SVR结合小波变换的SUH传感器故障诊断

针对微小型无人直升机故障多、采样难且精确建模难度大的特点，将回归型支持向量机（SVR）引入到微小型无人直升机机载传感器的故障诊断中，提出了一种将SVR与离散小波变换（DWT）相结合的微小型无人直升机传感器故障检测与分离方法。利用回归型支持向量机（SVR）具有自学习和非线性映射能力强的特点，建立基于SVR的残差生成器并利用残差检测故障。在此基础上，利用小波变换实现对故障的隔离与定位。实验结果表明，将SVR与DWT相结合进行微小型无人直升机机载传感器的故障诊断是行之有效的。

Fault detection and isolation for sensors on SUH based on SVR and wavelet transform

In order to cope with the difficulties in multiple kinds of faults,data collection and precise modeling,Support Vector ＇Regression（SVR） is introduced into the fault diagnosis of sensors on Small Unmanned Helicopters（SUH）,and a new fault detection and isolation method based on Support Vector Regression（SVR） combined with Discrete Wavelet Transform （DWT） method is presented in this paper.With its strong capabilities in self learning and nonlinear mapping, SVR is used to build a residual generator to detect faults.Then,DWT is used to isolate the faulty sensor.The experiment result shows that the method is feasible and effective in the sensors fault detection and isolation.