Fault Diagnostics of Electromechanical Actuators in Aerospace Safety Critical Applications

  • Yameen M Hussain

Student thesis: Doctoral ThesisEngineering Doctorate (EngD)

Abstract

Electromechanical Actuators (EMAs) are increasingly being considered for safety critical applications across the aerospace sector because of the potential benefits this technology can offer compared to traditional types of actuator. One of the main challenges for EMA implementation within safety critical applications is mitigating the single point of failure: ballscrew jamming. Better understanding of the onset of EMA ballscrew jamming, and consequences of jamming, would make EMAs a more viable option for aerospace safety critical applications.

Through Hierarchical Process Modelling (HPM) and review of previous literature, various diverse strategies were considered to mitigate EMA ballscrew jamming. The most favoured approach was fault diagnostics i.e. predicting the state of health of a component or onset of failure by monitoring system operation. Monitoring the state of health of a component in turn allows new maintenance strategies, for example Condition Based Maintenance (CBM). As part of a systems approach towards evaluating fault diagnostics, a Systems Dynamics (SD) study was conducted to capture the cost benefits of applying a CBM maintenance strategy to a fleet of aircraft in comparison to a conventional time-based maintenance strategy. Historical in-service data for EMAs was used in this study and it was notable that the reliability of EMAs had significantly improved over the timescale of the data, which meant the direct economic benefit of CBM was reduced. Therefore, the primary benefit of fault diagnostics was improving safety.

Sensing for fault detection was limited to using motor current alone, thus exploiting an existing sensor of the actuator system. A hybrid approach to fault diagnostics was proposed which utilises a combination of high-fidelity modelling of the system and experimental data to supplement the real application being monitored. Through simulations it was demonstrated that feature extraction of ballscrew dynamic frictional behaviour could be achieved through Iq current analysis. The results were also mapped to health states in a classification algorithm. The analysis was then extended to an industrial based case study for an Airbus A320 Nose Landing Gear extension-retraction system where it was demonstrated that EMA ballscrew stiction could be identified through motor current in the presence of aero loads.

The final outcome of this thesis was the development of a CBM technique for the A320 NLG extension-retraction system. The approach taken was to perform offline CBM checks on accumulated flight data (motor current signals) on a weekly basis. The diagnostics were based on extracting dynamic friction features of the EMA ballscrew through Iq currents and comparison of these with an analytical model in a hybrid approach.
Date of Award23 Jun 2020
Original languageEnglish
Awarding Institution
  • The University of Bristol
SponsorsStirling Dynamics Ltd.
SupervisorSteve G Burrow (Supervisor)

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