Active Packet Dropout Kalman Filter Based Diagnosis Scheme For Liquid Rocket Engines With Measurement Fault

Abstract

Abstract Various faults of the liquid rocket engine (LRE) threaten the safety of space launches. The LRE system faults are challenging to detect and isolate owing to sensor faults. In this paper, an active packet dropout Kalman filter (APD-KF) based method is proposed for solving the problem of LRE system fault detection and isolation (FDI) under measuring fault. Sensor faults are isolated firstly based on distributed extended multiple model adaptive estimation (EMMAE) scheme, and the sensor fault detection isolation (FI) result are then transformed to the package drop matrix and inserted into the system fault factor estimation process to discard fault measurement information. Experimental results based on data from simulation are used to decorate the efficiency of the method. This study may help to improve LRE health management and reduce launch risk by solving the problem of LRE system FDI with measurement fault.