摘要
提出利用神经网络进行高速铣削表面粗糙度预报的方法,给出了具体的网络实现过程,应用灵敏度剪枝算法克服了网络隐层难以确定的问题,仿真结果表明该方法的有效性,对高速加工切削参数的选择和表面质量控制具有指导意义。
The prediction models for surface roughness of high speed machining was created based on neural networks ,the networks was realized and sensitivity pruning algorithm was applied to resolve the problem that the hidden layer nodes of neural networks are hard to determine ,the simulation shows the method is effective and can provide a guidance to optimize cutting pararneters and control surface quality.
出处
《机械设计与制造》
北大核心
2010年第3期216-217,共2页
Machinery Design & Manufacture
基金
河南省教育厅自然科学研究资助项目(2008A510014)
关键词
神经网络
预测模型
剪枝算法
表面粗糙度
Neural network
Prediction model
Pruning algorithm
Surface roughness