한국공작기계학회:학술대회논문집 (Proceedings of the Korean Society of Machine Tool Engineers Conference)
- 한국공작기계학회 2005년도 춘계학술대회 논문집
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- Pages.66-70
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- 2005
표면 비드높이 예측을 위한 최적의 신경회로망 선정에 관한 연구
A Study on the Selection of Optimal Neural Network for the Prediction of Top Bead Height
초록
The full automation of welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an neural network model to predict the weld top-bead height as a function of key process parameters in the welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to select an optimal neural network model.
키워드