飞机发动机关键系统智能故障诊断方法

飞机发动机是一个非常复杂的大系统,由于其结构复杂,工作环境恶劣,对其关键系统的故障进行准确诊断始终是困扰业界的技术瓶颈之一。提出了采用EMD小波阈值降噪与主元分析相结合的方法,对飞机发动机气路系统故障诊断进行了深入研究。针对某型真实飞机发动机进行测试试验采集的气路多参量数据,首先采用经验模态分解(Empirical Mode Decomposition,EMD)对气路系统各参量信号进行EMD分解,然后采用软阈值函数对其进行降噪,并进行信号重构,从而可得到飞机发动机气路工作状态有效数据。在此基础上,设计了飞机发动机气路系统主元分析故障诊断模型,并结合预处理得到的飞机发动机气路有效数据,运用所设计的主元分析故障诊断模型对飞机发动机进行故障诊断技术研究。研究结果表明,所提出的方法能够很好地诊断出飞机发动机气路系统实际运行时所出现的故障,具有重要的实际应用价值,并有广泛的应用前景。

Research on Intelligence Fault Diagnosis Methods of Aeroengine Key System

Aircraft engine is a very complex system,and it has complex structure,poor working environment. So it is one of the technical bottlenecks for accurate diagnosis of the key system fault which plagued the industry. The paper proposes one method which combines EMD threshold de-noising in wavelet and principal component analysis method. And the paper is depth study of the fault diagnosis for aircraft engine gas path system. For the multi parameter data which has be obtained for a certain type aircraft engine gas path test collection,the signal of the pneumatic system the parameters are decomposed using the empirical mode decomposition(EMD),and use the soft threshold function to reduce the noise,and the signals are reconstructed. So it can get the aircraft engine gas path valid data. On this basis,the paper designs fault diagnosis model of principal component analysis for the aircraft engine gas path system,and combined with valid data obtained from the aircraft engine gas path. The paper develops the fault diagnosis technology research using the principal component analysis fault diagnosis model for aircraft engines. Research results shows that the proposed method can diagnose the actual operation of aircraft engine gas path system fault,and the method has important practical application value and wide application prospect.