Browsing by Author "Els, Dylan"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Detection of oscillatory actuator failures in passenger airliners
    (Stellenbosch : Stellenbosch University, 2019-04) Els, Dylan; Engelbrecht, J. A. A.; Engelbrecht, H. A.
    ENGLISH ABSTRACT: This project investigates and develops techniques to detect oscillatory failure cases (OFCs) in aircraft control surface actuators. Oscillatory failures induce additional loads on the structure of the aircraft, requiring additional structural support to withstand these loads, increasing the overall mass of the aircraft. If oscillatory failures can be detected and pacified quickly, then the additional structural support would not be required, and the mass of the aircraft can be reduced, resulting in improved fuel efficiency and aircraft performance. Oscillatory failure case (OFC) detection is performed by evaluating the difference (residual) between the measured behaviour of the real actuator and the simulated behaviour of a fault-free analytically redundant actuator model running in parallel with the real actuator. An OFC detection system must generate a residual signal using the analytically redundant actuator model, and evaluate the residual signal to determine whether an oscillatory failure is present. The challenge for the residual evaluation stage is to distinguish between the components of the residual signal resulting from modelling uncertainty and sensor noise, and the components resulting from an actual oscillatory failure case. The OFC detection system must detect oscillatory failures within a maximum allowable detection time, but must not produce false alarms. Five different oscillatory failure detection techniques are investigated and developed, namely oscillation counting, integrated absolute error (IAE), discrete Fourier transform (DFT), multi-window Fourier transform (MWFT), and phase-locked loop (PLL) detection. Oscillation counting is an existing OFC detection technique that was developed by Goupil [1] and is currently in service on the Airbus A380 passenger airliner. The other four techniques are new OFC detection techniques that are developed in this project. A simulation framework is created to serve as a testbed for the training and testing of the different OFC detection techniques. The simulation framework contains models for the physical actuator, the analytically redundant actuator, the oscillatory failures (both liquid and solid failures), the flight control system, and the aircraft longitudinal dynamics. The simulation models the aircraft’s response to an oscillatory failure, since it affects the performance of the OFC detection. The five OFC detection techniques are trained and rigorously tested using training and testing data generated with the simulation framework. The detection thresholds for each technique are “trained” on fault-free data to determine the lowest detection thresholds that do not produce false alarms. The detection techniques are then tested using testing data to determine the smallest amplitude oscillatory failure that each technique can detect within the specified maximum allowable detection time. The number of false alarms for each technique is also determined. The results show that DFT, MWFT, and the PLL outperform oscillation counting and IAE by detecting smaller amplitude oscillatory failures and with shorter detection times, with MWFT providing the most promising results. However, oscillation counting and IAE are the most computationally efficient techniques, while DFT, MWFT, and PLL are more computationally expensive. Overall, the multi-window Fourier transform (MWFT) technique is the recommended approach for OFC detection, offering the best detection performance with only a small increase in computational complexity.