Prediction of Surface Roughness for HSM Based on BP Neural Network

被引：0
|
作者：
Chen, Ying [1 ]
Sun, Yanhong [1 ]
Yang, Zhenwen [1 ]
Wu, Guangdong [1 ]
机构：
[1] Jilin Engn Normal Univ, Coll Mech Engn, Changchun 130052, Jilin, Peoples R China
来源：
PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, INFORMATION AND COMPUTER SCIENCE (ICEMC 2017) | 2017年 / 73卷
关键词：
Surface roughness; BP neural network; Cutting parametres; 5-axis machine; Toroidal cutter;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A predictive model is presented for the surface roughness in high-speed milling of P1.2738 (plastic die steel) based on BP Neural network. The data for establishing the model is derived from the experiment conducted on a high-speed 5-axis machining center by factorial design of experiments. Compared with measured data and data from regression analysis, the result of prediction using BP neural network indicates its feasibility, which provides reference for the optimization of cutting parameters.
引用
收藏
页码：421 / 424
页数：4
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