车削粗糙表面的特征解耦与形貌仿真

doi:10.3901/JME.2019.23.200

机械工程学报 ›› 2019, Vol. 55 ›› Issue (23): 200-209.doi: 10.3901/JME.2019.23.200

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车削粗糙表面的特征解耦与形貌仿真

安琪¹, 索双富², 林福严¹, 李永健², 时剑文²

1. 中国矿业大学(北京)机电与信息工程学院北京 100083;
2. 清华大学机械工程系北京 100084

收稿日期:2019-03-22 修回日期:2019-07-14 出版日期:2019-12-05 发布日期:2020-02-18
通讯作者: 安琪(通信作者),男,1991年出生,博士研究生。主要研究方向为摩擦学、粗糙表面接触。E-mail:kuangdaanqi@163.com
作者简介:索双富,男,1963年出生,博士,副教授。主要研究方向为摩擦磨损、润滑与密封。E-mail:sfsuo@tsinghua.edu.cn;林福严,男,1958年出生,博士,教授。主要研究方向为摩擦磨损、胶带输送机压线阻力。E-mail:linfy@cumtb.edu.cn;李永健,男,1981年出生,博士,助理研究员。主要研究方向为流体密封、摩擦磨损。E-mail:liyongjian@tsinghua.edu.cn;时剑文,男,1990年出生,博士后。主要研究方向为干气密封、摩擦磨损。E-mail:shjw6222@mail.tsinghua.edu.cn
基金资助:
国家重大仪器专项资助项目（2017YFF0108101）。

Feature Decoupling and Shape Simulation of Turning Rough Surface

AN Qi¹, SUO Shuangfu², LIN Fuyan¹, LI Yongjian², SHI Jianwen²

1. School of Mechanical Electronic & Information Engineering, China University of Mining & Technology(Beijing), Beijing 100083;
2. Department of Mechanical Engineering, Tsinghua University, Beijing 100084

Received:2019-03-22 Revised:2019-07-14 Online:2019-12-05 Published:2020-02-18

摘要/Abstract

摘要： 结合机床运动学与切削理论，对车削加工过程中表面形貌的影响因素进行了归类概括。基于复杂叠加信号解耦的思想，针对已加工成型的车削表面，采用频谱分析将形貌信号按照波长关系进行划分，得到加工因素对各波段信号幅值的影响规律。解决了直接分析多种加工因素耦合所引起考虑参数缺失与复杂信号分量叠加无法直接解耦的难题。针对相对精细的粗糙表面信号直接提取难度大的特点，按照加工表面粗糙度数值的大小，将粗糙表面划分为粗糙与精细两种类型。从幅值梯度较大，相对粗糙的加工表面形貌成分提取入手，得到各加工成分信息对实际形貌的影响规律。采用相应信号成分对各加工因素信号成分进行代替，实现粗糙表面形貌的提取与仿真。继而将分析得到的信号成分影响规律应用于相对精细粗糙表面信号的分析，最终实现从粗糙表面信号到精细表面信号成分的表征与解耦，为相对精细粗糙表面形貌的预测与仿真提供一种新的方法与思路。最后，结合表面信号特征提取的结果，实现了对车削粗糙表面形貌的仿真，为车削加工表面形貌的预测与车削粗糙表面接触分析提供了实用性的数字模型。

关键词: 车削加工, 表面形貌, 频谱分析, 幅值梯度, 特征解耦, 形貌仿真, 数字模型

Abstract: Combined with the kinematics and cutting theory of machine tools, the influencing factors of surface topography in turning process are classified and summarized. Based on the idea of decoupling complex and superimposed signals, the topography signal is divided according to the wavelength relationship by spectrum analysis. The influence of processing parameters on the signal amplitude of each wavelength band is obtained. It has solved the problem that direct analysis of the decoupling of many processing parameters causes missing of the parameters that must be considered and the complex adding of the signal components cannot be decoupled directly. In view of the difficulty of extracting relatively fine rough surface signals directly, machined surface is divided into two types:Rough surface and fine surface according to the roughness value. Starting with extracting the relatively rough surface, the influence rule of each processing component information on the actual topography is obtained. The corresponding signal components are used to replace the wavelet band signals respectively. According to this method, the relatively rough surface topography is obtained by simulation. Then the influence rule is applied to the analysis of relatively fine surface. The representation and decoupling of signal components from relatively rough surface to relatively fine surface is realized. The method presented provides a new approach for the prediction and simulation of relatively fine rough surface. Finally, the simulation of turning rough surface is realized by present method, which provides digital model for the prediction and contact analysis of turning rough surface.

Key words: turning machining, surface topography, spectrum analysis, amplitude gradient, signal decoupling, topography simulation, digital model

中图分类号:

TH123

安琪, 索双富, 林福严, 李永健, 时剑文. 车削粗糙表面的特征解耦与形貌仿真[J]. 机械工程学报, 2019, 55(23): 200-209.

AN Qi, SUO Shuangfu, LIN Fuyan, LI Yongjian, SHI Jianwen. Feature Decoupling and Shape Simulation of Turning Rough Surface[J]. Journal of Mechanical Engineering, 2019, 55(23): 200-209.

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车削粗糙表面的特征解耦与形貌仿真

Feature Decoupling and Shape Simulation of Turning Rough Surface

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