China Mechanical Engineering ›› 2022, Vol. 33 ›› Issue (16): 1891-1896.DOI: 10.3969/j.issn.1004-132X.2022.16.001

Previous Articles     Next Articles

Establishment and Research of Prediction Model of Discharge Gap Voltages in Discharge Arc Milling

ZHANG Jin1,2;HAN Fuzhu1,2   

  1. 1.Department of Mechanical Engineering,Tsinghua University,Beijing,100084
    2.Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipment and Control,Tsinghua University,Beijing,100084
  • Online:2022-08-25 Published:2022-09-08

电弧铣削加工间隙电压预测模型的建立与研究

张瑾1,2;韩福柱1,2   

  1. 1.清华大学机械工程系,北京,100084
    2.清华大学精密/超精密制造装备和控制北京市重点实验室,北京,100084
  • 通讯作者: 韩福柱(通信作者),男,1966年生,教授、博士研究生导师。研究方向为精密特种加工、水导激光等。E-mail:hanfuzhu@mail.tsinghua.edu.cn。
  • 作者简介:张瑾,女,1994年生,博士研究生。研究方向为电弧铣削加工。E-mail:zhangjin17@mails.tsinghua.edu.cn。
  • 基金资助:
    装备预先研究领域基金(6140923030701)

Abstract: It was difficult to directly measure the discharge gaps during arc milling. The changes of the discharge gaps were judged by the changes of the discharge gap voltages. The system identification theory was used to determine the structure and model parameters of the discharge gap voltage prediction model. The method for establishing the prediction model was elaborated, and the degree of fit of the prediction model was verified by experiments. The experimental results show that the fit accuracy of the prediction model decreases with the increase of the fitting time. Therefore, the recursive least squares method was used to perform the online discharge gap voltage measurements. It is predicted that the average error of online prediction is as 6.82%. The results show that the discharge gap voltage prediction model may predict the discharge gap voltage stably and effectively one step ahead, with fewer model identification parameters and high prediction accuracy.

Key words:  , discharge arc milling, discharge gap, prediction model, system identification

摘要: 针对电弧铣削加工过程中极间间隙难以直接测量的问题,通过极间间隙电压的变化判断极间间隙的变化,采用系统辨识理论确定间隙电压预测模型的结构和模型参数,对该预测模型的建立方法进行了详细阐述,对预测模型的拟合程度进行了实验验证。实验结果表明,预测模型的拟合精度随着拟合时间的延长而降低,因此,采用递推最小二乘方法进行间隙电压的在线预测,在线预测的平均误差为6.82%,结果表明所建模型能够稳定、有效地超前一步预测间隙电压,并且模型在线辨识的参数少,模型预测的精度高。

关键词: 电弧铣削加工, 放电间隙, 预测模型, 系统辨识

CLC Number: