State Tracking and Fault Diagnosis of Liquid Rocket Engine Based on Reduced-Order Model

This paper is aimed at the fault diagnosis of liquid rocket engine, especially in the case of deep thrust regulation scenario. After reducing the order of the model according to the actual sensor situation of the engine and using the state space expression, a new fault diagnosis algorithm is proposed based on the model. The algorithm is completely designed for the measurable parameters in the actual engine, which can avoid the complicated calculation of fault parameters in the previous research, and can accurately track the engine state when it performs a wide range of nonlinear thrust regulation. By applying the algorithm to engine simulation and test data, it proves the validity of the idea in this paper and the feasibility of its further optimization in the future.