论文部分内容阅读
航空发动机气动失稳状态严重影响发动机的性能和安全,如何对气动失稳先兆进行预测判断是发动机领域重要的研究内容之一。基于小波熵在非平稳、瞬变微弱信号辨识方面有着良好的定位能力和灵敏度,将小波熵用于气动失稳信号先兆的捕获。以实际发动机失稳信号为样本进行小波熵分析。分析结果表明,小波熵能够及时捕获失稳先兆信号并给出报警信息。而且此算法具有较好的普适性,有利于发动机失稳的在线预警。
Aero-engine aerodynamic instability seriously affects the performance and safety of the engine. How to predict and predict aero-instability aura is one of the most important research topics in the field of engines. Based on wavelet entropy, it has good localization ability and sensitivity in non-stationary and transient weak signal identification. The wavelet entropy is used to capture the precursor of aerodynamic instability signal. The actual engine instability signal as a sample wavelet entropy analysis. The analysis results show that the wavelet entropy can capture the destabilizing signal and give the alarm information in time. Moreover, this algorithm has good universality and is conducive to online warning of engine instability.