Fault detection of wind turbine gearbox using thermal network modelling and SCADA data
Corley, B. and Carroll, J. and Mcdonald, A. (2020) Fault detection of wind turbine gearbox using thermal network modelling and SCADA data. Journal of Physics: Conference Series, 1618. 022042. ISSN 1742-6588 (https://doi.org/10.1088/1742-6596/1618/2/022042)
Preview |
Text.
Filename: Corley_etal_JoP_2020_Fault_detection_of_wind_turbine_gearbox_using_thermal_network_modelling_and_SCADA_data.pdf
Final Published Version License: Download (647kB)| Preview |
Abstract
This work uses a detailed understanding of the physics inside a wind turbine gearbox and SCADA temperature data as an alternative to data-driven techniques for fault detection. Thermal modelling based on the principles of heat transfer theory is used with the aim of understanding the thermal behaviour of a ‘healthy’ gearbox and use it to detect abnormal gearbox operating conditions. Data for turbines, 'healthy' and one month to fail, are analysed for two different failure modes to see if a fault can be detected in advance with the aim to improve physical understanding of wind turbine gearbox operation and condition monitoring techniques.
ORCID iDs
Corley, B., Carroll, J. ORCID: https://orcid.org/0000-0002-1510-1416 and Mcdonald, A. ORCID: https://orcid.org/0000-0002-2238-3589;-
-
Item type: Article ID code: 75372 Dates: DateEvent21 September 2020Published27 April 2020Accepted11 March 2020SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 11 Feb 2021 11:56 Last modified: 11 Nov 2024 12:37 URI: https://strathprints.strath.ac.uk/id/eprint/75372