DocumentCode
2718120
Title
Fault Detection in Induction Machines by Using Power Spectral Density on the Wavelet Decompositions
Author
Cusido, J. ; Rosero, Javier A. ; Romeral, Luis ; Ortega, J.A. ; Garcia, Alvaro
Author_Institution
MCIA Res. Group, Univ. Politecnica de Catalunya
fYear
2006
fDate
18-22 June 2006
Firstpage
1
Lastpage
6
Abstract
Motor current signature analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. This paper proposes a new approach to motor fault detection, by analyzing the spectrogram and further combination of wavelet and power spectral density techniques. Theoretical development and experimental results are presented to support the research
Keywords
asynchronous machines; fault diagnosis; wavelet transforms; fault detection; fault diagnosis; induction machines; load torque; motor current signature analysis; power spectral density; spectrogram; wavelet decompositions; Electrical fault detection; Fault detection; Fault diagnosis; Frequency; Induction machines; Induction motors; Rotors; Stators; Torque; Wavelet analysis; Electrical drives; Fault detection; Induction motor; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics Specialists Conference, 2006. PESC '06. 37th IEEE
Conference_Location
Jeju
ISSN
0275-9306
Print_ISBN
0-7803-9716-9
Type
conf
DOI
10.1109/PESC.2006.1712271
Filename
1712271
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