A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine

被引：0
|
作者：
Bouchikhi, El. H. [1 ]
Choqueuse, V. [1 ]
Benbouzid, M. E. H. [1 ]
Charpentier, J. F. [2 ]
Barakat, G. [3 ]
机构：
[1] Univ Brest, LBMS, EA 4325, Rue Kergoat,CS 93837, F-29238 Brest 03, France
[2] French Naval Acad, French Naval Acad Res Inst IRENav, EA 3634, F-29240 Brest 9, France
[3] Univ Le Havre, GREAH, Dept Elect Engn, F-76600 Le Havre, France
来源：
IECON 2011: 37TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2011年
关键词：
Wind turbine; fault detection; broken-rotor bars; signal processing; time-frequency representations; INDUCTION-MOTORS;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
To reduce the cost of wind energy, minimization and prediction of maintenance operations in wind turbine is of key importance. In variable speed turbine generator, advanced signal processing tools are required to detect and diagnose the generator faults from the stator current. To detect a fault in non-stationary conditions, previous studies have investigated the use of time-frequency techniques such as the Spectrogram, the Wavelet transform, the Wigner-Ville representation and the Hilbert-Huang transform. In this paper, these techniques are presented and compared for broken-rotor bar detection in squirrel-cage generators. The comparison is based on several criteria such as the computational complexity, the readability of the representation and the easiness of interpretation.
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页数：6
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