基于信号经验模态分解与分集合并的齿轮故障诊断  

Gear fault diagnosis based on Empirical Mode Decomposition and Signal diversity merging

作　　者：邓博元 崔伟成 曾庆松 李晨 DENG Boyuan;CUI Weicheng;ZENG Qingsong;LI Chenxuan(Naval Aviation University,Yantai 264001,China)

机构地区：[1]海军航空大学,山东烟台264001

出　　处：《计算机测量与控制》2021年第9期43-49,共7页Computer Measurement &Control

摘　　要：为了准确地进行齿轮故障诊断,结合信号经验模态分解与分集合并,提出了一种新的故障诊断方法;首先,运用经验模态分解对齿轮振动信号进行分解得到若干个分量;其次,根据分量的峭度大小以及相邻分量的峭度是否接近,筛选、合成有效分量;然后,运用等增益分集合并技术对有效分量进行合并,即将其包络进行叠加;接着,使用快速傅立叶变换得到信号包络和的频率谱;最后,根据该频率谱进行故障诊断;通过对仿真信号和齿轮断齿故障振动信号的分析,验证了方法的有效性。In order to accurately diagnose gear faults,a new fault diagnosis method is proposed by combining signal empirical mode decomposition and diversity combination.First,use empirical mode decomposition to decompose the gear vibration signal to obtain several components;secondly,filter and synthesize effective components according to the kurtosis of the components and whether the kurtosis of adjacent components are close;then,use equal gain diversity combining technology add the signal envelopes of the effective components;then,use the fast Fourier transform to obtain the envelope and the frequency spectrum of the signal;finally,perform fault diagnosis based on the frequency spectrum.The effectiveness of the method is verified by analyzing the simulation signal and the vibration signal of the gear broken tooth fault.

关 键 词：齿轮故障诊断 经验模态分解 信号分集 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]