摘要
钛合金较差的切削加工性不利于保证好的表面完整性,影响钛合金零件的使用性能。基于田口方法建立钛合金车削试验模型,考察切削用量对表面粗糙度、刀具寿命、切削力和材料去除率的影响规律,以材料去除率为目标函数,以表面粗糙度、刀具寿命和切削力为约束函数,基于Krig-ing插值的响应曲面法和遗传算法构建了钛合金车削参数优化模型。研究结果表明:钛合金车削过程参数最优的水平组合为v3f1ap1r1E3,优化结果与初始试验相比,表面粗糙度、刀具寿命、切削力和材料去除率分别改善了75.86%、65.16%、36.41%和557.91%。
The poor machinability of titanium alloys has limited good surtace integrity wmcn aIxects me proce^sm~ and servicing properties. The experimental model for the titanium alloy turning based on the Taguchi method were proposed to express the correlation between the processing variables and the responses. With material removal rate as objective function and surface roughness, tool life, cutting force as constraint function, the optimization proce- dure of titanium alloy turning was presented based on the response surface method via Kriging interpolation and ge- netic algorithm. The results indicate that the optimum parameter levels for different variables have been suggested as v3f1ap1r1E3., Comparing to the initial experiment, surface roughness, tool life, cutting force and material removal rate of the optimal condition are improved with 75.86%, 65.16%, 36.41% and 557.91%, respectively.
出处
《机械科学与技术》
CSCD
北大核心
2013年第4期469-474,共6页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(51175262)
安徽高校省级科学研究项目(KJ2013Z192)
教育部新世纪优秀人才支持计划项目(NCET-08)
安徽省高等学校优秀青年基金项目(2010SQRL117)资助
关键词
钛合金
车削试验模型
KRIGING插值
遗传算法
优化
titanium alloy
turning experimental model
Kriging interpolation
genetic algorithms
optimization
