摘要
对不同工艺参数组合的连杆衬套的强力旋压成形过程进行了模拟,基于BP神经网络技术,建立了工艺参数与壁厚之间的非线性函数关系。用模拟实验结果训练神经网络模型,以实现对连杆衬套壁厚的预测。该方法不仅可以缩短工艺参数优化的时间,而且能够有效地提高连杆衬套工艺设计的效率。
The power spinning processes of connecting rod bushing at different process parameters were simulated. The nonlinear functional relationship between the process parameters and the wall thickness was established based on BP neural network technology. The simulated experimental results was used to train the neural network model, in order to predict rod bushing wall thickness. This method can not only shorten the time of process parameter optimization, but also effectively improve the efficiency of rod bushing process design.
出处
《热加工工艺》
CSCD
北大核心
2014年第3期129-130,134,共3页
Hot Working Technology
基金
山西省自然科学基金项目(2012011023-2)
山西省高校高新技术产业化项目(20120021)
关键词
连杆衬套
强力旋压
工艺参数
BP神经网络
预测
connecting rod bushing
power spinning
process parameters
BP neural network
prediction
