摘要
在航空发动机早期故障诊断中,特征提取是早期诊断的重要过程之一。文中以航空发动机转子故障为研究对象,给出了基于经验模式分解、小波分析为核心的故障特征提取方法,并作了针对性的比较研究。在matlab7.0环境下开发了一个故障特征提取软件系统。研究结果表明:基于经验模式分解的时频分析方法可以很有效地提取到非平稳故障特征信号,是一种适合于非线性信号处理的方法。
Extracting features of the faults is one of the most important processes in the aircraft engine incipient faults diagnosis. We study the aircraft engine rotor faults and present two methods for extracting feature of faults based on empirical mode decomposition （EMD） and wavelet transformation respectively. Through the numerical data magnitude analyzing and emulation, we compare the characteristics between two methods. Under the environment of Matlab7.0, a soft system of extracting feature of the fault is developed. The experiment result shows that the time-frequency method based on EMD can effectively extract the feature of unbalanced fault signal and is proper for non frequency modulation signal procession.
出处
《计测技术》
2007年第2期7-10,共4页
Metrology & Measurement Technology
基金
国家自然科学基金资助项目(60472116)
航空科学基金资助项目(03I53068)
关键词
经验模式分解
小波变换
早期故障诊断
故障特征提取
empirical mode decomposition
wavelet transformation
incipient faults diagnosis
extracting features of the faults
