摘要
文章描述了基于振动信号的Morlet小波变换和HHT(Hilbert-Huang变换)齿轮故障信息提取方法,并分别用来对四类齿轮进行故障信息提取,得到各状态齿轮振动信号的Morlet小波谱和Hilbert谱。实验研究表明:Morlet小波变换和HHT都可用于齿轮故障信息提取,但Hilbert谱分析比Morlet小波谱分析在时间和频率域都有较高的分辨率,且HHT比Morlet小波变换有更高的计算效率,更适用于故障信号微弱、振动信号数据量大的齿轮故障信息提取。
Morlet wavelet transform and HHT（Hilbert-Huang Transform） based on vibration signal were described in this paper as gear fault information extraction method,then they were used to extract four kinds of gear fault information,and Morlet wavelet spectrum and Hilbert spectrum of gear vibration signal were obtained.Studies showed that both Morlet wavelet transform and HHT can be used for gear fault information extraction,but Hilbert spectrum analysis had higher resolution than Morlet wavelet spectrum analysis in both time and frequency domain,and HHT had higher computational efficiency than Morlet wavelet transform,so HHT was more suitable for gear fault information extraction with weak vibration signal and large quantity of vibration data.
出处
《组合机床与自动化加工技术》
北大核心
2012年第6期35-37,41,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
863基金项目(2012AA06A406)
