AVMD及其在滚动轴承早期故障诊断中的应用

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关键词：滚动轴承；早期故障；自适应变分模态分解；故障冲击度量指标；鹦鹉算法 中图分类号：TH133.3 文献标志码：A DOI：10.16385/j.cnki.issn.1004-4523.202404069

Abstract：Aiingatteprobtatitisdifiulttoauratelextractthicipietfultfeaturesoflingbarng，anicitfault diagnosismethodbasedonadaptivevariationalmodedecomposition（AVMD）isproposed.Anewfaultimpactmeasureindex（FMl）is established toguidethemulti-trategyimprovedparrotoptimizer（IPO）toadaptivelyotaintheoptimalparametercombination [K，α] of variationalmodedecomposition（VMD），soastorealizetheaccuratedecompositionoffaultsignal.Teprincipalfaultcharacteristic componentis extractedbasedontheFMmaximzationcriterionTefaultcomponentundergoes enhancedenvelopespectrumprocesingto identifythefaulttype.Numealsimulatiosndexperimentaldataconfiemetod’sfectivenssadfeasiblityfriciifault diagnosis ofrolling bearings，showcasing its superiority over existing techniques.

Keywords：rolingbarings;incipientfault;adaptivearationalmodedecomposition;fault-mpactmeasureindex;parototizer

滚动轴承因其摩擦力矩低、功耗小等优点，已成为目前旋转机械中最主要的零部件之一，在能源电力、航天航空、交通运输等机械领域得到了广泛应用，但同时也是故障率较高的零部件[1]。（剩余18890字）