• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (5): 242-250.doi: 10.3901/JME.2021.05.242

• 制造工艺与装备 • 上一篇    下一篇

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变切深工况下恒定切削力约束的多目标进给量优化方法

张阳1, 吴宝海1, 夏卫红1, 张莹1, 赵静2   

  1. 1. 西北工业大学航空发动机高性能制造工业和信息化部重点实验室 西安 710072;
    2. 中国航发动力股份有限公司精密铸造中心 西安 710021
  • 收稿日期:2020-06-03 修回日期:2020-12-15 出版日期:2021-03-05 发布日期:2021-04-28
  • 通讯作者: 张莹(通信作者),女,1981年出生,博士,副研究员。主要研究方向为计算机辅助几何设计、多轴数控加工及自适应加工技术。E-mail:zhangyingcdim@nwpu.edu.cn
  • 作者简介:张阳,男,1996年出生。主要研究方向为数控加工工艺优化和数据采集。E-mail:zyang@mail.nwpu.edu.cn
  • 基金资助:
    国家重点研发计划(2020YFB1710400)和陕西省重点研发计划重点(2018ZDXM-GY-063)资助项目。

Multi-objective Feed Optimization with Constant Cutting Force Constraints under Variable Cutting Depth

ZHANG Yang1, WU Baohai1, XIA Weihong1, ZHANG Ying1, ZHAO Jing2   

  1. 1. Key Laboratory of High Performance Manufacturing for Aero Engine (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi'an 710072;
    2. Precision Casting Center, AECC Aviation Power Co., Ltd., Xi'an 710071
  • Received:2020-06-03 Revised:2020-12-15 Online:2021-03-05 Published:2021-04-28

摘要: 针对数控加工中工艺人员设定恒定的进给量导致零件加工效率低、表面质量差的问题,提出基于恒定切削力约束的多目标进给量优化方法。以切削力预测模型为基础,以综合考虑提高零件加工效率和表面质量为优化目标,以恒定切削力,机床参数,加工表面质量和进给量平滑过渡为约束条件,建立了多目标进给量优化模型。通过正交切削试验标定切削力系数,并验证了预测模型的正确性和精确性。通过试切工件采集原始切削力,并试验分析确定出最优目标切削力值,采用基于精英控制的非支配筛选遗传算法(Controlled elitist non-dominated sorting genetic algorithm,Controlled NSGA-II)对进给量进行了优化。试验结果验证了恒定切削力约束的多目标进给量优化模型的有效性,达到了恒定切削力约束目标,保证了加工表面质量,提高了加工效率,实现了数控加工工艺参数优化,提高了数控系统应用性能。

关键词: 进给量优化, 恒定切削力, 多目标优化, Controlled NSGA-II

Abstract: Aiming at the problem of low machining efficiency and poor surface quality caused by the constant feed set by craftsmen in CNC machining, a multi-objective feed optimization method based on constant cutting force constraints was proposed. Based on the cutting force prediction model, taking comprehensive consideration to improve the machining efficiency and surface quality of parts as the optimization goal, and taking the constant cutting force, machine parameters, machined surface quality and feeding smooth transition as the constraint conditions, the multi-objective feed optimization model is established. Then, the cutting force coefficients are calibrated by orthogonal cutting experiments, and the correctness and accuracy of the prediction model are verified by experiments. The original cutting force data was collected by trial cutting the workpiece, and the optimal target cutting force value was determined through experimental analysis. The optimization model is used to optimize the feed based on the controlled elitist non-dominated sorting genetic algorithm (Controlled NSGA-II). The experimental results verified the effectiveness of the multi-objective feed optimization model, which reached the goal of constant cutting force constraint, guaranteed the quality of the machining surface, improved the machining efficiency, achieved the process parameters optimization, and finally improved the application performance of the numerical system.

Key words: feed optimization, constant cutting force, multi-objective optimization, controlled NSGA-II

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