摘要
The analysis of variance(ANOVA), multiple quadratic regression and radial basis function artificial neural network(RBFANN) methods were used to study the springback and tensile strength in age forming of 2A97 aluminum alloy based on orthogonal array. The ANOVA analysis indicates that the springback reaches the minimum value when age forming is performed at 210 °C for 20 h using a single-curvature die with a radius of 400 mm, and the tensile strength reaches the maximum value when age forming is performed at 180 °C for 15 h using a single-curvature die with a radius of 1000 mm. The orders of the importance for the three factors of pre-deformation radius, aging temperature and aging time on the springback and tensile strength were determined. By analyzing the predicted results of the multiple quadratic regression and RBFANN methods, the prediction accuracy of the RBFANN model is higher than that of the regression model.
基于正交实验,运用方差分析、多元二次回归和径向人工神经网络研究2A97铝合金时效成形过程中的回弹量和抗拉强度。方差分析结果表明,在预弯半径为400 mm、时效温度为210°C时效20 h后试样具有最小的回弹量;而在预弯半径为1000 mm、时效温度为180°C下时效15 h后试样具有最大的抗拉强度。确定了预弯半径、时效温度和时效时间这3个因素对试样回弹量和抗拉强度影响大小的顺序。多元二次回归方法和径向人工神经网络的预测结果表明,径向人工神经网络模型具有更高的预测精度。
