Real‐time motor current signature analysis tool for undergraduate laboratory

The typical electrical engineering (EE) undergraduate curriculum is packed with foundational materials and offers limited room for other desirable materials that could be readily applied in the power industry. A Motor Current Signature Analysis (MCSA) tool is developed for effectively teaching the concepts of induction motor fault detection within one lecture or laboratory period. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 634–639, 2010; View this article online at wileyonlinelibrary.com; DOI 10.1002/cae.20263

[1]  W. T. Thomson,et al.  Current signature analysis to detect induction motor faults , 2001 .

[2]  C. Tassoni,et al.  Monitoring of induction Machines by maximum covariance method for frequency tracking , 2004, IEEE Transactions on Industry Applications.

[3]  M. E. H. Benbouzid,et al.  What Stator Current Processing Based Technique to Use for Induction Motor Rotor Faults Diagnosis , 2002, IEEE Power Engineering Review.

[4]  H. Khalil,et al.  Wavelet-based methods for the prognosis of mechanical and electrical failures in electric motors , 2005 .

[5]  David G. Dorrell,et al.  On-line current monitoring to diagnose airgap eccentricity in large three-phase induction motors-industrial case histories verify the predictions , 1999 .

[6]  Wenying Huang,et al.  A novel detection method of motor broken rotor bars based on wavelet ridge , 2003 .

[7]  B. Singh,et al.  A review of stator fault monitoring techniques of induction motors , 2005, IEEE Transactions on Energy Conversion.

[8]  Wenying Huang,et al.  A novel detection method of motor broken rotor bars based on wavelet ridge , 2003 .

[9]  E. A. Ebrahim,et al.  Fault analysis of current-controlled PWM-inverter fed induction-motor drives , 2003, Proceedings of the 7th International Conference on Properties and Applications of Dielectric Materials (Cat. No.03CH37417).

[10]  Girish Kumar Singh,et al.  Vibration signal analysis using wavelet transform for isolation and identification of electrical faults in induction machine , 2004 .

[11]  Mohamed El Hachemi Benbouzid.  A review of induction motors signature analysis as a medium for faults detection , 2000, IEEE Trans. Ind. Electron..

[12]  Tommy W. S. Chow,et al.  Induction machine fault diagnostic analysis with wavelet technique , 2004, IEEE Transactions on Industrial Electronics.