasma, and the result is quality of the welding of light, sound and the potential of poor signal. On this basis, making use of the advantage and objectivity of machine leaning, SVM classification and more comprehensive information to determine the parameters of laser welding quality of the welding seam.