Experimental Development of a Health Monitoring Method for Electro-Mechanical Actuators of Flight Control Primary Surfaces in More Electric Aircrafts

This paper presents a health monitoring approach for Electro-Mechanical Actuators (EMA). We define four different indicators to continuously evaluate the health state of the system. The four indicators are computed by leveraging the output from a Statistical Process Monitoring (SPM) method based on multivariate statistics, such as the Hotelling's T
²
statistic and the Q statistic. SPM approaches give a dichotomous answer, i.e. the presence/absence of a fault. In this work, we propose four ways to compute a continuous indicator starting from the discrete SPM output, that is better suited for health monitoring. We test the approach using a dataset collected from a large experimental campaign on a 1:1 scale EMA for primary flight controls of small aircrafts, that led to EMA failure. Results show the effectiveness of the method.