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Link to publication on Research at Birmingham portal General rights Unless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. The express permission of the copyright holder must be obtained for any use of this material other than for purposes permitted by law. • Users may freely distribute the URL that is used to identify this publication. • Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. • User may use extracts from the document in line with the concept of 'fair dealing' under the Copyright, Designs and Patents Act 1988 (?) • Users may not further distribute the material nor use it for the purposes of commercial gain. Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.
As wind energy continues to develop with increasing wind turbine power capacities often deployed offshore, reducing operation and maintenance costs have become a critical aspect. Condition monitoring has been found to be the key to achieve this goal. Under this framework, the induction generator of a wind turbine is a major contributor to failure rates and downtime where doublyfed induction generators are the dominant technology employed. This paper presents a spectral analysis of a real doubly-fed induction generator of an inservice wind turbine. A one-year measurement campaign on an operating wind turbine has been used to perform the study. Three test cases representing different wind turbine operating conditions are presented to illustrate the results. All the peaks found in the spectra have been identified, and the frequency components related to electrical rotor unbalance have been found. The results show which components are more suitable for effective condition monitoring.
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