基于随机森林算法的行星滚柱丝杠副摩擦力矩预测

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关键词：行星滚柱丝杠；摩擦力矩；机器学习；随机森林算法

中图分类号：TH132

DOI：10.3969/j.issn.1004-132X.2025.07.013 开放科学（资源服务）标识码（OSID）：

Prediction of Frictional Torques of Planetary Roller Screw Pairs Based on Random Forest Algorithm

XU Yang ZU Li*LI Weilong LIU Xiaoling HE Jianliang LIU Jun of Mechanical Engineering，Nanjing University of Science and Technology，Nanjing，210094

Abstract： The increase in frictional torques of planetary roller screw pairs led increased wear of planetary roller screw mechanisms（PRSM），which seriously affected the use and service life of PRSM. The feasibility of using ML algorithms to predict the frictional torques of PRSM was explored，and the relationship between PRSM frictional torques and wear states was analyzed. Random forest algorithm，support vector regression，and BP neural network were used to predict the changes in frictional torques of PRSM at different rotational speeds.The results demonstrate that the random forest algorithm achieves the prediction accuracy of 97% for the frictional torques of PRSM.

Key words： planetary rollr screw; frictional moment；machine learning（ML） ; random forest algorithm

0 引言

行星滚柱丝杠副（planetaryrollerscrewmechanism，PRSM）主要由丝杠、滚柱、螺母等部件组成，其中，丝杠、滚柱、螺母构成丝杠-滚柱副和螺母-滚柱副。（剩余12756字）