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Fault Diagnostic in Power System Using Wavelet Transforms and Neural Networks

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3 Author(s)
Charfi, F. ; Lab. d''Electron. et de Technol. de I''lnformation, Sfax ; Sellami, F. ; Al-Haddad, K.

This paper presents a new approach to Fault detection and diagnosis in power system. Discrete wavelet transformations (DWT) combined with neural networks (NN) have been applied to a typical three phase inverter. A set of faults have been examined, such as inverter IGBT open-circuit fault, leg open fault. The input signals of this algorithm are the three-phase stator currents. Identification and classification uses approximation and details at levels 6 of these currents. The results of simulation show that the proposed technique can accurately detect identify and classify effectively the faults of interest in the power system.

Published in:

Industrial Electronics, 2006 IEEE International Symposium on  (Volume:2 )

Date of Conference:

9-13 July 2006