摘要
针对汽轮机叶片常用钢2Cr13不锈钢在切削加工中表面质量存在的问题,对高速铣削条件下2Cr13不锈钢表面粗糙度预测模型进行了研究。将最小二乘支持向量机原理应用到高速铣削2Cr13不锈钢的表面粗糙度预测建模中。得出的模型能方便地预测铣削参数对表面粗糙度的影响,并能利用有限的试验数据得出整个工作范围内的表面粗糙度预测值。经试验验证,应用最小二乘支持向量机原理建立的粗糙度预测模型回归预测精度高。基于最小二乘支持向量机原理建模方法适合于表面粗糙度预测。
For 2Cr13 stainless steel in the cutting surface quality prediction,this paper studied the high-speed milling surface roughness prediction model of stainless steel.This principle of the least squares support vector machine is applied to the high-speed milling of 2Cr13 stainless steel surface roughness prediction modeling.The model can be easily predicted milling parameters on surface roughness.And it can take advantage of the limited test data to obtain over the entire range of surface roughness prediction.Based on the experimental validation,the roughness of the regression prediction model has high precision.The least squares support vector machine modeling approach is good for surface roughness prediction.
出处
《工具技术》
2012年第2期73-76,共4页
Tool Engineering
关键词
表面粗糙度
预测模型
最小二乘支持向量机
高速铣削
surface roughness
prediction model
least squares support vector machine
high-speed milling
