Dynamic eccentricity in squirrel cage induction motors - Simulation and analytical study of its spectral signatures on stator currents

Most of faults in three-phase induction motors have relationship with airgap eccentricity. There are two forms of airgap eccentricity: static (SE) and dynamic (DE). According to the literatures, the well known signatures of dynamic eccentricity, on the stator current spectra, are sidebands around the principal slot harmonics (PSH). However, many other researches have shown that DE induces also spectral components around the fundamental, but few are reported on the sources and the causes of these components. In this direction and since it is difficult to study experimentally the DE separately from the SE; the present paper attempts to explain, analytically and by simulation, the generation process of all frequency components that are a function of only DE. For that reason, a detailed analytical study for three-phase induction motors working under DE is performed. This study is based on rotating field approach. A general theoretical analysis of the interaction between all harmonics of the eccentric airgap permeance and the stator and rotor MMF components is put forward. The simulation results, obtained from an accurate model, confirm the existence of specific frequency components around the fundamental, caused by the dynamic airgap eccentricity. The interactions between the DE and the inherent SE are also illustrated using this mathematical model.

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

[2]  J. Penman,et al.  Dynamic simulation of dynamic eccentricity in induction machines-winding function approach , 2000 .

[3]  I. Culbert,et al.  Using current signature analysis technology to reliably detect cage winding defects in squirrel cage induction motors , 2005 .

[4]  S. Ahmed,et al.  Detection of Rotor Slot and Other Eccentricity-Related Harmonics in a Three-Phase Induction Motor with Different Rotor Cages , 2001, IEEE Power Engineering Review.

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

[6]  Xianghui Huang,et al.  Using a Surge Tester to Detect Rotor Eccentricity Faults in Induction Motors , 2007, IEEE Transactions on Industry Applications.

[7]  Peter Tavner,et al.  Condition monitoring of electrical machines , 1987 .

[8]  H. Razik,et al.  Considerations about the modeling and simulation of air-gap eccentricity in induction motors , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[9]  Kil To Chong,et al.  Induction Machine Condition Monitoring Using Neural Network Modeling , 2007, IEEE Transactions on Industrial Electronics.

[10]  Antero Arkkio,et al.  DWT analysis of numerical and experimental data for the diagnosis of dynamic eccentricities in induction motors , 2007 .

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

[12]  Gojko Joksimovic,et al.  Dynamic simulation of cage induction machine with air gap eccentricity , 2005 .

[13]  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 .

[14]  Bong-Hwan Kwon,et al.  Online Diagnosis of Induction Motors Using MCSA , 2006, IEEE Transactions on Industrial Electronics.

[15]  C. Hansen,et al.  Estimation of Static Eccentricity Severity in Induction Motors for On-Line Condition Monitoring , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

[16]  A. J. Marques Cardoso,et al.  The Use of Instantaneous Phase-Angle Signature Analysis for Airgap Eccentricity Diagnosis in Three-Phase Induction Motors , 2007, 2007 International Conference on Power Engineering, Energy and Electrical Drives.

[17]  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.

[18]  W. Rhodes,et al.  Notice of Violation of IEEE Publication PrinciplesUsing Current Signature Analysis Technology to Reliably Detect Cage Winding Defects in Squirrel-Cage Induction Motors , 2007, IEEE Transactions on Industry Applications.

[19]  Hanifi Guldemir,et al.  Detection of airgap eccentricity using line current spectrum of induction motors , 2003 .

[20]  S. Nandi,et al.  Performance Analysis of a Three-Phase Induction Machine With Inclined Static Eccentricity , 2007, IEEE Transactions on Industry Applications.

[21]  A.M. Knight,et al.  Mechanical fault detection in a medium-sized induction motor using stator current monitoring , 2005, IEEE Transactions on Energy Conversion.

[22]  Girish Kumar Singh,et al.  Induction machine drive condition monitoring and diagnostic research—a survey , 2003 .

[23]  Gerardo G. Acosta,et al.  A current monitoring system for diagnosing electrical failures in induction motors , 2006 .

[24]  David G. Dorrell,et al.  ON-LINE CURRENT MONITORING TO DIAGNOSE AIRGAP ECCENTRICITY HISTORIES VERIFY THE PREDICTIONS IN LARGE THREE-PHASE INDUCTION MOTORS - INDUSTRIAL CASE , 1999 .

[25]  Mohamed Benbouzid,et al.  A review of induction motors signature analysis as a medium for faults detection , 1998, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200).

[26]  J. Faiz,et al.  Diagnosis of a Mixed Eccentricity Fault in a Squirrel-cage Three-phase Induction Motor using Time Stepping Finite Element Technique , 2007, 2007 IEEE International Electric Machines & Drives Conference.

[27]  B. Heller,et al.  Harmonic field effects in induction machines , 1977 .

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

[29]  H. A. Toliyat,et al.  Performance Analysis of a Three-Phase Induction Motor under Mixed Eccentricity Condition , 2002, IEEE Power Engineering Review.

[30]  H.A. Toliyat,et al.  Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review , 2005, IEEE Transactions on Energy Conversion.

[31]  Austin H. Bonnett,et al.  Rotor Failures in Squirrel Cage Induction Motors , 1986, IEEE Transactions on Industry Applications.

[32]  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.

[33]  Xianghui Huang,et al.  Detection of Rotor Eccentricity Faults in a Closed-Loop Drive-Connected Induction Motor Using an Artificial Neural Network , 2007, IEEE Transactions on Power Electronics.

[34]  Slim Tnani,et al.  Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines , 2006, IEEE Transactions on Industrial Electronics.

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

[36]  H. Razik,et al.  An improved model of the induction machine dedicated to faults detection extension of the modified winding function , 2005, 2005 IEEE International Conference on Industrial Technology.