• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (11): 157-163.doi: 10.3901/JME.2017.11.157

• 绿色制造技术 • 上一篇    下一篇

面向低能耗少切削液的多目标加工参数优化

马峰1, 张华1, 曹华军1,2   

  1. 1. 武汉科技大学机械自动化学院 武汉 430081;
    2. 重庆大学机械传动国家重点实验室 重庆 400044
  • 出版日期:2017-06-05 发布日期:2017-06-05
  • 作者简介:

    马峰,男,1989年出生,博士研究生。主要研究方向为绿色制造,制造系统能效。

    E-mail:MF0425@163.com

  • 基金资助:
    * 国家自然科学基金资助项目(51275365); 20160802收到初稿,20161218收到修改稿;

Multi-objective Machining Parameters Optimization for Low Energy and Minimum Cutting Fluid Consumption

MA Feng1, ZHANG Hua1, CAO Huajun1,2   

  1. 1. School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081;
    2. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044
  • Online:2017-06-05 Published:2017-06-05

摘要:

数控加工是一种广泛采用的机械制造加工方法,为实现数控加工的高能效,从数控铣削加工的低能耗少切削液两个方面对切削参数进行优化,建立切削加工过程能量消耗目标函数和切削液消耗目标函数。考虑加工过程中数控机床设备性能和加工质量的实际约束条件,建立以数控加工的切削速度和进给量以及切削液流速为优化变量,以最低加工能耗和最少切削液消耗为目标的多目标优化模型,并应用非支配排序遗传算法-II对优化模型进行优化求解。最后,通过某具体实例验证了所建模型的有效性。

关键词: 低能耗, 多目标优化, 切削参数, 少切削液, 数控加工

Abstract:

The NC machining is a widely used processing method in the mechanical manufacturing system. In order to realize the high efficiency of the NC machining, the NC milling parameters optimization problem for low energy and minimum cutting fluid consumption is studied. The energy consumption objective function and cutting fluid consumption objective function are established. Considering the machine tool property and processing quality constraints, a multi-objective optimization model is established, which takes the NC machining cutting speed and feed and cutting fluid flow as the variables, the lowest energy consumption and the minimum cutting fluid consumption as the optimization objectives and non-dominated sorting genetic algorithm-II (NSGA-II) algorithm is applied to solve it. An experiment case is performed to verify the effectiveness of the optimization model, and the machining parameters optimization results are analyzed.

Key words: cutting parameters, low energy, minimum cutting fluid, multi-objective optimization, NC machining