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首页> 外文会议>International Conference on Fluid Power Transmission and Control(ICFP' 2005); 20050405-08; Hangzhou(CN) >Application of Wavelet Analysis and Fractal Geometry for Fault Diagnosis of Hydraulic Pump
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Application of Wavelet Analysis and Fractal Geometry for Fault Diagnosis of Hydraulic Pump

机译：小波分析和分形几何在液压泵故障诊断中的应用

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摘要

In this paper, the method of wavelet analysis and fractal dimension calculation is firstly applied in diagnosis of hydraulic pump with shoe-doffing fault. In recent years, fractal dimension is studied by some researchers and is applied in many fields. But some research has shown that the correlation dimension is easily affected by noise. So in this paper the wavelet analysis is applied in the noise elimination of pressure signal. The initial pressure signal is decomposed, noise eliminated, and reconstructed by use of the wavelet analysis method through selecting wavelet function Daubechies 5. The fault characteristic frequency is extracted correctly in its corresponding high frequency coefficient. Then the correlation dimension of the noise-eliminated data is calculated with the G-P algorithm. When the pump outlet pressure is 3MPa, the correlation dimension of signal in normal condition is 1.68, while in fault condition it is 1.35. The result shows that the correlation dimension of signal in fault state is lower than that in normal state. The combination of wavelet and fractal technology can give us an effective method in condition monitoring and fault diagnosis of equipments.
机译：本文首先将小波分析和分形维数的计算方法应用于滑靴故障的液压泵诊断中。近年来，一些研究人员研究了分形维数，并将其应用于许多领域。但是一些研究表明，相关维很容易受到噪声的影响。因此本文将小波分析应用于压力信号的噪声消除。通过选择小波函数Daubechies 5，使用小波分析方法对初始压力信号进行分解，消除噪声并进行重构。正确提取故障特征频率的相应高频系数。然后，使用G-P算法计算消噪数据的相关维。当泵出口压力为3MPa时，正常情况下信号的相关维数为1.68，而在故障情况下为1.35。结果表明，故障状态信号的相关维数低于正常状态。小波与分形技术相结合可以为设备状态监测和故障诊断提供有效的手段。

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