Digital twin of aircraft electrical actuator to generate data for health management research

Abstract

Electric-powered actuators play an important role in the new generations of commercial aircraft systems. They are used in Flight Control, Propulsion, Landing Gear and even seat actuation. As they are “Power-by-Wire” and connected to the aircraft control system, it is easy to acquire their operations and health data. Electro-Mechanical Actuator (EMA) is increasingly used to replace traditional hydraulic actuators in the future All/More Electric Aircraft. However, lack of historical operational data makes complicated the risk analysis of EMA into aircraft systems. This research aims to develop an approach of Digital Twin design to support data generation for Aircraft Health Management algorithm development. The Digital Twin is designed to represent flight control EMA. The data generator is developed combining the Digital Twin EMA and a fault injection module, controlled by MATLAB scripts, to simulate operations in multiple scenarios, including nominal operations, degradation, and fault. EMA faults represented include unstable power supply, mechanical backlash, and power cable wear. The combination of simultaneous faults is explored by introducing multiple faults as part of the case analysis. This research indicates data could be generated to enable failure features detection in early or mid-stage failures. The research tackles the challenge to monitor, trigger and locate faults at subsystem/component level of an EMA. The framework could generate datasets to accelerate diagnostic and prognostic research in the early detection of EMA failures and enhance performance, thus facilitating timely maintenance actions that can prevent costly downtimes and extend the operational life of aircraft components. The framework extends the concept of Digital Twin as a tool to support engineering design and operations to a toll for data generation.