Self-Learning Fuzzy Neural Networks and Computer Vision for Control of Pulsed GTAW Neural network modeling and computer vision techniques are used to control the dynamics of the pulsed gas tungsten arc welding process

Abstract

The objective of this research is to apply intelligent control methodology to improve weld quality. Based on fuzzy logic and artificial neural network theory, a self-learning fuzzy and neural network control scheme has been developed for real-time control of pulsed gas tungsten arc welding (GTAW). Using an industrial TV camera as the sensor, the weld face… (More)

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