The gradual deployment of Electro Mechanical Actuators (EMAs) as primary flight controls actuators, driven by the “more electric” approach, must be paired up with a solid prognostic background in order to overcome the limited experience and to support the system during his lifecycle. In fact, assessing EMAs actual states thanks to Prognostic and Health Monitoring (PHM) systems and detecting potential failures is crucial to guarantee the compliance to the relative safety requirements. The research activity described in this paper focuses on the development of a model-driven deterministic methodology based on Failure Modes Maps (FMMs). Thanks to data obtained through a Numerical Test Bench (NTB) and a Simplified Model (SM), the proposed prognostic algorithm is proved capable of detecting and identifying the source and magnitude of two different failures: rotor eccentricity and increased friction. After a short description of the implemented models and a general overview of typical EMA failure modes as well as FMMs development, the proposed algorithm is explained in detail. This is followed by a comprehensive study of the two simulated failures as well as the creation of the relative FMMs. Finally, the proposed prognostic algorithm is successfully applied on the obtained FMMs.

PROGNOSTICS OF AEROSPACE ELECTROMECHANICAL ACTUATORS USING THE FAILURE MAPS TECHNIQUE / Aimasso, A.; Baldo, L.; Vedova, M. D.; Maggiore, P.. - In: INTERNATIONAL JOURNAL OF MECHANICS AND CONTROL. - ISSN 1590-8844. - 23:1(2022), pp. 93-104.

PROGNOSTICS OF AEROSPACE ELECTROMECHANICAL ACTUATORS USING THE FAILURE MAPS TECHNIQUE

Aimasso A.;Baldo L.;Vedova M. D.;Maggiore P.
2022

Abstract

The gradual deployment of Electro Mechanical Actuators (EMAs) as primary flight controls actuators, driven by the “more electric” approach, must be paired up with a solid prognostic background in order to overcome the limited experience and to support the system during his lifecycle. In fact, assessing EMAs actual states thanks to Prognostic and Health Monitoring (PHM) systems and detecting potential failures is crucial to guarantee the compliance to the relative safety requirements. The research activity described in this paper focuses on the development of a model-driven deterministic methodology based on Failure Modes Maps (FMMs). Thanks to data obtained through a Numerical Test Bench (NTB) and a Simplified Model (SM), the proposed prognostic algorithm is proved capable of detecting and identifying the source and magnitude of two different failures: rotor eccentricity and increased friction. After a short description of the implemented models and a general overview of typical EMA failure modes as well as FMMs development, the proposed algorithm is explained in detail. This is followed by a comprehensive study of the two simulated failures as well as the creation of the relative FMMs. Finally, the proposed prognostic algorithm is successfully applied on the obtained FMMs.
File in questo prodotto:
File Dimensione Formato  
JoMaC J23A_RI_06 Aimasso.pdf

non disponibili

Descrizione: PostPrint J23A Aimasso
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 968.3 kB
Formato Adobe PDF
968.3 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
JoMaC 2022A Aimasso DRAFT.pdf

accesso aperto

Descrizione: JoMaC 2022A PrePrint
Tipologia: 1. Preprint / submitted version [pre- review]
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 962.48 kB
Formato Adobe PDF
962.48 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2970095