基于Hilbert-Huang变换的发动机振动信号特征提取

基于Hilbert-Huang变换与小波分析相结合的故障特征提取方法,先利用小波分析方法将缸盖振动分解在低、中、高三个频段,然后对各个频段的信号进行EMD分解,对得到的IMF分量做Hilbert变换,得到各个频段的Hilbert谱.再根据发动机冲击响应的特点,将Hilbert谱沿频率轴积分,然后在时间-幅值平面上投影成二维的频带能量分布图,突出故障信息.实例表明,通过各频段、各冲击响应能量分布的变化,可实现故障的判断和定位.

Feature Extraction from Vibration Signals of Engine Based on Hilbert-Huang Transformation

HHT (Hilbert-Huang Transformation) was combined with wavelet analysis as a method of feature extraction. Cylinder head 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). Then Hilbert spectrum of signal in each frequency band was obtained by HHT. According to characteristics of impulse response in vibration signal of engine, energy integration along frequency axes was projected to the time-amplitude plan. An example of practical application shows that faults can be judged and located through different energy distribution of each frequency band and impulse response.