机械科学与技术2025，Vol.44Issue(9)：1522-1529,8.DOI:10.13433/j.cnki.1003-8728.20230226
一种北方苍鹰参数优化的VMD-MRE轴承故障诊断方法
A VMD-MRE Bearing Fault Diagnosis Method with Northern Goshawk Parameter Optimization
摘要
Abstract
Aiming at the problem of difficult parameter selection in bearing fault diagnosis by variational modal decomposition(VMD),a method based on the northern goshawk optimization(NGO)algorithm to optimize the VMD parameters is proposed in this paper.Firstly,after using the NGO optimization algorithm to find the optimal number of decomposition layers and penalty factors of the VMD decomposition,the optimal parameters are input into the VMD to decompose the fault signal to obtain the specified number of intrinsic mode function(IMF).Secondly,the multi-scale ranger entropy(MRE)feature extraction method is used to extract features from the decomposed IMF of VMD to form a series of feature sample sets for better fault classification.Finally,the fault diagnosis of the feature-extracted data set is performed by a fault classification model,and the effectiveness of the proposed method is illustrated by experimental results.关键词
北方苍鹰算法/变分模态分解/多尺度极差熵/特征提取/故障诊断Key words
northern goshawk optimization/variational modal decomposition/multiscale ranger entropy/feature extraction/fault diagnosis分类
机械制造引用本文复制引用
章涛,陈勇旗,廖紫洋,陈杨..一种北方苍鹰参数优化的VMD-MRE轴承故障诊断方法[J].机械科学与技术,2025,44(9):1522-1529,8.基金项目
浙江省自然科学基金项目(Y16E050003) （Y16E050003）
