• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (11): 184-194.doi: 10.3901/JME.2017.11.184

• 绿色制造技术 • 上一篇    下一篇

面向能效的曲面数控加工刀具路径优化方法

李丽, 邓兴国, 尚川博   

  1. 西南大学工程技术学院 重庆 400715
  • 出版日期:2017-06-05 发布日期:2017-06-05
  • 作者简介:

    李丽(通信作者),女,1982年出生,副教授,硕士研究生导师。主要研究方向为可持续设计与制造,现代设计方法。

    E-mail:swulili@swu.edu.cn

    邓兴国(通信作者),男,1992年出生。主要研究方向为绿色制造。

    E-mail:dxgjy0409@163.com

  • 基金资助:
    * 国家自然科学基金(51451396)、重庆市基础科学与前沿技术(cstc2016jcyjA0422)和西南大学实验技术研究(SYJ2016013)资助项目; 20160911收到初稿,20161217收到修改稿;

Tool Path Optimization with High-efficiency and Low Energy Consumption for Surface CNC Machining

LI Li, DENG Xingguo, SHANG Chuanbo   

  1. College of Engineering Technology, Southwest University, Chongqing 400715
  • Online:2017-06-05 Published:2017-06-05

摘要:

刀具路径规划是曲面数控加工过程的一个重要环节,优化的刀具路径能显著提高曲面加工效率,降低机床能量消耗。通过对刀具路径优化问题的描述及其影响因素的分析,建立以机床加工效率和能量消耗为目标,以主轴转速、进给量、机床功率、主轴力矩、加工行距及表面质量为约束的刀具路径优化模型。在模型优化求解过程中,根据待加工曲面曲率半径、刀具半径及曲面加工后的残留高度,优化出合理的刀触点间距和加工行距以确定刀触点;采用自适应模拟退火遗传算法对刀触点连接顺序和方式进行优化运算,寻求最优刀具路径。通过实例加工和与传统方法的对比,验证了提出方法的有效性和实 用性。

关键词: 刀具路径优化, 加工能耗, 曲面数控加工, 遗传算法, 加工效率

Abstract:

Tool path planning is an important content in the process of complex surface CNC machining, and tool path optimization can significantly improve the machining efficiency, reduce the energy consumption of machine tools. Based on the description of the tool path optimization and the analysis of impact factors, an optimization model is established to achieve high machining efficiency and low energy consumption, with the constraints of the spindle speed, feed rate, power of machine tool, spindle torque, machining intervals and surface quality. In the optimization process, the number of the cutting contact points is determined by the optimized the cutter spacing and intervals, according to the surface curvature, cutter radius, and residual height of surface. The connection order and path way are optimized by using adaptive simulated annealing genetic algorithm. Finally, the validity and practicability of the proposed method are verified by practical examples compared with several traditional methods.

Key words: energy consumption, genetic algorithm, surface CNC machining, tool path optimization, machining efficiency