基于EMD的奇异值熵在转子系统故障诊断中的应用

提出了一种基于EMD（Empirlcal Mode Decomposition）和奇异值熵的转子系统故障诊断方法。该方法首先用EMD方法分解转子系统的振动信号，得到若干个基本内禀模式函数（Intrinsic Mode Function，简称IMF），然后利用IMF分量形成初始特征向量矩阵，并对初始特征向量矩阵求奇异值熵，奇异值熵的大小反映了转子系统运行状态的差别，从而可以通过奇异值熵的大小判断转子系统的工作状态和故障类型。对实验数据的分析结果证明了该方法的有效性。

Fault Diagnosis Approach for Rotor System Based on EMD Method and Singular value Entropy

A fault diagnosis approach for rotor system based on empirical mode decomposition (EMD) and singular value entropy is proposed. The rotor vibration signal is decomposed with EMD method into a number of intrinsic mode functions (IMFS), from which the initial feature vector matrixes are formed. By applying the singular value decomposition to the initial feature vector matrixes, the singular value entropy, whose value can demonstrate the differences among the rotor system operating states are obtained. The singular value entropy is used to identify the condition and fault pattern of a rotor system. Analysis results of the experimental data show that the proposed method can be applied to fault diagnosis for rotor system efficiently.