Cutting Parameter Optimization Technique for High Efficiency NC Machining

被引:1
作者
Cai, Anjiang [1 ]
Guo, Shihong [1 ]
Dong, Zhaoyang [1 ]
Guo, Hongwei [1 ]
机构
[1] Xian Univ Architecture & Technol, Xian 710055, Shaanxi, Peoples R China
来源
MECHATRONICS AND INTELLIGENT MATERIALS, PTS 1 AND 2 | 2011年 / 211-212卷
关键词
high efficiency NC machining; cutting parameter; optimization technique; BP neural network;
D O I
10.4028/www.scientific.net/AMR.211-212.167
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
High efficient cutting process technique is one of the main development directions of cutting process technology in the future, a reasonable choice of NC machining cutting parameter is an important way to realize high efficiency NC machining. NC machining cutting parameter optimization techniques were studied, using BP neural network, milling parameters optimization model of aluminum alloy shell structure was built, and the structure of BP neural network was analysed, realizing the optimizing of the BP neural network model, the improving of the convergence accuracy, convergence speed, prediction accuracy, generalization ability of BP neural network model, which optimized the cutting parameters selection and predicted the processing efficiency to provide a theoretical basis for the selection of high efficiency NC machining cutting parameter. Production practice showed: the application of the optimized cutting parameters of BP neural network for processing could improve processing efficiency, reduce costs notablely while guaranteeing the processing quality, and achieve the optimization of integrated application efficiency for high efficiency NC machining and NC machine, so it has a higher promotional value.
引用
收藏
页码:167 / +
页数:2
相关论文
共 6 条
[1]  
Balazinski M, 2002, ENG APPL ARTIF INTEL, V73-80, P15
[2]  
GUO Wei, 2008, J JILIN U ENG TECHNO, V84-88, P38
[3]  
LIU Hai Jiang, 2008, J TONGJI U NATURAL S, V803-806, P36
[4]  
Szeesi T, 1999, MAT PROCESS TECHNOL, V344-349, P92
[5]  
WANG Qiaohua, 2006, T CHINESE SOC AGR MA, V104-106, P37
[6]  
Zhao H., 2008, MACHINE TOOL HYDRAUL, V36, P213