Fault detection of wind turbine gearbox using thermal network modelling and SCADA data

Tools

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)

[thumbnail of Corley-etal-JoP-2020-Fault-detection-of-wind-turbine-gearbox-using-thermal-network-modelling-and-SCADA-data]
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: Creative Commons Attribution 3.0 logo
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 logoORCID: https://orcid.org/0000-0002-1510-1416 and Mcdonald, A. ORCID logoORCID: https://orcid.org/0000-0002-2238-3589;
CORE (COnnecting REpositories)