实时振动数据驱动的薄壁件平铣工艺参数自适应优化

doi:10.3901/JME.2020.23.172

机械工程学报 ›› 2020, Vol. 56 ›› Issue (23): 172-184.doi: 10.3901/JME.2020.23.172

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实时振动数据驱动的薄壁件平铣工艺参数自适应优化

赵雄¹, 郑联语¹, 樊伟¹, 余路²

1. 北京航空航天大学机械工程及自动化学院北京 100083;
2. 上海飞机制造有限公司C919事业部智能装配技术室上海 201324

收稿日期:2019-12-18 修回日期:2020-06-24 出版日期:2020-12-05 发布日期:2021-01-11
作者简介:赵雄,男,1995年出生,博士研究生。主要研究方向为数字化与智能加工工艺及系统、可重构柔性智能工装。E-mail:zhaoxiong@buaa.edu.cn;郑联语(通信作者),男,1967年出生,博士,教授,博士研究生导师。主要研究方向为数字化与智能制造、可重构制造系统、制造建模与仿真,下一代工业辅助技术及系统。E-mail:lyzheng@buaa.edu.cn;樊伟,男,1989年出生,博士研究生。主要研究方向为薄壁件自适应精加工、可重构柔性智能工装、数字化设计与智能制造。E-mail:fanweiok@buaa.edu.cn;余路,男,1986年出生,硕士,工程师。主要研究方向为飞机大部件自适应加工。E-mail:yulu@comac.cc
基金资助:
国家自然科学基金资助项目（51775024）。

Real-time Machining Vibration Data Driven Milling Process Parameters Adaptive Optimization

ZHAO Xiong¹, ZHENG Lianyu¹, FAN Wei¹, YU Lu²

1. School of Mechanical Engineering and Automation, Beihang University, Beijing 100083;
2. Business Department, Shanghai Aircraft Manufacturing Co., Ltd, Shanghai 201324

Received:2019-12-18 Revised:2020-06-24 Online:2020-12-05 Published:2021-01-11

摘要/Abstract

摘要： 为减小加工振动对薄壁件平铣（端面盘铣）加工质量及效率的影响，提出一种实时铣削振动数据驱动的平铣工艺参数自适应优化方法。首先根据再生效应原理建立薄壁件平铣颤振稳定性模型。其次将薄壁件平铣过程中前一个工步内的实测振动数据分为若干段，以此模拟其材料去除过程，对各段铣削振动数据进行分析，由有限元单位力法和优化STD法分别识别出薄壁件刚度和各材料去除阶段模态频率及阻尼比，并由此导出薄壁件单模态频响函数，将其代入颤振稳定性模型求解稳定域叶瓣图并做插值处理后即可确定包含材料去除信息的薄壁件三维颤振稳定域叶瓣图。基于此，以避免铣削颤振、共振和满足机床性能要求为约束条件，以材料去除率最大为目标，利用遗传算法计算薄壁件下一个工步较优的工艺参数，如此循环进行，直到完成薄壁件加工。最后，通过某型飞机垂尾薄壁装配界面平铣试验验证该方法的可行性和有效性。由试验结果可看出，采用优化后的加工工艺参数，能使薄壁装配界面粗加工过程表面粗糙度从Ra 3.2提升为Ra 1.6，加工效率提高33%。

关键词: 实时振动数据, 薄壁件, 工艺参数优化, 工步, 优化STD法

Abstract: In order to decrease the influence of machining vibration to the finishing quality and efficiency of the thin-walled parts, this paper proposed a real-time machining vibration data driven milling process parameters adaptive optimization method. Firstly, the chatter stability model is constructed according to the regeneration principle. Next, dividing the measured vibration data of one step into several segments to simulate the material remove process. The stiffness and modal parameters of thin-walled parts is calculated by finite element unit force method and optimized STD method to derive the frequency response function of thin-walled parts, which is used to calculate the 3D stability lobe diagram. Then, taking the maximum material removal rate as the goal, the genetic algorithm is used to calculate the optimized process parameters of next process step considering to avoid the milling chatter and resonance. Repeat the above cycle again until the thin-walled parts milling process is completed. Finally, the feasibility and effectiveness of the method are verified by the assembly interface of aircraft cutting experiment. The experiment results proves that the method can not only shorten the assembly interface milling process time by 33%, but also improve the surface roughness from Ra 3.2 to Ra 1.6.

Key words: real-time vibration data, thin-walled parts, process parameters optimization, process step, optimized STD method

中图分类号:

V262

赵雄, 郑联语, 樊伟, 余路. 实时振动数据驱动的薄壁件平铣工艺参数自适应优化[J]. 机械工程学报, 2020, 56(23): 172-184.

ZHAO Xiong, ZHENG Lianyu, FAN Wei, YU Lu. Real-time Machining Vibration Data Driven Milling Process Parameters Adaptive Optimization[J]. Journal of Mechanical Engineering, 2020, 56(23): 172-184.

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实时振动数据驱动的薄壁件平铣工艺参数自适应优化

Real-time Machining Vibration Data Driven Milling Process Parameters Adaptive Optimization

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