基于NSGA-II算法的高强模具钢切削参数优化方法
Parameters Optimization in Cutting of High-strength Mould Steel Based on NSGA-II
查看参考文献10篇
|
文摘
|
以高强度模具钢NAK80为对象,设计以切削速度、每转进给量、切削深度为参数的正交试验,并通过线性回归方法建立切削力及表面粗糙度的数理统计模型;配合材料去除率的理论公式,建立三者为目标函数的多目标优化模型,采用非支配排序遗传算法NSGA-II对模型进行寻优求解,研究高强度模具钢铣削过程中的工艺参数优化,获得了多组符合加工要求的工艺参数组合。结果表明:该方法可以获得最优的切削工艺参数组合,可用于指导实际的加工生产。 |
|
其他语种文摘
|
An orthogonal experiment for high-strength mould steel NAK80 was designed with cutting speed, feed rate and cutting depth as relevant parameters. According to the experimental results, statistical models of cutting force and surface roughness were built up using a linear regression method. Superadded the theoretical formula of material removal rate, a multi-objective optimal model with three objective functions was built up and optimized by applying non-dominated sorting genetic algorithm-II(NSGA-II), to study the optimization of parameters in milling process for high-strength mould steel. Several cutting parameter combinations conforming to the requirements were acquired. The results show the proposed method can get the optimal cutting parameter combinations and guided the actual production. |
|
来源
|
机械工程材料
,2013,37(12):85-91 【核心库】
|
|
关键词
|
NAK80钢
;
切削参数
;
数理统计模型
;
多目标优化
|
|
地址
|
中国科学院沈阳自动化研究所, 沈阳, 110016
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1000-3738 |
|
学科
|
金属学与金属工艺 |
|
基金
|
国家自然科学基金资助项目
;
国家973计划
|
|
文献收藏号
|
CSCD:5014435
|
参考文献 共
10
共1页
|
|
1.
Taylor F W. On the art of cutting metals.
Transactions of ASME,1907,28:31-35
|
被引
5
次
|
|
|
|
|
2.
Baskar N. Selection of optimal machining parameters for multi-tool milling operations using a memetic algorithm.
Journal of Materials Processing Technology,2006,174(13):239-249
|
被引
2
次
|
|
|
|
|
3.
王军. 一次走刀立铣加工优化与CAM软件开发.
机械工程学报,2003,39(10):141-146
|
被引
2
次
|
|
|
|
|
4.
Benardos P G. Prediction of surface roughness in CNC face milling using neural networks and tagu chi's design of experiments.
Robotics and Computer-Integrated Manufacturing,2002,18(5/6):343-354
|
被引
8
次
|
|
|
|
|
5.
Wang M Y. Parametric optimization on multi-objective precision turning using grey relational analysis.
Information Technology Journal,2008,7(7):1072-1076
|
被引
2
次
|
|
|
|
|
6.
张臣. 基于仿真数据的数控铣削加工多目标变参数优化.
计算机辅助设计与图形学学报,2005,17(5):1039-1045
|
被引
10
次
|
|
|
|
|
7.
Agapiou J S. The optimization of machining operations based on a combined criterion, part 1: the use of combined objectives in single-pass operations.
Transactions of ASME,1992,114(4):500-507
|
被引
4
次
|
|
|
|
|
8.
Srinivas N. Multi-objective optimization using non-dominated sorting in genetic algorithms.
Evolutionary Computation,1994,2(1):221-248
|
被引
516
次
|
|
|
|
|
9.
Deb K. A fast and elitist multiobjective genetic algorithm: NSGA-II.
IEEE Transactions on Evolutionary Computation,2002,6(2):182-197
|
被引
3061
次
|
|
|
|
|
10.
王占礼. 数控车削加工仿真中的切削力预测.
大连交通大学学报,2010,31(1):17-20
|
被引
1
次
|
|
|
|
|
了解气象卫星更多信息，请访问