Fault diagnostics of induction motors based on internal flux measurement

A new fault diagnosis scheme based on the monitoring of main air gap flux of squirrel cage induction motors is proposed. Most of the existing flux monitoring techniques are based on the leakage or stray flux measurement outside of the motor. A few methods, however, use the main air gap flux as the fault signature, where search coils are used to monitor the derivative of the flux, which eventually introduces noise in the signal. Moreover, the diagnosis methods are mainly based on detecting a fault, whereas very little initiative has been taken to locate a fault precisely. To address these problems, a sophisticated yet robust condition monitoring and fault diagnosis method is needed. To this aim, we propose to monitor the main air gap flux using Hall Effect Flux Sensors (HEFS) at all the stator slots of an induction motor, which can be used to address the stator and rotor slot effects not only through frequency analysis of the magnetic flux, but also by magnitude and phase shift comparison of sensors located at different geometric positions around the stator. We have successfully detected the stator turn-to-turn fault at a very incipient stage and detected the location of the fault precisely. Promising results have been obtained through simulation in the case of broken rotor bar faults as well.

[1]  O.V. Thorsen,et al.  Failure identification and analysis for high voltage induction motors in petrochemical industry , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[2]  Humberto Henao,et al.  A frequency-domain detection of stator winding faults in induction machines using an external flux sensor , 2002 .

[3]  Don-Ha Hwang,et al.  Development of diagnosis algorithm for induction motor using flux sensor , 2008, 2008 International Conference on Condition Monitoring and Diagnosis.

[4]  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.

[5]  R. Romary,et al.  Eccentricity and broken rotor bars faults - Effects on the external axial field , 2010, The XIX International Conference on Electrical Machines - ICEM 2010.

[6]  Mario Vasak,et al.  Stator-Current Spectrum Signature of Healthy Cage Rotor Induction Machines , 2013, IEEE Transactions on Industrial Electronics.

[7]  M. Negrea Electromagnetic flux monitoring for detecting faults in electrical machines , 2006 .

[8]  H. Henao,et al.  Simplified axial flux spectrum method to detect incipient stator inter-turn short-circuits in induction machine , 2004, 2004 IEEE International Symposium on Industrial Electronics.

[9]  P. Bauer,et al.  Detection of eccentricity and bearings fault using stray flux monitoring , 2011, 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics & Drives.

[10]  Vitezslav Hajek,et al.  Effects of eccentricity on external magnetic field of induction machine , 2010, Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference.

[11]  W. T. Thomson,et al.  On-line diagnosis of stator shorted turns in mains and inverter fed low voltage induction motors , 2002 .

[12]  Gonzalo A. Orcajo,et al.  Unambiguous Detection of Broken Bars in Asynchronous Motors by Means of a Flux Measurement-Based Procedure , 2011, IEEE Transactions on Instrumentation and Measurement.

[13]  Don-Ha Hwang,et al.  Detection of air-gap eccentricity and broken-rotor bar conditions in a squirrel-cage induction motor using the radial flux sensor , 2008 .

[14]  G. Venchi,et al.  Development of a leakage flux measurement system for condition monitoring of electrical drives , 2011, 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics & Drives.

[15]  A. Arkkio,et al.  Electromagnetic flux-based condition monitoring for electrical machines , 2005, 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[16]  G. Mirzaeva,et al.  Performance evaluation of DC motors for electric rope shovels based on air gap flux measurement , 2009, 2009 Australasian Universities Power Engineering Conference.

[17]  Don-Ha Hwang,et al.  A Method for Rotor Vibration Monitoring of Induction Motor by Air-gap Flux Detection , 2006 .

[18]  J. Ilonen,et al.  Diagnosis tool for motor condition monitoring , 2005, IEEE Transactions on Industry Applications.

[19]  M. Ahmed,et al.  Comparison of stator current, axial leakage flux and instantaneous power to detect broken rotor bar faults in induction machines , 2008, 2008 Australasian Universities Power Engineering Conference.

[20]  R. Alves,et al.  Analysis of Air Gap Flux to Detect Induction Motor Faults , 2006, Proceedings of the 41st International Universities Power Engineering Conference.

[21]  S. Williamson The future of electrical machines , 2004, Proceedings. 2004 First International Conference on Power Electronics Systems and Applications, 2004..

[22]  Hiroyuki Mikami,et al.  Magnetic flux density analysis of wound rotor induction motor by permeance model , 2009, 2009 International Conference on Electrical Machines and Systems.

[23]  G. Venchi,et al.  A novel approach to detect short circuits in low voltage induction motor by stray flux measurement , 2012, 2012 XXth International Conference on Electrical Machines.

[24]  V. Kokko CONDITION MONITORING OF SQUIRREL-CAGE MOTORS BY AXIAL MAGNETIC FLUX MEASUREMENTS , 2003 .

[25]  Remus Pusca,et al.  Study of Rotor Faults in Induction Motors Using External Magnetic Field Analysis , 2012, IEEE Transactions on Industrial Electronics.

[26]  B. Ayhan,et al.  Multiple signature processing-based fault detection schemes for broken rotor bar in induction motors , 2005, IEEE Transactions on Energy Conversion.

[27]  G. Mirzaeva,et al.  A laboratory system to produce a highly accurate and uniform magnetic field for sensor calibration , 2012, 2012 IEEE International Conference on Industrial Technology.