Author : Pawan Kumar Singh Nain 1
Date of Publication :23rd February 2018
Abstract: To improve the welding quality of the robot, monitor the welding accuracy and optimization of the parameters in the welding process, create an intelligent welding quality judgment system based on the Fuzzy Neural Network Control Technology, perform continuous optimization of the welding quality database and improve the efficiency of welding defect detection. This paper explains the technical approach of developing smart judgment framework, employing fuzzy control theory combined with BP neural network to recognize welding defects and optimize process parameters for welding operation. Through integrating different features into the fuzzy neural network, seam classification accuracy will exceed 90%, and the experimental results indicate that the proposed method of optimizing welding parameters and enhancing welding efficiency is successful and feasible. Introduction of the intelligent control theory described by expert method and fuzzy control as well as neural network and its implementation status in the management of welding processes. It addresses the creation trend of smart control technology in the welding process.
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