Current signature and vibration analyses to diagnose an in-service wind turbine drive train

Artigao, Estefania and Koukoura, Sofia and Honrubia-Escribano, Andrés and Carroll, James and McDonald, Alasdair and Gómez-Lázaro, Emilio (2018) Current signature and vibration analyses to diagnose an in-service wind turbine drive train. Energies, 11 (4). ISSN 1996-1073 (

[thumbnail of Artigao-etal-Energies2018-Current-signature-and-vibration-analyses-to-diagnose]
Text. Filename: Artigao_etal_Energies2018_Current_signature_and_vibration_analyses_to_diagnose.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (1MB)| Preview


The goal of the present paper is to achieve the diagnosis of an in-service 1.5 MW wind turbine equipped with a doubly-fed induction generator through current signature and vibration analyses. Real data from operating machines have rarely been analysed in the scientific literature through current signature analysis supported by vibrations. The wind turbine under study was originally misdiagnosed by the operator, where a healthy component was replaced and the actual failure continued progressing. The chronological evolution of both the electrical current and vibration spectra is presented to conduct an in-depth tracking of the fault. The diagnosis is achieved through spectral analysis of the stator currents, where fault frequency components related to rotor mechanical unbalance are identified. This is confirmed by the vibration analysis, which provides insightful information on the health of the drive train. These results can be implemented in condition monitoring strategies, which is of great interest to optimise operation and maintenance costs of wind farms.