机械制造与自动化2025，Vol.54Issue(3)：77-81,5.DOI:10.19344/j.cnki.issn1671-5276.2025.03.015
基于POA-VMD与综合筛选指标的轴承故障诊断
Bearing Fault Diagnosing Based on POA-VMD and Comprehensive Screening Index
摘要
Abstract
In order to diagnose coal mine bearing with more accuracy,the bearing fault diagnosis method based on POA-VMD and comprehensive screening index is proposed.Aimed at the two parameters K and α which have great influence on decomposition effect in VMD,the bugs leading to the poor decomposition effect of vibration signal are sought out by experience.The POA algorithm is used to automatically optimize the K and α,obtaining the two optimal parameter combination of the maximized VMD decomposition performance,and the POA-VMD is applied to decompose the bearing vibration signal.Regarding the poor accurate fault feature extraction caused by the selection of components based on a single index,the optimal component after decomposition is determined with the comprehensive screening indexes of inter connection,kurtosis and relative entropy.And the Hilbert method is used to process the optimal component,extract the fault features and realize the bearing fault diagnosis.The experimental results show that the bearing fault diagnosis method based on POA-VMD and comprehensive screening index,in comparison with the conventional VMD method and the single index selection component one,has better fault diagnosis effect.关键词
POA/VMD/轴承/故障诊断Key words
POA/VMD/bearing/fault diagnosis分类
机械制造引用本文复制引用
刘永亮..基于POA-VMD与综合筛选指标的轴承故障诊断[J].机械制造与自动化,2025,54(3):77-81,5.基金项目
国家发改委基金项目(CCTC30211636) （CCTC30211636）
安标国家矿用产品安全标志中心科技创新基金项目(2019ZL004,2019ZL005) （2019ZL004,2019ZL005）
