中南大学学报（自然科学版）2016，Vol.47Issue(12)：4027-4033,7.DOI:10.11817/j.issn.1672-7207.2016.12.010
基于GM-LS-SVM层级模型的数控机床热误差建模
CNC machine tool thermal error modeling based on GM-LS-SVM hierarchical model
摘要
Abstract
In order to predict and compensate thermal error of CNC (computer numerical control) machine tools more accurately, and to make up the shortcomings of single use of grey model (GM) or least squares support vector machine (LS-SVM) model, a hierarchical model (GM-LS-SVM) combining the data processing merits of GM with that of LS-SVM was proposed for thermal error modeling in machine tools. According to the temperature data and thermal error data of the machine tool, first several thermal error GMs with different data sequence length were established as preprocessing layer, and then the preprocessed thermal errors of preprocessing layer and the measured thermal errors were used as input and output of LS-SVM model respectively, to correct prediction accuracy. A modeling experiment was carried out on a precision horizontal machining center, and the prediction accuracies were compared among the proposed GM-LS-SVM hierarchical model, GM, LS-SVM model and BP neural network. The results show that the proposed GM-LS-SVM hierarchical model has higher prediction accuracy and better generalization ability than the other three models in CNC machine tools’ thermal error modeling.关键词
数控机床/热误差建模/灰色模型/最小二乘支持向量机/BP神经网络Key words
CNC machine tool/thermal error modeling/grey model/least squares support vector machine/BP neural network分类
机械制造引用本文复制引用
谭峰,殷国富,殷勤,董冠华,王亮..基于GM-LS-SVM层级模型的数控机床热误差建模[J].中南大学学报（自然科学版）,2016,47(12):4027-4033,7.基金项目
国家科技重大专项项目(2013ZX04005-012)(Project(2013ZX04005-012) supported by the National Science and Technology Major Project of China) （2013ZX04005-012）
