中国机械工程 ›› 2014, Vol. 25 ›› Issue (2): 169-173.

• 机械基础工程 • 上一篇    下一篇

钛合金铣削加工参数多目标优化研究

陈建岭1;孙杰2;李剑峰2   

  1. 1.山东交通学院,济南,250023
    2.山东大学,济南,250061
  • 出版日期:2014-01-25 发布日期:2014-02-19
  • 基金资助:
    国家高技术研究发展计划(863计划)资助项目(2009AA44303);山东省自然科学基金资助项目(ZR2011GL006);山东大学自主创新基金资助项目(2011JC015) 

Multi-objective Optimization of Cutting Parameters during Milling of Titanium Alloys

Chen Jianling1;Sun Jie2;Li Jianfeng2   

  1. 1.Shandong Jiaotong University,Jinan,250023;;
    2.Shandong University,Jinan,250061
  • Online:2014-01-25 Published:2014-02-19
  • Supported by:
    National High-tech R&D Program of China (863 Program) (No. 2009AA44303);Shandong Provincial Natural Science Foundation of China(No. ZR2011GL006)

摘要:

为解决钛合金铣削加工存在的高成本、低效率问题,以生产效率最大和刀具寿命消耗率最小为目标,建立了铣削参数优化模型。提出了扩展非支配排序遗传算法(ENSGA-Ⅱ),对种群初始化子过程进行规范化处理,保证了种群的多样性和均匀性;根据Pareto最优原理将非支配概念从目标函数空间扩展到约束空间,使得多目标多约束问题的处理更具有适应性和有效性。实例表明,该方法具有良好的寻优能力,能够获得满意的Pareto解集。借助于该方法,工艺人员可根据优化目标灵活地选择铣削参数,更好地协调生产效率、生产成本和表面质量之间的关系。

关键词: 钛合金, 铣削, 加工参数, 多目标优化, Pareto最优

Abstract:

A multi-objective optimization model of cutting parameters was built to solve the problem of high cost and low efficiency while milling titanium alloys. The maximized productivity and the minimized rate of tool life elapsed were selected as the optimization objectives. An extended non-dominated sorting genetic algorithm-Ⅱ(ENSGA-Ⅱ) was presented. A normalized process was added into the subroutine of initialization to get better variety and more uniformly distribution of population. In order to handle the multi-objective and multi-constraint more adaptively and effectively, a concept of non-dominance was defined extensively from the objectives space to constraints space based on the principle of Pareto optimality. A case was used to investigate the effect of the proposed approach. The results show that the approach gives a good performance in finding satisfying Pareto solutions. By means of this approach, the technician is able to flexibly select the cutting parameters according to the optimization objectives, and to better coordinate the relations between productivity, cost and surface quality.

Key words: titanium alloy, milling, cutting parameter, multi-objective optimization, Pareto optimality

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