한국공작기계학회:학술대회논문집 (Proceedings of the Korean Society of Machine Tool Engineers Conference)
- 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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- Pages.208-213
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- 2001
A New Technology for Optimization of Bead Height Using ANN
- Kim, Ill-Soo (The Department of Mechanical Engineering at Mokpo National University) ;
- Son, Joon-Sik (The graduate School at Mokpo National University) ;
- Sung, Back-Sub (The Department of Mechanical Engineering at Mokpo National University) ;
- Lee, Chang-Woo (The graduate School at Mokpo National University) ;
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Cha, Yong-Hoon
(The Department of Mechanical Engineering at Chosun University)
- 발행 : 2001.04.01
초록
Objective of this paper is to develop a new approach involving the use of an Artificial Neural Network(ANN) and multiple regression methods in the prediction of process parameters on bead height for GMA welding process. Using a series of robotic are welding, multi-pass butt welds carried out in order to verify the performance of the neural network estimator and multiple regression methods. To verify the developed system, the design parameters of the neural network estimator are selected from an estimation error analysis. The experimental results show that the proposed models can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.
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