Thermal error modeling of electric spindles based on cuckoo algorithm optimized Elman network

被引：0
|
作者：
Ye Dai
Xin Wang
Zhaolong Li
Sai He
Baolei Yu
Xingwen Zhou
机构：
[1] Harbin University of Science and Technology,Key Laboratory of Advanced Manufacturing Intelligent Technology of Ministry of Education
[2] Harbin University of Science and Technology,Institute of Digital Design and Automatic Machinery Product Development
来源：
The International Journal of Advanced Manufacturing Technology | 2024年 / 132卷
关键词：
Cuckoo algorithm; Elman neural network; Thermal displacement; Spearman rank correlation coefficient method; Thermal error modeling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In order to improve the accuracy of the thermal error model of the electric spindle, a thermal error modeling method based on the optimized Elman neural network using the cuckoo algorithm is proposed. To analyze the thermal behavior of the electric spindle, an ANSYS analysis approach is utilized to create a temperature map. Based on the simulation analysis outcomes, an experimental platform is established to gather temperature data and thermal displacement data. The electric spindle temperature is optimized through the utilization of fuzzy cluster analysis and the Spearman rank correlation coefficient method in combination. The comparison between the established model and the Elman model and the GA-Elman model proves that the CS-Elman model has good prediction accuracy and stability.
引用
收藏
页码：1365 / 1375
页数：10
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