This paper proposes the use of a change detection algorithm to monitor the degradation of mechanical components of Electro-Mechanical Actuators (EMA) employed in the aerospace industry. Contrary to the standard on-line application of change detection methods, the presented approach can be applied in a batch mode, leveraging on the knowledge of when the data were collected. The methodology is applied to data measured during an endurance test campaign on a real EMA employed in aerospace, by means of a developed test bench, progressively bringing the EMA to failure. Three rationales for building an indicator of degradation are tested. Results show how the method is able to assess the degradation of the actuator over time, constituting a first step towards a condition monitoring solution for the more-electric-aircraft of the future.

(2018). Condition Monitoring of Electro-Mechanical Actuators for Aerospace Using Batch Change Detection Algorithms . Retrieved from http://hdl.handle.net/10446/131590

Condition Monitoring of Electro-Mechanical Actuators for Aerospace Using Batch Change Detection Algorithms

Mazzoleni, Mirko;Previdi, Fabio;
2018-01-01

Abstract

This paper proposes the use of a change detection algorithm to monitor the degradation of mechanical components of Electro-Mechanical Actuators (EMA) employed in the aerospace industry. Contrary to the standard on-line application of change detection methods, the presented approach can be applied in a batch mode, leveraging on the knowledge of when the data were collected. The methodology is applied to data measured during an endurance test campaign on a real EMA employed in aerospace, by means of a developed test bench, progressively bringing the EMA to failure. Three rationales for building an indicator of degradation are tested. Results show how the method is able to assess the degradation of the actuator over time, constituting a first step towards a condition monitoring solution for the more-electric-aircraft of the future.
2018
Mazzoleni, Mirko; Scandella, Matteo; Maccarana, Yamuna; Previdi, Fabio; Pispola, Giulio; Porzi, Nicola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/131590
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