中文摘要：

针对齿轮箱复合故障的故障特征分离,提出了一种基于形态分量分析与能量算子解调的齿轮箱复合故障诊断方法。该方法先根据振动信号中各组成成分形态的差异,采用形态分量分析方法构建不同形态的稀疏表示字典进行故障成分分离,将齿轮箱复合故障信号分解为包含齿轮故障信息的谐振分量、包含轴承故障信息的冲击分量和噪声分量,然后分别对谐振分量和冲击分量进行能量算子解调分析,最后根据各解调谱诊断齿轮和轴承故障。算法仿真和应用实例表明该方法能有效地分离齿轮箱复合故障振动信号中齿轮与轴承的故障特征。

英文摘要：

Aiming at the problem ot separating fault characteristics trom vibration signals ot a gearbox with compound faults, a compound fault diagnosis method for gearbox was proposed based on MCA and energy operator demodulating. According to the morphological difference of each compo- nent, different sparse dictionaries were built by MCA to separate each component from the vibration signals of a gearbox. By using MCA, the vibration signals of a gearbox with compound fault can be decomposed into harmonic component containing fault information of the gear, impulse component containing fault information of the bearing and random noise component. The harmonic component and the impulse component were analyzed respectively by the energy operator demodulating, and the compound fault diagnosis was carried out according to the demodulation spectrum. The simulation and application examples show that the proposed method can separate the fault characteristics from the vibration signals of a gearbox with compound faults effectively.