利用小波分析检测航空发动机传感器故障  

Aero-Engine Sensor Failure Detection by Using Wavelet Analysis

作　　者：缑林峰[1] 赵廷渝[1] 王镛根[1] 

机构地区：[1]西北工业大学动力与能源学院,陕西西安710072

出　　处：《计算机仿真》2005年第9期37-39,共3页Computer Simulation

摘　　要：该文比较了傅立叶变换与小波分析的基本理论并研究了它们在航空发动机传感器故障检测应用中的特点,提出了一种基于小波变换的故障检测方法。该方法针对噪声和故障信号均具有呈现非平稳瞬态特性的特点,利用小波多分辨分析将量测信号分解到不同的频率通道中去,因此它就可以在一定的频率区间内,将故障信号成分和正常信号输出成分区分开来,提高传感器故障检测的准确度。仿真结果表明,该方法借助小波变换强大的时频分析能力,可以准确判定传感器软、硬故障,有效降低误报率和漏报率,具有良好的应用价值。This paper compares Fourier transform with Wavelet Analysis on basic theories, and studies their characteristics of applying to aero - engine sensor failure detection. A new detection method is proposed based on wavelet transform. To noise and failure signals it shows unsteady instant characteristics to decompose measuring signal in different frequency channels by using wavelet multiresolution analysis, then distinguishes failure from normal signal. The simulation results prove that wavelet analysis has a superior skill of time and frequency analysis to detect sensor＇s soft and hard failure, reduce distortion and failing report, and is effective and useful.

关 键 词：傅立叶变换 小波分析 故障检测 多分辨分析 

分 类 号：TP206.3[自动化与计算机技术—检测技术与自动化装置]