Aero-engine dynamic modeling based on flight parameter data and BP neural network

Abstract:
The aero-engine is a large and complex system, and the research and use of simulation technology can greatly reduce the cost and difficulty of learning, training and, experimental research. Based on the flight parameter data and the engine control plan, this paper uses computer simulation technology to establish the steady-state process neural network model of the engine, and adopts the process fitting method to establish the transient state process engine model. Finally, by integrating the transition state model and the steady state model, the development of the aero-engine dynamic model is completed. Since the development of the model is based on real flight parameter data, it has high simulation accuracy and can achieve better simulation results.