Construction of Welding Quality Intelligent Judgment System
Jinjin Guo, Yang Liu, Gang Wu
- Year
- 2019
- Citations
- 5
Abstract
In order to improve the welding quality of the robot, control the welding precision and parameter optimization in the welding operation, establish a welding quality intelligent judgment system based on the fuzzy neural network control technology, realize the continuous optimization of the welding quality database, and improve the welding defect identification efficiency. This paper outlines the technical method of constructing intelligent judgment system, using fuzzy control theory combined with BP neural network to identify welding defects and optimize welding process parameters. By inputting various features into the fuzzy neural network, the accuracy of seam classification can reach 90%, and the experimental results show that the proposed method of optimizing welding parameters and improving welding performance is effective and feasible. The intelligent control theory represented by expert system, fuzzy control and neural network and its application status in welding process control are introduced. The development trend of intelligent control technology in the welding process is discussed.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002