Abstract: To improve the numerical control machining efficiency of the rocket tank panel with multi-pocket,a tool optimization selection method for multi-pocket based on genetic algorithm was proposed.The influence of tool size and machining strategy on machining time was studied.Then,the machining time model of the tool milling process was constructed.The tools in the optional tool group were used as genetic genes,the milling machining time as the fitness function,and the tool diameter and tool number as the optimization variables,a genetic algorithm for optimal selection of roughing tools was established to maximize machining efficiency based on existing machining resources.The example test showed that the tool selected by the proposed method could shorten the machining time by 64.5% compared to the initial tool machining time.

Key words: genetic algorithms, tool combination selection, rocket tank panel, multi-pocket, tool optimization, numerical control machining

摘要： 为提高具有多槽腔结构的火箭贮箱壁板的数控加工效率,针对贮箱壁板数控加工自动选刀问题,提出基于遗传算法的多槽腔粗加工刀具组合优化选取方法。研究了刀具尺寸与加工策略对加工时间的影响,构建了刀具铣削过程加工时间模型;以可选刀具组内的刀具作为遗传基因,铣削加工时间作为适应度函数,刀具直径和刀具数量作为优化变量,建立了粗加工刀具组合优化选取遗传算法,实现了对基于现有加工资源的加工效率的最大化。实例测试表明,所提方法选取的组合刀具的加工时间相对于初始刀具加工时间缩短了64.5%。

关键词: 遗传算法, 刀具组合选取, 火箭贮箱壁板, 多槽腔, 刀具优化, 数控加工