Fault diagnosis algorithm for heat exchanger of aircraft environment control system based on double model filter

A fault diagnosis algorithm based on the double model filter (DMF) for a heat exchanger of the aircraft environment control system (ECS) is developed to improve the capability of fault diagnosis. The minimum mean-square values currently used in fault diagnosis can only get the static estimate values, and although the extended Kalman filter (EKF) can realize dynamic parameter estimation, yet for a nonlinear system, a single EKF does not exhibit good ability for either the normal process or the fault process. For the aircraft ECS, a fault diagnosis algorithm based on DMF is presented in this paper to deal with nonlinear systems. Two filters are used to track the different processes (normal or fault) in the DMF. For the ECS, two filters are used respectively to trace the steady state and the transient state of the system. The performance of parameter estimation and state prediction for ECS can be improved by using this method, and the accuracy and speed of fault diagnosis are also improved. Simulation is done to demonstrate the performance of this fault diagnosis algorithm.