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The work deals with the development of deterministic model-based condition-monitoring algorithms for an electromechanical flight control actuator with fault-tolerant architecture, in which two permanent magnets synchronous motors are coupled with differential ball screws in speed-summing paradigm, so that the system can operate even after a motor fault, an inverter fault or a mechanical jamming. To demonstrate the potential applicability of the system for safety-critical aerospace applications, the failure transients related to major fault modes have to be characterised and analysed. By focusing the attention to jamming faults, a detailed nonlinear model of the actuator is developed from physical first principles and experimentally validated in both time and frequency domains for normal condition and with different types of jamming. The validated model is then used to design the condition-monitoring algorithms and to characterize the system failure transient, by simulating mechanical blocks in different locations of the transmission. The operability after the fault, obtained via fault-tolerant control strategy and position regulator reconfiguration, is also verified, by highlighting and discussing possible enhancements and criticalities.

The paper deals with theoretical and experimental studies for the development of a self-powered structural health monitoring (SHM) system using macro-fiber composite (MFC) patches. The basic idea is to integrate the actuation, sensing, and energy harvesting capabilities of the MFC patches in a SHM system operating in different regimes. As an example, during flight, under the effects of normal structural vibrations, the patches can work as energy harvesters by maintaining or restoring the battery charge of the stand-by SHM electronic board; on the other hand, if relevant/abnormal loadings are applied, or if local faults produce a noticeable stiffness variation of the monitored component, the patches can act as sensors for the power-up SHM board. During maintenance, the patches can then work as actuators, to stress the structure with pre-defined load profiles, as well as sensors, to monitor the structural response. In this paper, the investigation, based on the electromechanical impedance technique, is carried out on a system prototype made of a cantilevered composite laminate with six MFC patches. A high-fidelity nonlinear model of the system, including the piezoelectric hysteresis of the patches and three vibration modes of the laminate beam, is presented and validated with experiments. The results support the potential feasibility of the system, pointing out that the energy storage can be used for recharging a 3V-65mAh Li-ion battery, suitable for low-power electronic boards. The model is finally used to characterize a condition-monitoring algorithm in terms of false alarms rejection and vulnerability to dormant faults, by simulating built-in tests to be performed during maintenance.

The work deals with the model-based characterization of the failure transients of a fail-safe rotary EMA developed by Umbragroup (Italy) for the flap movables of the RACER helicopter-plane by Airbus Helicopters (France). Since the reference application requires quasi-static position-tracking with high disturbance-rejection capability, the attention is focused on control hardover faults which determine an actuator runaway from the commanded setpoint. To perform the study, a high-fidelity nonlinear model of the EMA is developed from physical first principles and the main features of health-monitoring and closed-loop control functions (integrating the conventional nested loops architecture with a deformation feedback loop enhancing the actuator stiffness) are presented. The EMA model is then validated with experiments by identifying its parameters by ad-hoc tests. Simulation results are finally proposed to characterize the failure transients in worst case scenarios by highlighting the importance of using a specifically designed back-electromotive damper circuitry into the EMA power electronics to limit the position deviation after the fault detection.

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