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

Clicks: 166
ID: 142783
2018
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
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.
Reference Key
artigao2018energiescurrent Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Estefania Artigao;Sofia Koukoura;Andrés Honrubia-Escribano;James Carroll;Alasdair McDonald;Emilio Gómez-Lázaro
Journal acs combinatorial science
Year 2018
DOI
10.3390/en11040960
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.