中文摘要：

航空发动机的转子系统扮演着重要的角色,如果在运行过程中出现预期之外的故障会造成严重的后果。为了预防这类事件,采用转子的振动信号作为目标信号,对振动信号进行智能基函数分析,采用支持向量机分类器测试所提取的智能特征。实验表明,该方案的分类精度达到95.6%,是针对航空发动机转子系统故障诊断的一种有效的特征提取方法。

英文摘要：

The rotor system of aircraft engine plays a vital role during flight, in which unexpected mechanical faults during operation can lead to severe consequences. We take the vibration signals of rotor system as the target signals and analyze the vibration signal by means of decomposition of intelligent basis functions. A support vector machine classifier is used to verify the extracted sparse features whether it is suitable. Experiments show that the total classification accuracy can reach 95.6%, and the method is an effective feature extraction method for aircraft engine rotor system.