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https://doi.org/10.1109/ccta.2...
Article . 2018 . Peer-reviewed
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Condition Monitoring of Electro-Mechanical Actuators for Aerospace Using Batch Change Detection Algorithms

Authors: Mazzoleni, Mirko; Scandella, Matteo; Maccarana, Yamuna; Previdi, Fabio; Pispola, Giulio; Porzi, Nicola;

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

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.

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Keywords

Aerospace Engineering; Control and Optimization; Automotive Engineering; Safety, Risk, Reliability and Quality

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Top 10%
Green