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Abstract
During flights aircraft continuously collect data regarding operations, health status and system condition. Data-driven approaches typically applied to system specific sensor data provide a way to predict failures of aircraft systems. However, it is believed that some systems deteriorate faster when subjected to particular environmental conditions, such as humidity or dust. In this study, we consider an aircraft system which is suspected to experience degradation due to humidity during ground operations. We apply a Random Forest approach to sensor data only and a combination of sensor data and environmental data from airports to estimate the system's remaining useful life. To our knowledge this is the first paper addressing the problem of integrating environmental data in prognostics for aircraft systems using raw sensor data. The method is validated on a data set provided by an airline that includes the per-second sensor data of 11 different sensors for roughly 12,300 flights, as well as 15 removals. Meteorological data for airports worldwide is obtained from the Meteorological Aerodrome Reports database. The results show that incorporating environmental data in prognostics has a potential towards more accurate prediction models.
Original language | English |
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Title of host publication | 67th Annual Reliability and Maintainability Symposium, RAMS 2021 |
Subtitle of host publication | Proceedings |
Publisher | IEEE |
Number of pages | 6 |
ISBN (Electronic) | 978-1-7281-8017-5 |
ISBN (Print) | 978-1-7281-8018-2 |
DOIs | |
Publication status | Published - 2021 |
Event | 2021 Annual Reliability and Maintainability Symposium (RAMS) - Orlando, United States Duration: 24 May 2021 → 27 May 2021 |
Publication series
Name | Proceedings - Annual Reliability and Maintainability Symposium |
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Volume | 2021-May |
ISSN (Print) | 0149-144X |
Conference
Conference | 2021 Annual Reliability and Maintainability Symposium (RAMS) |
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Country/Territory | United States |
City | Orlando |
Period | 24/05/21 → 27/05/21 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- condition-based maintenance
- prognostics
- aircraft maintenance
- RUL
- environmental data
Fingerprint
Dive into the research topics of 'Data-Driven Prognostics Incorporating Environmental Factors for Aircraft Maintenance'. Together they form a unique fingerprint.Projects
- 1 Finished
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ReMAP: Real-time Condition-based Maintenance for Adaptive Aircraft Maintenance Planning
Santos, B. F., Zarouchas, D., Mitici, M. A., Verhagen, W. J. C., Mechbal, N., Rébillat, M., Guskov, M., Bieber, P., Olive, X., Ghosh, A., Chabukswar, R., Couto, L., Ribeiro, B., Cardoso, A., Machado, P., Dourado, A., Arrais, J. P., Silva, C., Roque, L., Loutas, T., Kostopoulos, V. & Sotiriadis, G.
1/06/22 → 31/08/22
Project: Research