Online Model-Based Remaining-Useful-Life Prognostics for Aircraft Cooling Units Using Time-Warping Degradation Clustering

Remaining-useful-life prognostics for aircraft components are central for efficient and robust aircraft maintenance. In this paper, we propose an end-to-end approach to obtain online, model-based remaining-useful-life prognostics by learning from clusters of components with similar degradation trend...

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Bibliographic Details
Published in:Aerospace 2021-06, Vol.8 (6), p.168
Main Authors: Mitici, Mihaela, de Pater, Ingeborg
Format: Article
Language:English
Subjects:
Aging aircraft
Aircraft
Aircraft components
aircraft Cooling Unit
Aircraft maintenance
Airplane engines
Algorithms
Clustering
Cooling
Degradation
Kalman filters
Libraries
multi-model degradation
Neural networks
online remaining-useful-life prognostics
particle filtering
Predictive maintenance
Sensors
Standard deviation
Time measurement
Trends
Warping
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Summary:Remaining-useful-life prognostics for aircraft components are central for efficient and robust aircraft maintenance. In this paper, we propose an end-to-end approach to obtain online, model-based remaining-useful-life prognostics by learning from clusters of components with similar degradation trends. Time-series degradation measurements are first clustered using dynamic time-warping. For each cluster, a degradation model and a corresponding failure threshold are proposed. These cluster-specific degradation models, together with a particle filtering algorithm, are further used to obtain online remaining-useful-life prognostics. As a case study, we consider the operational data of several cooling units originating from a fleet of aircraft. The cooling units are clustered based on their degradation trends and remaining-useful-life prognostics are obtained in an online manner. In general, this approach provides support for intelligent aircraft maintenance where the analysis of cluster-specific component degradation models is integrated into the predictive maintenance process.
ISSN:2226-4310
2226-4310
DOI:10.3390/aerospace8060168