DGLR-Publikationsdatenbank - Detailansicht

Titel:

Monitoring of MGB Lubrication and Cooling System based on Big Data Normality Models and Fuzzy Expert Rules

Autor(en):
A. Mechouche, M. Houles, J. Belmonte, P.-L. Maisonneuve
Zusammenfassung:
This paper presents an original method for the monitoring of the helicopter main gearbox lubrication and cooling system. The method relies on sensor data of oil pressures and temperature, as well as on domain expert knowledge. It combines oil pressures and temperature normality models built from a significant amount of training data collected from customers helicopters, with fuzzy expert rules which allow precise root cause identification in case of lubrication or cooling sub-systems anomalies. The results have been validated based on known maintenance findings, showing that the proposed method allows to accurately detect anomalies related to the lubrication and cooling sub-systems as soon as they appear.
Veranstaltung:
49th European Rotorcraft Forum 2023, Bückeburg, 2023
Medientyp:
Conference Paper
Sprache:
englisch
Format:
21,0 x 29,7 cm, 9 Seiten
Veröffentlicht:
DGLR-Bericht, 2023, 2023-01, 49th European Rotorcraft Forum 2023 - Proceedings; S.1-9; 2023; Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V., Bonn
Preis:
NA
ISBN:
ISSN:
Kommentar:
Klassifikation:
Stichworte zum Inhalt:
Verfügbarkeit:
Bestellbar
Veröffentlicht:
2023


Dieses Dokument ist Teil einer übergeordneten Publikation:
49th European Rotorcraft Forum 2023 - Proceedings