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
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;
Conference_Titel :
Power Electronics Specialists Conference, 2006. PESC '06. 37th IEEE
Conference_Location :
Jeju
Print_ISBN :
0-7803-9716-9
DOI :
10.1109/PESC.2006.1712271
