湖北文理学院学报2025，Vol.46Issue(2)：23-28,6.
基于ILSO-BP神经网络的数控机床主轴热误差建模
Modeling of Spindle Thermal Error of CNC Machine Tool Based on ILSO-BP Neural Network
摘要
Abstract
In order to improve the machining accuracy of CNC machine tools,a BP neural network thermal error model based on Improved Lion Swarm Optimization Algorithm(ILSO)was proposed,taking the spindle system of Jiashite S7H CNC machine tool as the research object.By using the improved K-means clustering analysis and correlation analysis method based on genetic algorithm,the number of temperature measurement points was reduced from 10 to 5.Combining the optimization ability of ILSO algorithm and the advantages of BP neural network,an ILSO-BP mathematical model was established in the Z-axis direction.Through comparative experiments with traditional BP neural network and LSSVM model,the results showed that the ILSO-BP model has advantages such as high accuracy and strong robustness.关键词
数控机床/主轴热误差/BP神经网络/狮群优化算法Key words
CNC machine tools/spindle thermal error/BP neural network/Lion Swarm Optimization Algorithm分类
金属材料引用本文复制引用
薛东,袁鑫,王新科,刘宏伟..基于ILSO-BP神经网络的数控机床主轴热误差建模[J].湖北文理学院学报,2025,46(2):23-28,6.基金项目
湖北文理学院科研基金项目(2024pygpzk06) （2024pygpzk06）
