Title :
Diagnosis of Broken-Bar Fault in Induction Machines Using Discrete Wavelet Transform Without Slip Estimation
Author :
Kia, Shahin Hedayati ; Henao, Humberto ; Capolino, Gérard-André
Author_Institution :
Dept. of Electr. Eng., Univ. of Picardie Jules Verne, Amiens, France
Abstract :
The aim of this paper is to present a wavelet-based method for broken-bar detection in squirrel-cage induction machines. The frequency-domain methods, which are commonly used, need speed information or accurate slip estimation for frequency-component localization in any spectrum. Nevertheless, the fault frequency bandwidth can be well defined for any squirrel-cage induction machine due to numerous previous investigations. The proposed approach consists in the energy evaluation of a known bandwidth with time-scale analysis using the discrete wavelet transform. This new technique has been applied to the stator-current space-vector magnitude and the instantaneous magnitude of the stator-current signal for different broken-bar fault severities and load levels.
Keywords :
asynchronous machines; discrete wavelet transforms; fault diagnosis; signal processing; squirrel cage motors; stators; broken-bar fault diagnosis; discrete wavelet transform; envelope detection; signal processong; slip estimation; squirrel-cage induction machines; stator-current signature analysis; AC motor protection; Hilbert transforms; amplitude modulation (AM); asynchronous rotating machines; envelope detection; fault diagnosis; induction motors; monitoring; signal processing; wavelet transforms;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2009.2018975