农业机械学报2017，Vol.48Issue(3)：390-395,6.DOI:10.6041/j.issn.1000-1298.2017.03.050
基于多元混沌时间序列的数控机床运动精度预测
Prediction of Numerical Control Machine's Motion Precision Based on Multivariate Chaotic Time Series
摘要
Abstract
In order to solve the problem that information could be easily lost in the phase space constructed by the unit precision time series with finite length or containing noises,the method of predicting numerical control machine's motion precision was put forward based on multivariate chaotic time series.Firstly,multiple characteristic quantity of motion precision were extracted from CNC machine tool.Delay time and embedding dimension of the multiple motion precision time series were worked out by the C-C algorithm.The low-dimensional sequences were mapped to high-dimensional space to establish a multi-precision state space by phase reconstruction of multivariate time series.The phase space established was the same topological isomorphism with the original system.The state space points' track was described motion precision's evolution in multivariate phase space.Then the principal component analysis was used to reduce dimensions of high dimensional phase space and remove redundant information.Finally,the state vector of the phase space was taken as a multi-dimensional input.The predicting model of wavelet neural network could be trained by the information constructed to achieve the motion precision prediction.The experiments results showed that the proposed method could well analyze the changing regulation of NC machine tools motion precision and the mean square error of prediction model was 0.009 5.Compared with the way of prediction by the unit chaotic time series,it had better predictive effects,and its adaptability and practicality were stronger.关键词
数控机床/运动精度/混沌/多元时间序列/预测Key words
CNC machine tool/motion precision/chaos/multivariate time series/prediction分类
机械制造引用本文复制引用
杜柳青,曾翠兰,余永维..基于多元混沌时间序列的数控机床运动精度预测[J].农业机械学报,2017,48(3):390-395,6.基金项目
国家自然科学基金项目(51305476) （51305476）
