Health On Line Monitoring for Electro-mechanical a.. (HOLMES)
Health On Line Monitoring for Electro-mechanical actuator Safety
Start date: Nov 1, 2013,
End date: Jun 30, 2016
"In the scope of the development of a more electrical aircraft, the project aims to develop a reliable tool for the health monitoring of electro-mechanical actuators (EMAs). The replacement of hydraulic systems with the implementation of EMAs on flight control actuation systems of both A/C and H/C can lead to many advantages but, since the mechanical jam of such a system has to be considered as a possible and high critical event, research activities have to pay attention to the compliance with the operational reliability and safety requirements. One of the most attractive and promising way to meet these requirements is the implementation of advanced health monitoring systems. Use of sensors for the detection of failures has been successfully proved by the research community, including Umbra, but the challenge of the HOLMES project is to rely on components that are basic on an EMA like electric motors, position sensors, motor commutation devices without additional sensing on the internal mechanical components (vibration, temperature, etc...). A promising parameter is the phase electric motor currents but other (e.g. voltage, speed of the motor and position of the actuator) will be evaluated. When this is the case, the reliability and safety of the EMA will be improved without any penalty in terms of weight and envelope. So, the strategy of the HOLMES project is to simplify the hardware measurement layout, moving complexity in the software and algorithm design. In this view, a mixed approach for FDI will be proposed. When a degradation (in a stochastic sense) of “on flight” measured variables will be evident with respect to the nominal values, a model-free FDI generates an alarm. This information will be integrated by the results of a spectral analysis of the measured signals that will put in evidence the presence of unexpected harmonics. The two sources of information will be merged by using black box identification methods."
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