基于Lyapunov指数谱的航空发动机故障诊断研究

提出了基于Lyapunov指数谱和Lyapunov指数谱熵的航空发动机状态识别和故障诊断新方法。基于实测的某型航空发动机振动时间序列求解了系统不同工作状态和故障状态的Lya-punov指数谱;基于Lyapunov指数谱,对该型航空发动机进行了状态识别和故障诊断;为给出对Lyapunov指数谱及其对状态识别和故障诊断的整体表述,定义了Lyapunov指数谱熵,并基于该谱熵对该型航空发动机进行了状态识别和故障诊断。研究结果表明该型航空发动机振动时间序列在不同状态下具有不同的Lyapunov指数谱及其谱熵,即可以Lyapunov指数谱及其谱熵作为识别其状态的特征量,为航空发动机的故障诊断和状态监控提供了新的可靠的方法。

Lyapunov Exponent Spectrum with Application to Aero Engine Fault Diagnosis

The new method for fault diagnosis and state recognition of aero engines is presented based on the Lyapunov exponent spectrum and its entropy. The Lyapunov exponent spectrum under different working states and fault conditions of aero engine is calculated by the experimental vibration time series measured from aero engine pedestal. To perfectly describe the Lyapunov exponent spectrum and the capability for fault diagnosis and state recognition,the Lyapunov exponent spectrum entropy is defined. The research shows that the Lyapunov exponent spectrum and the entropy for the vibration time series of aero engine varying with the working state and fault condition to be able to serve as the characteristic parameters for aero engine fault diagnosis and state recognition.