Current Signature and Vibration Analyses to Diagnose an In-Service Wind Turbine Drive Train

Estefania Artigao, Sofia Koukoura, Andrés Honrubia-Escribano, James Carroll, Alasdair McDonald and Emilio Gómez-Lázaro
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Estefania Artigao: Renewable Energy Research Institute (IIER) and DIEEAC-EDII-AB, University of Castilla—La Mancha, 02071 Albacete, Spain
Sofia Koukoura: Department of Electric & Electronic Engineering, University of Strathclyde, Glasgow G11XV, UK
Andrés Honrubia-Escribano: Renewable Energy Research Institute (IIER) and DIEEAC-EDII-AB, University of Castilla—La Mancha, 02071 Albacete, Spain
James Carroll: Department of Electric & Electronic Engineering, University of Strathclyde, Glasgow G11XV, UK
Alasdair McDonald: Department of Electric & Electronic Engineering, University of Strathclyde, Glasgow G11XV, UK
Emilio Gómez-Lázaro: Renewable Energy Research Institute (IIER) and DIEEAC-EDII-AB, University of Castilla—La Mancha, 02071 Albacete, Spain

Energies, 2018, vol. 11, issue 4, 1-18

Abstract: 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.

Keywords: condition monitoring; current signature analysis; doubly-fed induction generator; gearbox; vibration analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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