In this paper, we propose an aging state monitoring system for robotic welding gun using ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters and inspection equipment data. In this method, the inspection equipment data used for diagnosis of robotic welding gun via ART2 NN modules. The Graphical User Interface (GUI) program by Lab VIEW designed for convenient operation of the monitoring system. We also carried out the computer simulation to confirm the suitability of the proposed monitoring system.
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