单晶硅电火花成形加工试验研究与工艺参数优化

发布时间：2018-07-09 15:50

  本文选题：机械制造工艺与设备 + 电火花成形加工　； 参考：《兵工学报》2017年09期

【摘要】：针对电火花加工过程中材料去除率、表面粗糙度和电极损耗这3个工艺目标不能同时兼顾的问题,以P型单晶硅为试验加工对象,采用中心组合设计试验考察峰值电流、脉冲宽度、脉冲间隔对单晶硅电火花成形加工过程中材料去除率、表面粗糙度以及电极损耗的影响,引入响应曲面法建立材料去除率、表面粗糙度和电极损耗的2阶关系模型,方差分析结果表明响应模型具有很好的拟合程度和适应性。进一步分析实际加工条件对工艺参数的约束,以提高材料去除率,降低表面粗糙度和电极损耗为目标建立工艺参数优化模型,设计基于带精英策略的非支配排序遗传算法对优化问题进行求解。在最优解条件下材料去除率的验证结果与理论最优值的平均相对误差为4.9%,表面粗糙度的验证结果与理论最优值的平均相对误差为5.2%,电极损耗的验证结果与理论最优值的平均相对误差为5.7%.验证试验表明,该算法能实现硅材料放电成形加工过程的工艺参数优化。
[Abstract]:In order to solve the problem that the material removal rate, surface roughness and electrode loss can not be taken into account simultaneously in EDM, P-type monocrystalline silicon is taken as the experimental processing object, and the peak current is investigated by the central combination design test. The effects of pulse width and pulse interval on material removal rate, surface roughness and electrode loss in EDM process were studied. The second order model of material removal rate, surface roughness and electrode loss was established by using response surface method. The results of variance analysis show that the response model has good fitting degree and adaptability. In order to improve the material removal rate, reduce the surface roughness and electrode loss, the optimization model of the process parameters is established by further analyzing the constraints of the actual processing conditions on the process parameters. An undominated sorting genetic algorithm with elitist strategy is designed to solve the optimization problem. The average relative error between the material removal efficiency and the theoretical optimal value is 4.9, the average relative error between the surface roughness verification result and the theoretical optimal value is 5.2, and the electrode loss verification result is the theoretical one. The average relative error of the best value is 5.7. The experimental results show that the algorithm can optimize the process parameters of the discharge forming process of silicon material.
【作者单位】： 西安理工大学机械与精密仪器工程学院;西安现代控制技术研究所;
【基金】：国家自然科学基金项目(51575442) 陕西省自然科学基金项目(2016JZ011) 陕西省教育厅基金项目(2014SZS10-Z01)
【分类号】：TQ127.2
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本文编号：2109865