Gas Flow Path Fault Diagnosis and Sensor Fault Diagnosis for Aeroengine Based on Fusion Filter Algorithm
Yafan Wang, Junning Qian · 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) · 2017
Kalman filter can be used to estimate the aeroengine's gas flow path health parameters. However, highdimensional matrix is difficult to solve and fault tolerance is limited. In this paper, fusion filter algorithm is first time suggested to estimate the aero-engine's gas flow path health parameters based on linear Kalman filter (LKF), extended Kalman filter (EKF) and unscented Kalman filter (UKF). Secondly, the aero-engine's gas flow path components diagnosis is presented on the basis of sensor measurement signal, the validity of sensor signal will have a direct impact on the fault diagnosis of the gas flow path components and the effectiveness of the whole engine control system. In this paper, on the basis of the fusion filter algorithm, the sensor fault detection unit is added between sub-filter and the main filter. Sensor fault can be detected based on the consistency of each sub-filter's state estimation. The test result shows that this approach is able to diagnose three major types of failure modes, such as the fault of engine sensor, the fault of gas flow path component fault and the simultaneous fault of sensor and the gas flow path component.