Surface Roughness Prediction of High Speed Milling Based on Back Propagation Artificial Neural Network

被引：2

作者：

Hu, Jinping ^{[1
]}

Li, Yan ^{[1
]}

Zhang, Jingchong ^{[1
]}

机构：

[1] Heilongjiang Inst Sci & Technol Harbin, Harbin 150027, Peoples R China

来源：

ADVANCED MANUFACTURING SYSTEMS, PTS 1-3 | 2011年 / 201-203卷

关键词：

Aluminum Alloy; High Speed Milling; Surface Roughness; BP Artificial Neural Network;

D O I：

10.4028/www.scientific.net/AMR.201-203.696

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Prediction of surface roughness is an important research for machining quality analysis. In order to predict surface roughness in machining, increasing productivity under ensuring milling, the artificial neural network is introduced into milling area. To build high-speed milling surface roughness prediction model using BP neural network. Prediction results are compared with experimental value, which shows that this method can achieve better prediction accuracy. It has certain significance for parameters selection of high-speed milling and quality control of the surface.

引用

页码：696 / 699

页数：4