两种工况下电主轴热误差的组合预测模型

雷春丽 1; 芮执元 1; 刘军 1; 2; 冯瑞成 1; 2

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两种工况下电主轴热误差的组合预测模型

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- 两种工况下电主轴热误差的组合预测模型
- Thermal Error Combined Forecasting Model on Motorized Spindle under Two Operating Conditions
- 西安交通大学学报 2011年45卷第7期页码：50-54
- 作者机构：
  
  1. 兰州理工大学数字制造技术与应用省部共建教育部重点实验室,兰州,730050
  2. 兰州理工大学机电工程学院,兰州,730050
- 作者简介：
- 基金信息：
  
  : 2011-01-17. 作者简介: 雷春丽(1977-),女,讲师. 基金项目: 国家科技重大专项基金资助项目(2009ZX04001-015);甘肃省自然科学基金资助项目(1010RJZA043)
- DOI：
  中图分类号： TG659
- 网络首发：2011-07-10，
  
  纸质出版：2011
- 稿件说明：
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雷春丽 1, 芮执元 1, 刘军 1, 等. 两种工况下电主轴热误差的组合预测模型[J]. 西安交通大学学报, 2011,45(7):50-54.

Thermal Error Combined Forecasting Model on Motorized Spindle under Two Operating Conditions[J]. 2011, 45(7): 50-54.
雷春丽 1, 芮执元 1, 刘军 1, 等. 两种工况下电主轴热误差的组合预测模型[J]. 西安交通大学学报, 2011,45(7):50-54. DOI：

Thermal Error Combined Forecasting Model on Motorized Spindle under Two Operating Conditions[J]. 2011, 45(7): 50-54. DOI：

摘要

为了有效地提高数控机床电主轴热变形模型的预测精度

在2种典型工况下

根据电主轴结构热变形的产生机理

提出了一种基于模糊逻辑的组合预测模型.该模型综合了由自回归分析理论和灰色系统预测理论所建立的热误差模型

采用模糊逻辑选取权值

使各单项预测模型能够扬长避短

从而增强了组合预测模型的泛化能力.通过对电主轴热变形工况下的实验结果与计算结果的比较表明

在单项预测模型中的工况1下

灰色系统预测模型的相对误差较小(6.9%)

在工况2下

自回归预测模型的相对误差较小(12.1%)

而组合预测模型在2种工况下的相对误差分别为2.2%和8.9%.因此

组合预测模型具有较高的精度和较强的鲁棒性.

Abstract

According to the generation mechanism of motorized spindle thermal deformation

the combined forecasting model based on the fuzzy logic is proposed under two typical working conditions. The model can be expected to improve the forecasting accuracy by autoregressive analysis and grey system theory combined with different weight. The combined model synthetically employs the above methods and makes the best use of each of them. The experimental results show that under the two operating conditions

the smaller relative error in single forecasting model is 6.9% and 12.1% respectively

however

the relative prediction error of combined model is respectively 2.2% and 8.9%

which demonstrates the higher precision and stronger robust of the intelligence combination forecasting model.

关键词

Keywords

references

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