摘要
作为一种连续局部塑性成形工艺,滚珠旋压被应用于制造高强度、高精度的纵向内筋薄壁筒形件。通过使用铝合金作为旋压材料,在实验的基础上分析了滚珠旋压过程中金属材料非稳定流动的基本原理及旋压件产生表面质量缺陷的原因。以人工神经元网络为基础,对旋压件的表面质量缺陷进行了预测。实验证明,神经元网络能够精确地诊断旋压件的表面质量缺陷。
As a successively and locally plastic deformation process, ball spinning is applied in order to manufacture high-strength and high-precision thin-walled tubular part with longitudinal inner ribs. By using aluminum alloy as spinning material, based on the experiments, not only the basic principle with respect to non-steady flow of metal material in ball spinning, but also the reasons for surface quality defects of the spun parts are analyzed. On the basis of artificial neural networks （ANN）, the surface quality defects of the spun parts are predicted. Experiments have proved that ANN can predict and diagnose the surface quality defects of the spun part successfully.
出处
《锻压技术》
CAS
CSCD
北大核心
2006年第3期79-83,共5页
Forging & Stamping Technology
关键词
滚珠旋压
强力旋压
神经元网络
铝合金
ball spinning
power spinning
artificial neuron networks
aluminum alloy
