基于变长度编码遗传算法的铣削深度分配优化  

Milling Depth Allocation Optimization Based on Variable Length Coded Genetic Algorithm

作　　者：郑晓军[1] 段泽波 郑人豪 ZHENG Xiaojun;DUAN Zebo;ZHENG Renhao(School of Mechanical Engineering,Dalian Jiaotong University,Dalian Liaoning 116028,China)

机构地区：[1]大连交通大学机械工程学院,辽宁大连116028

出　　处：《机床与液压》2022年第17期95-100,共6页Machine Tool & Hydraulics

基　　金：辽宁省教育厅基金(JDL2019016);辽宁省自然科学基金(2019-ZD-0115)。

摘　　要：根据某企业车辊机架大轴向铣削深度的实际需求,在满足铣削总深度及加工精度要求下,为实现对轴向铣削深度分配方案的智能决策,建立了刀具失效累计率和铣削总时间为优化目标的分配数学模型。通过对轴向铣削深度分配进行可变长度编码,对遗传算子交叉、变异的重新改写,并采用加权方法处理优化结果。结果表明:与传统平均分配方式相比较,采用变长度编码的遗传算法所获得的目标值最高减少16.5%。该方法可提高企业生产效率,降低企业成本。According to the actual demand of large axial milling depth of the turning roller frame of an enterprise,under the requirement of total milling depth and machining accuracy,an allocation mathematical model with tool failure accumulation rate and total milling time as the optimization target was established to realize the intelligent decision on the axial milling depth allocation scheme.The optimization results were processed by variable-length encoding of axial milling depth assignment,rewriting of genetic operator crossover and variation,and using a weighting method.The results show that a maximum reduction of 16.5%in the target value can be obtained by the genetic algorithm with variable length coding compared to the traditional average distribution method.This method can improve the production efficiency and reduce the cost of the enterprise.

关 键 词：轴向铣削深度 可变长度编码 变长度编码遗传算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]