Induction motor mixed fault diagnosis based on wavelet analysis of the current space vector

Broken bars and eccentricity are common faults in induction motors. These two faults usually occur simultaneously, since most installed induction motors have a small inherent eccentricity. In this paper a detailed investigation of the possibilities for induction motor fault diagnosis based on wavelet analysis of the current space vector is provided. The main objective is to formulate a method for enhanced diagnosis of broken rotor bars in induction motors by applying wavelet analysis to the motor current space vector. To this purpose, a detailed wavelet analysis of stator current space vector is implemented. The analysis is at first performed through simulation of a faulty asynchronous machine in Matlab-Simulink. Subsequent to the simulation results analysis, experimental tests were conducted. Characteristic results are presented and briefly discussed

[1]  Thomas G. Habetler,et al.  Evaluation and implementation of a system to eliminate arbitrary load effects in current-based monitoring of induction machines , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[2]  Jawad Faiz,et al.  Modeling and Dynamic Simulation of Induction Machine under Mixed Eccentricity Conditions using Winding Function , 2004 .

[3]  Mohamed Benbouzid,et al.  Induction motors' faults detection and localization using stator current advanced signal processing techniques , 1999 .

[4]  M. Haji,et al.  Pattern Recognition-A Technique for Induction Machines Rotor Broken Bar Detection , 2001, IEEE Power Engineering Review.

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

[6]  E. S. Saraiva,et al.  Computer aided detection of airgap eccentricity in operating three-phase induction motors, by Park's vector approach , 1991, Conference Record of the 1991 IEEE Industry Applications Society Annual Meeting.

[7]  Hamid A. Toliyat,et al.  Transient analysis of cage induction machines under stator, rotor bar and end ring faults , 1995 .

[8]  Zhe Zhang,et al.  Online rotor mixed fault diagnosis way based on spectrum analysis of instantaneous power in squirrel cage induction motors , 2004 .

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

[10]  Christian Kral,et al.  Sequences of field-oriented control for the detection of faulty rotor bars in induction machines-the Vienna Monitoring Method , 1998, IEEE Trans. Ind. Electron..

[11]  Pragasen Pillay,et al.  A new algorithm for transient motor current signature analysis using wavelets , 2003 .

[12]  David G. Dorrell,et al.  Analysis of airgap flux, current and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors , 1995, IAS '95. Conference Record of the 1995 IEEE Industry Applications Conference Thirtieth IAS Annual Meeting.

[13]  C. Kral,et al.  Detection of mechanical imbalances of induction machines without spectral analysis of time-domain signals , 2004, IEEE Transactions on Industry Applications.

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

[15]  W. Deleroi,et al.  Der Stabbruch in Kräfigläufer eines Asynchronmotors. I: Beschreibung mittels Uberlagerung eines Störfeldes , 1984 .

[16]  C. Hargis Steady-state analysis of 3-phase cage motors with rotor-bar and end-ring faults , 1983 .

[17]  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.

[18]  Mohamed Benbouzid,et al.  Monitoring and diagnosis of induction motors electrical faults using a current Park's vector pattern learning approach , 2000 .

[19]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Alireza Sadeghian,et al.  Current signature analysis of induction motor mechanical faults by wavelet packet decomposition , 2003, IEEE Trans. Ind. Electron..

[21]  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 .

[22]  T.A. Lipo,et al.  Complex vector model of the squirrel cage induction machine including instantaneous rotor bar currents , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[23]  W. T. Thomson,et al.  Vibration and current monitoring for detecting airgap eccentricity in large induction motors , 1986 .

[24]  J. Penman,et al.  Condition monitoring of electrical drives , 1986 .

[25]  W. T. Thomson,et al.  On-line current monitoring and application of a finite element method to predict the level of static airgap eccentricity in three-phase induction motors , 1998 .

[26]  Gary G. Yen,et al.  Wavelet packet feature extraction for vibration monitoring , 2000, IEEE Trans. Ind. Electron..

[27]  J. S. Hsu,et al.  Monitoring of defects in induction motors through air-gap torque observation , 1995 .

[28]  Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part I , 1985, IEEE Transactions on Industry Applications.

[29]  Chanan Singh,et al.  Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part II , 1985, IEEE Transactions on Industry Applications.

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

[31]  B. Szabados,et al.  Shaft current in AC induction machine: an on line monitoring system and prediction rules , 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).