신경회로망을 이용한 실시간 용접비드 자동제어에 관한 연구

A Study on the Real-Time Automatic Control of the Welding Bead using Neural Network

Recently, several models to control weld quality, productivity, microstructure and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead geometry as well as apply for the on-line quality automatic control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, The system will extend to other welding process and rule-based expert system which can be incorporated with to integrate an optimized system for the robotic welding system.