Induction motor fault detection by spectral principal components analysis of the supply currents

A new method of obtaining diagnostic data from induction motors, derived from the three supply currents using principal components analysis, is presented in this paper. The techniques presented here focus on extracting relevant information from spectral matrices. These techniques are qualified as parsimonious tools for exploring the behaviour of current vector valued signals in the frequency domain with minimal loss of information. In fact, the new diagnostic method obtains data from the three stator currents by exploring special fault characteristic frequencies in the power spectral density of the first principal component. The main advantage of this new diagnostic tool is its ability to extract automatically the characteristic frequencies relative to the different machine operating modes. This is accomplished using the proportion of the power attributed to the first principal component and/or using the sensor contribution to the power at specific frequencies. Thus, the new diagnostic method gives a good basis for an automatic non intrusive condition monitoring for rotating machinery.

[1]  F. Filippetti,et al.  Quantitative evaluation of induction motor broken bars by means of electrical signature analysis , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[2]  D. R. Rankin The industrial application of phase current analysis to detect rotor winding faults in squirrel cage induction motors , 1995 .

[3]  A.M. Trzynadlowski,et al.  Instantaneous stator power as a medium for the signature analysis of induction motors , 1995, IAS '95. Conference Record of the 1995 IEEE Industry Applications Conference Thirtieth IAS Annual Meeting.

[4]  Li Ran,et al.  Monitoring torsional vibrations of electro-mechanical systems using stator currents , 1998 .

[5]  Andrzej M. Trzynadlowski,et al.  Comparative investigation of diagnostic media for induction motors: a case of rotor cage faults , 2000, IEEE Trans. Ind. Electron..

[6]  S. F. Legowski,et al.  Diagnostics of mechanical abnormalities in induction motors using instantaneous electric power , 1997, 1997 IEEE International Electric Machines and Drives Conference Record.

[7]  I. Zein,et al.  Non-invasive torque estimation for broken bar detection in induction motors , 2003, 2003 European Control Conference (ECC).

[8]  Gaëtan Didier,et al.  A new approach to detect broken rotor bars in induction machines by current spectrum analysis , 2007 .

[9]  Alberto Bellini,et al.  Quantitative Evaluation of Induction Motor Broken Bars By Means of Electric Signals Signatures , 2001 .

[10]  A. J. Marques Cardoso,et al.  Rotor Cage Fault Diagnosis in Three-Phase Induction Motors by Extended Park's Vector Approach , 2000 .

[11]  Jérôme Antoni,et al.  Quantitative analysis of noninvasive diagnostic procedures for induction motor drives , 2007 .

[12]  Gerald Burt Kliman,et al.  Methods of Motor Current Signature Analysis , 1992 .

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

[14]  Clemens Gühmann,et al.  Fault Diagnosis on Bearings of Electric Motors by Estimating the Current Spectrum , 1994 .

[15]  Mario Eltabach,et al.  Comparative Investigation of Electric Signal Analyses Methods for Mechanical Fault Detection in Induction Motors , 2007 .