基于小波消噪的液压泵故障诊断

Study on Fault Diagnosis Based on Wavelet for Hydraulic Pump

针对液压泵出口故障检测信号信噪比低、难以进行故障特征提取的特点 ,采用小波分析进行消噪处理 ,利用具有紧支结构的小波函数进行分解和重构消除检测信号中的干扰成分 ,有效提取故障特征 ,从而实现液压泵配流盘偏磨故障及滑靴磨损故障的高效故障诊断。试验结果表明 ,小波包分析能够将信号进行多层次的划分 ,根据被分析的信号的特征 ,自适应地选择相应的频带 ,从而提高信号的时 -频分辨率 ,在时域和频域上有效突出故障信息 。

Directing to the dispersiveness and faintness of failure characteristics of hydraulic pump, this paper adopted wavelet analysis to cancel the interference existing in the measured signals and pick up the fault characteristics. Through decomposition and reconfiguration the measured signals with wavelet, it is easy to eliminate the noise and to strengthen the failure signals effectively. The experimental results indicate that the wavelet analysis can divide the signals into multi-frequency band when portplate and slipper wear occured among friction pairs in hydraulic pump. According to the signal characteristics,the frequency band was selected adaptively so as to promote the failure information, then the fault diagnosis was realized based on small SNR (Signal-to-Noise Rate) signals. The experimental results indicate that the method is feasible.