摘要
为提高飞机燃油系统中传感器的有效性,对基于小波分析的传感器故障诊断方法进行了改进;该方法通过对传感器输出信号进行小波多分辨分析(MRA)能对缓变故障和突变故障进行准确定位,同时根据故障奇异点的模极大值和各尺度下故障前后能量变化特征实现对故障类型的判别;利用LabVIEW设计了传感器智能故障诊断系统,利用试验中采集的数据成功实现对飞机燃油系统油位传感器几种典型故障的诊断,证明该方法的有效性。
For the purpose of increasing the effectiveness of sensors in aircraft fuel system,the method based on the wavelet analysis of sensor fault diagnosis was improved.With this method,by Multi-Resolution Analysis（MRA） the sensor＇s output signals,the time and location of drift failure and abrupt fault occurred can be accurately detected,meanwhile,fault diagnosis can be finished according to the modulus maximum of fault singularity and energy variation characteristics on all decomposed wavelet scales of the signal before and after the time fault occurred.Then design intelligent sensor fault diagnosis system based on LabVIEW,by using the data collected in test,we successfully realize several typical fault diagnosis in oil level sensor of aircraft fuel system,this indicates the effectiveness of the method.
出处
《计算机测量与控制》
CSCD
北大核心
2011年第4期772-775,共4页
Computer Measurement &Control
关键词
飞机燃油系统
小波多分辨率分析
能量变化
故障诊断
aircraft fuel system
wavelet Multi-Resolution Analysis
energy variation
fault diagnosis
