小波包能量谱和功率谱分析在水电机组故障诊断中的应用

小波包克服了小波分析在高频空间分辨率差的缺点,能够给信号提供更加精确的分解。因此在小波包分析的基础上,从能量和功率分析的角度出发,阐述了在水电机组故障诊断中采用小波包能量谱和功率谱分析相结合的信号特征提取的方法。通过对实验及电厂振动故障信号的提取与分析,表明小波包能量谱和功率谱分析相结合的信号特征提取方法准确而高效,是一种应用价值较高的信号特征提取方法,并能为机组故障的准确诊断提供依据。

Analysis of wavelet packet energy spectrum and power spectrum and its application to fault diagnosis of hydropower units

Wavelet packet analysis overcomes the shortcoming of wavelet analysis in poor resolution of high frequency band, thus providing a more accurate decomposition of signals. Basis on this analysis, a method for signal feature extraction is described for fault diagnosis of hydropower units, which combines wavelet packet energy spectrum with power spectrum analysis. Extraction and analysis of the in-situ test data and vibration fault signal at a hydropower station shows that this extraction method is accurate and efficient. It is a method of high application value and would lie a basis for accurate unit fault diagnosis.