基于单节点重构改进小波包能量与包络谱的滚动轴承故障特征提取

FAULT FEATURE EXTRACTION OF ROLLING BEARING BASED ON SINGLE NODE RECONSTRUCTION WAVELET PACKET ENERGY AND ENVELOPE SPECTRUM

针对滚动轴承故障特征提取困难问题,采用单节点重构改进小波包能量与包络谱结合的方法,有效提取出各个不同部位的故障特征。对所采集到的故障信息进行三层改进后的小波包分解重构,计算各个重构节点的能量,并以此来确定包含故障特征信息的节点。对包含故障特征信息的节点进行Hilbert变换求取其包络谱,将其进行细化,读取特征频率,识别故障特征,判别故障类型,实现滚动轴承故障的诊断和定位。并通过仿真信号和滚动轴承故障特征的提取实验证明了该方法的有效性。

Aiming at difficult problems of rolling bearing fault feature extraction,combine single node reconstruction wavelet packet energy and envelope spectrum, we extracted the faulty features of different parts effectively. We decomposed and reconstructed the fault information collected after three-layer of improvement. And we calculated the energy of each reconstruction node to determine the node which contained the fault signature information,using envelope spectrum to hand the node that contains fault feature information,reading the failure frequency,realizing the diagnosis and localization of rolling bearing fault. The effectiveness of this method is proved by the extraction experiments of the simulation signal and rolling bearing fault characteristics.