基于小波降噪和EMD方法的风力发电系统齿轮箱故障诊断  

Wind Turbine Gearbox Fault Diagnosis Based on Wavelet De-Noising and EMD

作　　者：王龙[1] 沈艳霞[1] 季凌燕[1] 

机构地区：[1]江南大学电气自动化研究所,江苏无锡214122

出　　处：《江南大学学报（自然科学版）》2012年第2期159-162,共4页Joural of Jiangnan University (Natural Science Edition)　

基　　金：国家自然科学基金项目(61104183);教育部新世纪优秀人才支持计划项目(NCET-10-0437)

摘　　要：将小波降噪和经验模态分解相结合,提出一种风电机组齿轮箱故障诊断的方法。先对齿轮故障振动信号进行小波降噪预处理,再进行经验模态分解,对包含故障特征的固有模态函数用Hilbert变换得到包络谱,通过对包络信号做功率谱分析,提取故障特征频率,与未降噪信号处理的结果进行比较,降噪后诊断效果明显。A method combining wavelet and empirical mode decomposition was proposed for the fault diagnosis of wind turbine gearbox.The vibration signal was first de-noised using wavelet,and then EMD was applied.The envelope spectrum of IMF that contained fault characteristic frequencies was obtained using Hilbert transform,then the power spectrum of the envelope was computed,and the fault characteristic frequencies were extracted.The improvements were illustrated by comparing with those without wavelet de-nosing.

关 键 词：小波降噪 经验模态分解 风电齿轮箱 故障诊断 

分 类 号：TM614[电气工程—电力系统及自动化] TH165.3[机械工程—机械制造及自动化]