Detection of Localized Bearing Faults in Induction Machines by Spectral Kurtosis and Envelope Analysis of Stator Current

作者：Leite Valeria C M N^*; Borges da Silva Jonas Guedes; Cintra Veloso Giscard Francimeire; Borges da Silva Luiz Eduardo; Lambert Torres Germano; Bonaldi Erik Leandro; de Lacerda de Oliveira Levy Ely

来源：IEEE Transactions on Industrial Electronics, 2015, 62(3): 1855-1865.

DOI：10.1109/TIE.2014.2345330

• Ball bearings
• condition monitoring
• fault detection
• fault diagnosis
• induction motors
• kurtosis
• signal processing
• spectral analysis

Early detection of faults in electrical machines, particularly in induction motors, has become necessary and critical in reducing costs by avoiding unexpected and unnecessary maintenance and outages in industrial applications. Additionally, most of these faults are due to problems in bearings. Thus, in this paper, experimental bearing fault detection of a three-phase induction motor is performed by analyzing the squared envelope spectrum of the stator current. Spectral kurtosis-based algorithms, namely, the fast kurtogram and the wavelet kurtogram, are also applied to improve the envelope analysis. Experimental tests are performed, considering outer bearing faults at different stages, and the results are promising.

• 出版日期2015-3