摘要
针对旋转设备局部碰摩故障振动信号的特征,提出了一种基于经验模式分解(Emp iricalMode Decomposition,EMD)与小波分析相结合的故障特征提取的改进方法,先利用小波分析方法将振动信号分解为低、中、高3个频段,然后对各个频段的信号进行EMD分解,实现碰摩、背景和噪声信号分离,从而提取旋转设备局部碰摩振动信号的故障特征。在某热电厂2号汽轮发电备用机组的碰摩故障诊断的应用中,仿真信号和试验数据的分析结果表明,该方法正确、有效,可应用于工程实践。
Aimed at the characteristics of the vibration signal of rotating machinery with local rub-impact fault, A novel impulse identification a improved method of feature extraction based empirical mode decomposition （EMD） and wavelt analysis is proposed. Vibration signal was decomposed and restructured in low, middle and high frequency bands by wavelet. Signal in each frequency band was divided into some IMFS （Intrinsic Mode Function） by EMD（ Empirical Mode Decomposition）. The rub-impact, background and noise signal can be separated efficiently and the fault feature of vibration signal of rotating machinery with local rub-impact fault can be extracted. And this method can be applied in the steam turbogenerator set of certain thermoelectricity factory. Simulations and experiments verified that the proposed methods are accurate and efficient and can be applied in engineering practice effectively.
出处
《汽轮机技术》
北大核心
2008年第4期289-291,295,共4页
Turbine Technology
