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基于PSO-BP的超越离合器磨损预测算法

周龙 李乐 王立勇

北京信息科技大学学报(自然科学版)2026,Vol.41Issue(1):69-79,11.
北京信息科技大学学报(自然科学版)2026,Vol.41Issue(1):69-79,11.DOI:10.16508/j.cnki.11-5866/n.2026.01.008

基于PSO-BP的超越离合器磨损预测算法

Overrunning clutch wear prediction algorithm based on PSO-BP

周龙 1李乐 1王立勇1

作者信息

  • 1. 北京信息科技大学机电工程学院,北京 100192
  • 折叠

摘要

Abstract

In order to improve the evaluation accuracy of the wear state of the key components of the overrunning clutch,an overrunning clutch wear prediction algorithm based on particle swarm optimization-back propagation(PSO-BP)was proposed.Firstly,a wear finite element model was established based on the ABAQUS finite element simulation platform by combining the Archard wear criterion and introducing the user subroutine UMESHMOTION.By mapping the wear amount to the displacement of the grid nodes,the geometric boundary evolution of the material removal effect and the dynamic update of the wear depth were realized,and the accuracy of the model was verified by experiments.Secondly,on this basis,the key parameters such as cumulative slip distance,instantaneous slip distance,and contact stress were further extracted as inputs,and the wear depth was used as output to construct a PSO-BP prediction model,realizing high-precision prediction of the wear depth of the contact area between the wedge and the inner ring.Comparative analysis shows that,compared with the traditional BP neural network and the GA-BP neural network,the PSO-BP model achieves a fitting accuracy of 99.838%,and its prediction error is more concentrated in the zero error region,reflecting a higher accuracy.

关键词

超越离合器/磨损深度/有限元分析/磨损预测

Key words

overrunning clutch/wear depth/finite element analysis/wear prediction

分类

机械制造

引用本文复制引用

周龙,李乐,王立勇..基于PSO-BP的超越离合器磨损预测算法[J].北京信息科技大学学报(自然科学版),2026,41(1):69-79,11.

基金项目

国家自然科学基金项目(52175074) (52175074)

北京信息科技大学学报(自然科学版)

1674-6864

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