摘要
以轿车离合器板料多工步级进冲压轴承套圈为例,提出一种适用于大变形、大应变的级进冲压过程的径向基函数神经网络模型,结合有限元计算机数值模拟结果和遗传算法,达到优化冲压工艺参数的目的。
Taking the bearing ring of car clutch from sheet metal multi-step stamping for example, a new Radial Basis Function (RBF) Neural Network model applicable for large deformation and large strain in progressive stamping procedure was put forwarded in this paper. With the help of computer finite element numerical simulation and genetic algorithm, the stamping technology parameter could be optimized.
出处
《洛阳工学院学报》
1999年第3期73-76,共4页
Journal of Luoyang Institute of Technology
基金
机械工业部技术发展基金
关键词
离合器
神经网络
最佳化
轴承
套圈
轿车
汽车
Clutches
Neural networks
Optimization
Bearings
Bearings rings