基于离散小波变换的某型航空发动机故障诊断研究

Investigation of Aeroengine Fault Diagnosis Based on Discrete Wavelet Transform

主要研究了离散小波变换极值点的方法在航空发动机传感器故障诊断中的应用;对输入信号输出信号进行离散小波高、低频系数分解重构,利用该系数求出输入输出信号的奇异值,然后去除由于输入突变所引起的极值点,其余的极值点对应于传感器的故障;在MATLAB平台下,仿真结果表明,该故障诊断方法可以及时、有效地检测出航空发动机传感器出现的各类故障。

This paper describes a novel approach based upon discrete wavelet transform for fault detection of aeroengine. By the use of discrete wavelet transform that well localize the characterization of signal both in time and frequency domains, the occurring instants of abnormal status of a sensor in its output signal can be identified. We mainly study aeroengine sensor fault diagnosis based on discrete wavelet transform. According to the decomposition and reconstruction of discrete wavelet coefficients of input and output, we can locate the singularity of signals. And then, by deducting the extreme points corresponding to the input signal, we can detect the sensor fault. It indicates that aeroengine sensor faults can be detected accurately and promptly using this method through a large number of simulations in Matlab.