A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators

As More/All Electric Aircraft gradually become a research hotspot, electromechanical actuators (EMAs), which can directly convert electrical energy into mechanical energy, have gained more and more attention. However, since the reliability of EMA cannot meet the requirements of actual aircrafts, the practical application of EMA is severely limited. Therefore, fault diagnosis, prognosis and health management (DPHM), which can realise condition-based maintenance (CBM), has become the key technology in the application of EMA. The aim is to summarise the research on EMA fault modes, fault diagnosis, prognosis and health management systematically and comprehensively. First, the basic structure and common fault modes of EMAs are introduced, and the failure mechanism of EMA is studied. Then, the algorithms of DPHM for EMAs are reviewed in detail. The perception strategies of data acquisition are analysed, and the EMA fault diagnosis methods, including model-based and data-driven methods, are reviewed. The research of remaining useful life (RUL) prediction and fault-tolerant control are introduced. After that, some problems of the existing research on EMA DPHM and their potential solutions are put forward. Finally, several possible developing directions of research on EMA DPHM are predicted.

Automated summary

This paper provides a systematic and comprehensive summary of the research on electromechanical actuators (EMAs) in terms of fault modes, fault diagnosis, prognosis, and health management (DPHM). It introduces the basic structure and common fault modes of EMAs, studies the failure mechanism of EMAs, and reviews the algorithms of DPHM for EMAs in detail. The paper also analyzes the perception strategies of data acquisition, reviews the fault diagnosis methods for EMAs, and introduces the research on remaining useful life (RUL) prediction and fault-tolerant control. Furthermore, it identifies existing problems in EMA DPHM research and predicts possible future directions.