摘要
为了提高防锈铝合金加工质量和效率,通过对防锈铝合金ALMn1Cu进行系统的高速铣削加工试验,该文研究了切削参数对表面粗糙度的影响。根据析因试验的方差分析结果得到了切削参数中影响表面粗糙度的显著性影响因素,并采用最小二乘回归法建立了基于切削参数的表面粗糙度预测模型。在预测模型的基础上建立了以最大加工过效率为优化目标的切削参数优化模型,运用遗传优化算法对切削参数进行了优化计算,得到了不同表面粗糙度技术要求下较优的切削参数组合。应用优化结果对某新型雷达上功能件进行了加工实验,将加工效率提高了近两倍。
In order to improve the machined surface quality and processing efficiency of the anti-rust aluminum alloy,a series of cutting experiments on AlMn1Cu is conducted to study the effect of the cutting parameters on the surface roughness in high-speed milling.According to the analysis result of variance(ANOVA) of factorial experiments,the cutting parameters significantly influencing the surface roughness are presented.The predictive mathematic model of surface roughness based on the cutting parameters is established by using the least-squares regression method.An optimization model of cutting parameters leading to maximum material removal rate is built according to the predictive mathematic model of surface roughness,and the genetic algorithm is employed to find the optimum cutting parameters in the different ranges of surface roughness values.The processing efficiency of the ALMn1Cu functional parts of a new type of radar in machining experiment increases by two times utilizing the research results.
出处
《南京理工大学学报》
EI
CAS
CSCD
北大核心
2010年第4期537-542,共6页
Journal of Nanjing University of Science and Technology
基金
国家部委"十一五"预研项目
关键词
高速铣削
表面粗糙度
铝合金
切削参数
遗传算法
high-speed milling
surface roughness
aluminum alloy
cutting parameters
genetic algorithm