小波包分析在汽轮机转子振动故障诊断中的应用

Wavelet Packet Analysis for Vibration Fault Diagnosis of Turbine Rotor

针对汽轮发电机组振动的频谱特点,提出了基于小波包变换的汽轮机转子振动故障诊断方法,它较一般的小波变换更能反映振动信号所包含的频谱成分及能量。根据Bently实验台所采集的4种典型汽轮机转子振动故障信号,运用小波包分析方法对其进行能量分析并提取故障特征。实验分析表明,基于小波包分析与信号能量分解的故障特征提取方法,可以获得汽轮机转子振动的故障状况;根据不同故障发生时的频谱特征,识别出不同的故障,从而进行汽轮机转子振动故障诊断。该方法比基于Fourier变换的故障特征提取方法更有效,适合于机械故障诊断。

A fault diagnosis method based on wavelet packet analysis for turbine rotor vibration has been put forward according to the vibration frequency spectrum characteristics of turbo-generator units. It can reflect the frequency spectrum ingredients and energy contained in vibration signals more exactly than wavelet transformation. Based on the four typical fault signals of turbine rotor vibration collected from the Bently experiment set, energy analysis and symptom extraction are carried out by wavelet packet analysis. The experimental analysis indicates that the conditions of turbine rotor vibration faults can be obtained by the extraction method of mechanical fault symptoms based on wavelet packet analysis and signal energy decomposition. According to the character in both the time domain and the frequency domain of faults, the fault types can be identified, and then the turbine rotor vibration faults can be diagnosed. This method is more effective than the extraction method of fault symptoms based on the Fourier transformation, and it is fit for mechanical fault diagnosis.