Electromechanical servomechanisms affected by motor static eccentricity: Proposal of fault evaluation algorithm based on spectral analysis techniques

The development of a prognostic algorithm capable of identifying the precursors of incipient failures of primary flight command Electromechanical Actuators (EMA) is beneficial for the anticipation of the incoming failure: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. Prognostic, though, is strictly technology-oriented as it is based on accurate analysis of the cause and effect relationships. As a consequence, it is possible that prognostics algorithms that demonstrate great efficacy for certain applications fail in other circumstances, just because the actuator is based on a different technology. In this paper the authors propose an innovative prognostic “model-based” technique able to identify symptoms of an EMA degradation before the actual exhibition of the anomalous behavior. The identification/evaluation of the considered incipient failures is performed analyzing proper critical operational system parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters are correlated with the actual health condition of the considered system by means of failure maps created by a reference monitoring model-based algorithm. According to preliminary testing, the proposed method has proved its worth for different types of EMA progressive failure: in particular, in the present work, it has been applied to the case of an actuator having brushless DC motor affected by a progressive increase of the static eccentricity of the rotor. © 2015 Taylor & Francis Group, London.