Dual State and Parameter Estimation for Diagnosis, Prognosis, and Health Monitoring of Electro-Mechanical Actuators

In this paper, the problem of diagnosis, prognosis, and health monitoring (DPHM) for electro-mechanical actuators (EMA) under degradation and fault is studied. The performance of the EMA is crucial in flight control systems (FCS), and hence, degradation in these systems should be accurately monitored. A dual state and parameter estimation methodology by utilizing particle filters (PF) is used in this work to estimate the states of EMA and their degradations. Moreover, the PF have been used to predict the evolution of states and degradation in the EMA, which can be used to estimate and evaluate their remaining useful life (RUL). In the provided numerical case study, the effectiveness of the dual state and parameter method in estimating and predicting states and degradation for a given electro-mechanical actuator is provided and the RUL of the system is predicted. Moreover, the predicted probability of failure by utilizing the estimated states and parameters up to the t-th instant as an indicator of the accuracy of our DPHM methodology is obtained.