中国机械工程

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规则约束下基于免疫遗传算法的机加工艺规划

郭祥雨;王琳;张永健   

  1. 哈尔滨工业大学(威海)船舶与海洋工程学院,威海,264200
  • 出版日期:2020-02-25 发布日期:2020-04-17
  • 基金资助:
    国家自然科学基金资助项目(51705100);
    中央高校基本科研业务费专项资金资助项目(HIT.NSRIF.2019078);
    装备预研领域基金资助项目(61409230102);
    校地共建支持项目

Machining Process Planning Based on Immune Genetic Algorithm under Rule Constraints

GUO Xiangyu;WANG Lin;ZHANG Yongjian   

  1. School of Naval Architecture and Ocean Engineering,Harbin Institute of Technology(Weihai Campus),Weihai,Shandong,264200
  • Online:2020-02-25 Published:2020-04-17

摘要: 由于特征的加工可能适应多种加工方法,因此在加工成本的计算公式中考虑了不同加工方法的制造资源与加工时长产生的成本差异。在免疫遗传算法基础上,利用前趋图描述工步关系并指导初始工艺路线的生成,引入自适应平行变换算子指导加工方法和制造资源的动态调整,使算法变异力度具有跟随迭代过程的动态调整能力。最后,以回转体零件的机加工艺路线为例验证了改进免疫遗传算法的有效性。

关键词: 工艺路线规划, 免疫遗传算法, 规则约束, 前趋图, 自适应平行变换算子

Abstract: Since machining features might be adapted to multiple manufacturing methods, the cost difference between manufacturing resources and processing time caused by different processing methods was considered in the calculation formula of machining cost. On the basis of immune genetic algorithm, a precedence graph was used to describe the process step relationship and generate the initial processes. An introduction to adaptive parallel transformation operator was used to guide the dynamic adjustment of processing methods and manufacturing resources, which enabled the algorithm to have adaptive adjustment capabilities that could follow the iterative processes. Finally, the effectiveness of the improved immune genetic algorithm was verified by taking the machining process decision of a rotating part as an example.

Key words: process planning, immune genetic algorithm, rule constraint, precedence graph, adaptive parallel transformation operator

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