FLEA

Electro-mechanical actuators (EMAs) have been gaining increased acceptance as safety-critical actuation devices in the next generation of aircraft and spacecraft. The aerospace manufacturers are not ready, however, to completely embrace EMAs for all applications due to apprehension with regard to some of the more critical fault modes. This work aims to help address these concerns by developing and testing a prognostic health management system that diagnoses EMA faults and employs prognostic algorithms to track fault progression and predict the actuator remaining useful life. The diagnostic algorithm is implemented using a combined model-based and data-driven reasoner. The prognostic algorithm, implemented using Gaussian Process Regression, estimates the remaining life of the faulted component. The paper also covers the selection of fault modes for coverage and methods developed for fault injection. Validation experiments were conducted both in laboratory and flight conditions using the Flyable Electromechanical Actuator (FLEA) test stand. The FLEA allows test actuators to be subjected to realistic environmental and operating conditions, while providing the capability to safely inject and monitor propagation of various fault modes. The paper covers both diagnostic and prognostic, run-to-failure experiments, conducted in laboratory and flight conditions for several types of faults. The experiments demonstrated robust fault diagnosis on the selected set of component and sensor faults and high-accuracy predictions of failure time in prognostic scenarios.