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基于多传感器信号的主轴回转误差在线回归预测方法研究

迟玉伦 宋卓阳 王国强 姚磊

计量学报2024,Vol.45Issue(9):1300-1313,14.
计量学报2024,Vol.45Issue(9):1300-1313,14.DOI:10.3969/j.issn.1000-1158.2024.09.07

基于多传感器信号的主轴回转误差在线回归预测方法研究

Study on Regression Prediction Method of Multi Signal Spindle PSO-SVM Rotation Error Based on LMD

迟玉伦 1宋卓阳 1王国强 1姚磊1

作者信息

  • 1. 上海理工大学机械工程学院,上海 200093
  • 折叠

摘要

Abstract

By analyzing the formation mechanism of spindle rotation errors,regression forecasting model of spindle rotation errors which based on multi-sensor signal was built.Firstly,the LMD method and Pearson correlation coefficient method were used to extract feature values and optimize dimensionality reduction for the vibration signals,current signals,and acoustic emission signals of the front bearing,which solve the problem that types of original signals used in prediction of spindle rotation error of CNC machine tools were too single.Secondly,aiming at the nonlinear problems between various monitoring signals and rotation errors of the machine tool spindle,the RBF kernel function was used to achieve nonlinear prediction under multiple inputs and find complex relationships between datas.However,to establish RBF kernel function,the effective determination of width coefficient σ,penalty factor C and insensitive loss coefficient ε was a challenge in the model.Therefore,a support vector machine model based on particle swarm optimization algorithm was established to predict the spindle rotation errors.Once again,to evaluate the effectiveness of the model,a regression prediction model evaluation method for spindle rotation error based on mean square error,mean absolute error and coefficient of determination was proposed.Finally,experimental research was conducted on above prediction model in the i5m4 CNC machining center.The results showed that the mean square error of PSO-SVM regression prediction model was 0.19%,the average absolute error was 4.58%,the coefficient of determination was 0.923 7.Compared with the model before optimization,the PSO-SVM regression forecasting model can predict the spindle rotation errors accurately and effectively.

关键词

几何量计量/主轴回转误差/多传感器信号/PSO-SVM/LMD/皮尔森相关系数

Key words

geometric measurement/spindle rotation error/multi signal/PSO-SVM/LMD/PCA

引用本文复制引用

迟玉伦,宋卓阳,王国强,姚磊..基于多传感器信号的主轴回转误差在线回归预测方法研究[J].计量学报,2024,45(9):1300-1313,14.

基金项目

国家自然科学基金(51605294) (51605294)

计量学报

OA北大核心CSTPCD

1000-1158

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