基于混合卡尔曼滤波器组故障传感器定位方法

为了在发动机性能蜕化与传感器故障并存的情况下实现故障传感器的定位与部件蜕化情况的估计,并实现故障诊断基准数据的修正,构建了1种包含了机载模型与线性卡尔曼滤波器的组合结构混合卡尔曼滤波器组。该卡尔曼滤波器组能够在之前所描述的故障/蜕化耦合情况下定位故障传感器,并得到较为准确的部件蜕化估计结果。为了验证了混合卡尔曼滤波器组的有效性,进行了相关仿真。仿真结果表明:混合卡尔曼滤波器组能够在发动机动态过程中遭遇传感器故障与部件蜕化并存的情况下完成故障定位与蜕化估计。

Sensor Fault Location Based on Bank of Hybrid Kalman Filters

In order to realize the estimation of sensor fault location and component degradation during the coexisting of sensor faultand component degradation,and to correct the datum data of fault diagnosis,a bank of hybrid Kalman filters was constructed. The bank ofhybrid Kalman filters was a combined structure of on-board engine model and linear Kalman filter. The bank of Kalman filter could locatethe sensor fault in the case of fault / degradation coupling described previously and get a more accurate result of component degradationestimation. In order to verify the validity of the bank of hybrid Kalman filters,the relevant simulation was carried out. From the simulationresults,it can be seen that the bank of hybrid Kalman filters can complete fault location and degradation estimation when the sensor faultand component degradation coexist during the dynamic process of the engine.