中速电火花线切割加工工艺建模与多目标优化研究

张国军; 李贺; 邵新宇; 黄禹

doi:10.13433/j.cnki.1003-8728.2015.0509

中速电火花线切割加工工艺建模与多目标优化研究

doi: 10.13433/j.cnki.1003-8728.2015.0509

1.
华中科技大学机械科学与工程学院, 武汉 430074;广东省制造装备数字化重点实验室, 东莞 523000

基金项目:

国家自然科学基金项目（51175207、51121002）、国家科技支撑计划项目（2012BAF13B07 ）及广东省数控一代示范工程项目（2012B011300015）资助

详细信息

作者简介:
张国军（1972-），教授，博士生导师，研究方向为精密电火花线切割和精密磨削与线切割工艺装备，zgj@mail.hust.edu.cn

计量
- 文章访问数: 224
- HTML全文浏览量: 35
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2013-07-20
- 刊出日期: 2015-05-05

Modeling and Multi-objective Optimization of Medium-speed WEDM Process

1.
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Guangdong Provincial Key Laboratory of Digital Manufacturing Equipment, Dongguan 523000, China

摘要

摘要: 利用正交试验设计，对中速电火花线切割加工过程中的脉冲宽度、脉冲间隙、峰值电流、丝筒速度和跟踪系数等工艺条件进行试验的优化设计。使用广义回归方法分别对加工参数与表面粗糙度（Ra）和材料去除率（MRR）之间的关系建模，并通过信噪比分析得出影响表面质量和加工效率的主要因素。表面质量随着电流的增加而变差；材料去除率随着脉宽和电流的增加而增加，丝速和跟踪系数对材料去除率几乎没有影响。运用非支配排序遗传算法（NSGA2）对MRR和Ra进行两目标优化，并对参数不同取值的优化结果进行了比较；NSGA2中的遗产操作参数对优化结果影响很小，算法具有鲁棒性。当种群规模和遗传代数足够大时，可以得到足够多且分布均匀的Pareto前沿。
- 电火花线切割 /
- 非线性系统 /
- 正交试验 /
- 广义回归 /
- 信噪比 /
- 非支配排序遗传算法
Abstract: The orthogonal experimental design method was used to optimize its technological parameters such as pulse-on time, pulse-off time, peak pulse current, wire cylinder speed and tracking coefficient of the medium-speed WEDM process. The relationship between process parameters and surface roughness (Ra) and the material removal rate (MRR) were modeled with the generalized regression method. Then the important factors that affect Ra and MRR are obtained with the signal to noise ratio (S/N Ratio) analysis. Finally, the non-dominated sorting genetic algorithm II (NSGA2) was used to optimize MRR and Ra. The effects of the corresponding parameters on optimal results were discussed. When the population size and the genetic number are larger enough, the adequate and uniform distribution Pareto front can be obtained.
- generalized regression /
- multiobjective optimization /
- non-dominated sorting genetic algorithm II (NSGA2) /
- orthogonal experiment /
- signal to noise ratio /
- surface roughness

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