飞行器伺服电磁阀电流去噪仿真研究

On Simulation of Current De-noising Method in Aircraft Servo Solenoid Valve

在地面对伺服电磁阀测试的过程中,某型飞行器搭载的伺服电磁阀的工作电流信号容易混入干扰噪声,这将直接导致伺服电磁阀故障检测产生虚警,耽误作战的黄金时机。针对上述问题,提出了采用量测残差自适应卡尔曼滤波的数据校正方法,将地面测试系统采集的电流值与同一时刻的预测值对系统真实状态进行最优估计,采用系统误差和量测误差自适应的方式解决噪声干扰问题,准确检测伺服电磁阀的状态。实验结果表明,改进自适应卡尔曼滤波算法(AKF)能够有效降低电流中的噪声,提高伺服电磁阀故障检测的准确率。

The solenoid valve current signal of a certain type of aircraft is easily mixed in noise in the process of ground testing, which will directly lead solenoid valve failure detection to false alarm, and delay the golden opportu- nity to fight. Based on the residual measurement, adaptive Kalman filter data correction method is proposed in this paper. Predictive values depending on previous cycle and data acquisition of fault detection can approach the state of the system by using adaptive filter depending on the systematic error and measured error. It accurately detects the state of the solenoid valve. The experiment results show that the proposed adaptive Kahnan filtering algorithm （AKF） can effectively remove the noise from current and improve the accuracy of fault detection of solenoid valve.