Research of Real-time Fault Diagnosis Platform of Aero-engine's Fuel Flow Sensors

摘要

The purpose of the research is to put up a fault diagnosis algorithm of the aero-engine's fuel flow sensors and verify the platform through simulation based on the QAR (Quick Access Recorder) data. By analyzing the correlations of the parameters that affect the conditions of the engine, a three-layer BP network model is established. Then, in order to solve the influences to the BP model in the full envelope due to the fluctuations of transition between different flight phases, a region partition method is used to divide the whole flight envelop into several regions and corresponding BP model is established. Finally, the QAR data are used as the training samples to build the BP network for different regions, then, the real-time data are used as the inputs to verify the platform. The simulation results show that the region partition method can effectively detect the fault of the fuel flow sensors.