关键词: 灰色模型, 神经网络, 板料成形缺陷, 预测

Abstract:

In order to predict accurately and reduce the possible defects in the sheet metal forming process, an improved gray neural network prediction model was proposed. In this model, BP neural network model was used to assist the grey prediction model, that is: the grey model made a coarse firstly,and the errors were corrected by the neural network, after that a new gray neural network model with higher accuracy was obtained through finding the best weight values to optimize the background value corresponding to the differential in the grey model. Taking the drawing of square boxes as an example, which is from the internationally famous sheet metal forming numerical simulation conference NUMISHEET'93, the crack and wrinkle is predicted by applying the improved gray neural network model. Compared with the gray neural network model which is not improved, the results show that the improved gray neural network model has higher prediction accuracy, and the prediction results are more stable.

Key words: gray model, neural network, sheet metal forming defect, prediction