What is it about?
This paper proposes a new prognostic model-based technique that detects EMA increasing degradations. Identifying and evaluating the considered incipient failures is based on suitable system operational parameters, using a numerical approach based on spectrum analysis techniques. Failure maps generated by a reference monitoring model-based algorithm are then used to connect these operational data with the real EMA health state. The proposed method has been tested in the case of an EMA affected by progressive combined failures. In particular, partial turn-to-turn short-circuit of the stator winding and rotor static eccentricity are considered.
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Why is it important?
The proposal of predictive algorithms that identify precursors of incipient failures of primary flight command electromechanical actuators (EMA) is beneficial for anticipating the incoming loss. Therefore, an early and correct interpretation of the failure degradation pattern can trig an early alert of the maintenance crew, who can adequately schedule the servomechanism replacement. Results gained by authors show that the method exhibit adequate robustness and a high degree of confidence in the ability to identify an eventual malfunctioning early, minimizing the risk of fake alarms or unannounced failures.
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This page is a summary of: Electromechanical actuators affected by multiple failures: Prognostic method based on spectral analysis techniques, January 2017, American Institute of Physics,
DOI: 10.1063/1.4981960.
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