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EnglishThe electrical system is replacing traditional hydraulic and pneumatic transmission of secondary power for aircraft on-board equipment. Consequently, fault detection and health management strategies applied to electrical machines are becoming a highly relevant topic for research and development in the aerospace field. A major issue with all fault detection algorithm is the need to deal with uncertainty and accuracy of available measures. Measuring errors on system parameters, either due to the inherent sensors precision or to environmental and operational effects, can be easily misinterpreted as faults. A possible solution is to consider parameters for diagnostic and prognostic monitoring that are highly sensitive to incipient faults but at the same time insensitive to operating conditions. For electrical machines, a good choice is the counter-electromotive (back-EMF) coefficient but this quantity cannot be directly measured during operations. In this work, we propose an algorithm for real-time reconstruction of the back-EMF coefficient, leveraging a virtual sensor approach that merges information available from different sources to evaluate the magnetic coupling of the motor as a function of rotor angular position. The proposed strategy only relies on information available from already installed sensors, and does not require the installation of additional hardware. The reconstructed signal shows a strong dependency on the considered fault modes and is almost insensitive to external factors such as motor operating conditions.
Back-EMF Reconstruction for Electromechanical Actuators in Presence of Faults / Quattrocchi, G.; Berri, P. C.; Dalla Vedova, M. D. L.; Maggiore, P.. - ELETTRONICO. - (2020). ((Intervento presentato al convegno 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15).
| Titolo: | Back-EMF Reconstruction for Electromechanical Actuators in Presence of Faults | |
| Autori: | ||
| Data di pubblicazione: | 2020 | |
| Abstract: | The electrical system is replacing traditional hydraulic and pneumatic transmission of secondary ...power for aircraft on-board equipment. Consequently, fault detection and health management strategies applied to electrical machines are becoming a highly relevant topic for research and development in the aerospace field. A major issue with all fault detection algorithm is the need to deal with uncertainty and accuracy of available measures. Measuring errors on system parameters, either due to the inherent sensors precision or to environmental and operational effects, can be easily misinterpreted as faults. A possible solution is to consider parameters for diagnostic and prognostic monitoring that are highly sensitive to incipient faults but at the same time insensitive to operating conditions. For electrical machines, a good choice is the counter-electromotive (back-EMF) coefficient but this quantity cannot be directly measured during operations. In this work, we propose an algorithm for real-time reconstruction of the back-EMF coefficient, leveraging a virtual sensor approach that merges information available from different sources to evaluate the magnetic coupling of the motor as a function of rotor angular position. The proposed strategy only relies on information available from already installed sensors, and does not require the installation of additional hardware. The reconstructed signal shows a strong dependency on the considered fault modes and is almost insensitive to external factors such as motor operating conditions. | |
| ISBN: | 978-981-14-8593-0 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| ESREL_2020 BEMF PrePrint.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia | |
| ESREL_2020 FINAL_5097.pdf | Paper - Final Version | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2855180
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