中文摘要：

提出了一种基于EMD和关联维数的转子系统故障诊断方法。该方法用EMD将转子系统振动信号分解成若干个基本模式分量IMF，对包含主要故障信息的IMF分量建立AR模型，AR模型自回归参数的关联雏数作为特征量神经网络识别转子系统的工作状态和故障类型。对实验数据分析的结果表明，该方法能有效地应用于转子系统的故障诊断。

英文摘要：

A fault diagnosis approach for rotor systems based on correlation dimension is proposed. The EMD method is used to decompose the rotor vibration signal into several intrinsic mode functions （IMFs）. The AR models of some IMF components which contain main fault information are constructed. Finally, the correlation dimensions of auto-regressive parameters in AR model are calculated and input into the neural network as feature vectors. The working state and fault pattern of the rotor system can be identified by the neural network. The analysis results of the experimental data show that the proposed approach can be applied to the fault diagnosis for rotor system efficiently.