航空发动机振动信号分析

针对航空发动机转子振动特性,提出基于累积量改进的独立分量分析盲源分离算法。运用新方法对转子振动信号进行分离,识别转子中的故障类型。通过航空发动机转子振动仿真实验验证了该算法的有效性。结合仿真实验,对比基于二阶累积量和高阶累积量的已有算法,该新方法在性能指数和信号相似系数方面均有提高。应用该算法对发动机转子平台采集的振动信号进行分离,转子故障设置为外环故障。实测振动信号经该算法处理后有更高的辨识性,可以判断出转子振动的故障类型。

Analysis of Aeroengine Vibration Signal

Aiming at the analysis of the vibration characteristics of aeroengine rotor, an improved blind source separation algorithm based on cumulant independent component analysis (ICA) is proposed. The new algorithm is used to separate the rotor vibration signal and identify the rotor fault types. The effectiveness of this algorithm is verified by the aeroengine rotor vibration signal simulation. Comparing with the existing algorithms based on second-order cumulants and high-order cumulants, the new method improves the performance index and the signal similarity coefficient. This algorithm is used to separate the vibration signal collected by the engine rotor platform and the rotor fault is set as the outer ring fault. The vibration signal measured by this algorithm has a higher recognition, and the fault types of rotor vibration can be identified.