基于小波包分析的液压泵状态监测方法

Wavelet Packets Analysis Based Method for Hydraulic Pump Condition Monitoring

液压泵是液压系统中的关键部件,对其运行状态的监测与故障诊断对整个液压系统的可靠性具有重要意义。基于小波包分解和小波系数残差分析方法,提出一种利用液压泵出口压力进行液压泵故障诊断的方法。通过分析液压泵出口处压力信号的特征,利用小波包对压力信号进行频谱分解,提取液压泵的故障特征,建立不同频率范围的特征信号与液压泵不同故障因素的对应关系,为液压泵的故障诊断与定位提供依据。利用小波包能量残差判别液压泵的运行健康状态,并比较不同小波基函数在故障诊断时的敏感度。为减小小波分析时边界效应所引起的信号畸变,引入"滑动双窗口"的分析方法。试验结果表明,与快速傅里叶方法相比,基于小波包分解的残差分析方法可有效提高故障诊断的准确率,实现对液压泵的状态监测与故障诊断。

The hydraulic pump is a key component in hydraulic system. Monitoring its operation state and carrying out fault diagnosis are of important significance to the reliability of the whole hydraulic system. Based on the wavelet packet decomposition （WPD） and wavelet coefficients residual analysis method, the fault diagnosis approach by employing the outlet pressure of the pump is proposed for the condition monitoring of hydraulic pump. By analyzing the characteristic of the discharge pressure of the hydraulic pump, the wavelet packet analysis is applied to the pressure signal to extract the feature spectrum of the hydraulic pump. The relationships of the feature signals in different frequency bands corresponding to the different fault factors are established. The wavelet packet energy residuals are then used to diagnose the pump health status. The sensitivities of the fault diagnosis with different wavelet function are also discussed. For eliminating the border distortions in WPD, a twin sliding window scheme is created to improve the performance of the diagnosing system. The validating test results show that this WPD and residual analysis based method can effectively improve the accuracy of fault diagnosis in comparison to the conventional fast Fourier transform （FFT） method.