Prediction Model of Milling Surface Roughness Based on Genetic Algorithms

被引：3

作者：

Chen, Ying ^{[1
]}

Sun, Yanhong ^{[1
]}

Lin, Han ^{[1
]}

Zhang, Bing ^{[1
]}

机构：

[1] Jilin Teachers Inst Engn & Technol, Changchun 130000, Jilin, Peoples R China

来源：

CYBER SECURITY INTELLIGENCE AND ANALYTICS | 2020年 / 928卷

关键词：

Surface roughness; High speed milling; Genetic algorithm; Prediction model;

D O I：

10.1007/978-3-030-15235-2_179

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

According to the orthogonal test results, the surface roughness prediction model based on BP artificial neural network algorithm combined with genetic algorithm and considering material removal rate, a multi-objective optimization mathematical model for high-speed milling process parameters optimization was established, and the optimal combination of parameters satisfying the requirements was found within the given parameters range. The method is validated by comparing the surface roughness and processing efficiency with the optimization parameters determined by range analysis method.

引用

页码：1315 / 1320

页数：6

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