关联维数分析方法在液压泵多故障诊断中的应用研究

针对液压泵故障信号非线性和非平稳性特征,提出了利用相空间重构技术和分形理论相结合的特征关联维数提取方法。该方法将液压泵不同故障模式下获取的一维振动信号重构到高维相空间,进行信息深层挖掘;通过对相空间特征信号关联维数变化规律的分析,找出对故障反映敏感的关联维数,由此进行故障识别。通过实验验证,该方法提取的关联维数能有效反映液压泵的故障特征,为液压泵多故障诊断方法的研究提供可靠的特征信息,具有良好的应用前景。

Feature Correlation Dimension Extraction Method for Hydraulic Pump Fault Diagnosis

Aimed at the nonlinear and non-stationary characteristics of the hydraulic pump fault vibration signals, the feature correlation dimension extraction method combined phase space reconstruction with fractal theory is proposed. The method reconstructs high-dimension phase space from one-dimension vibration signals of different fault states of the hydraulic pump so that deep data mining is achieved. Then through analysis of varying correlation dimension of phase space feature signals, feature correlation dimension (FCD) that corresponds to each fault state is extracted. The experiment shows that feature correlation dimension extracted by the method is effective to fault diagnosis of hydraulic pump. The method can provide reliable feature information for condition monitoring and fault diagnosis, and has a broad application prospect.