Condition monitoring techniques for induction motors

Induction motors are used in various work environment and critical industrial processes, operating conditions and well-being of these machines need to be monitored to avoid potential failures. In this paper, an extensive literature review is conducted for condition monitoring techniques for induction motors. Various state-of-art techniques are presented and summarized under three categories: 1) signature extraction based approach, 2) model-based approach, and 3) knowledge-based approach. Advantages and drawbacks of several commonly used methods are demonstrated. Although research has been conducted in this area for several decades, condition monitoring and fault diagnosis of induction motors remains an active research area, especially recent emerging transition from traditional techniques to knowledge-based approach using artificial intelligent, which opens a pathway to an exciting new research direction.

[1]  H. Arabaci,et al.  Squirrel Cage of Induction Motors Simulation via Simulink , 2012 .

[2]  T. G. Habetler,et al.  An Evaluation of Model-Based Stator Resistance Estimation for Induction Motor Stator Winding Temperature Monitoring , 2002, IEEE Power Engineering Review.

[3]  Galina Mirzaeva,et al.  Comprehensive Diagnostics of Induction Motor Faults Based on Measurement of Space and Time Dependencies of Air Gap Flux , 2017, IEEE Transactions on Industry Applications.

[4]  C. Kral,et al.  Rotor temperature estimation of squirrel-cage induction motors by means of a combined scheme of parameter estimation and a thermal equivalent model , 2004, IEEE Transactions on Industry Applications.

[5]  Osama Mohammed,et al.  Complex-Vector Model of Interturn Failure in Induction Machines for Fault Detection and Identification , 2017, IEEE Transactions on Industry Applications.

[6]  Eliathamby Ambikairajah,et al.  Online technique for insulation assessment of induction motor stator windings under different load conditions , 2017, IEEE Transactions on Dielectrics and Electrical Insulation.

[7]  Raj Kumar Patel,et al.  Bearing Fault Classification Based on Wavelet Transform and Artificial Neural Network , 2013 .

[8]  Thomas G. Habetler,et al.  A Sensorless Rotor Temperature Estimator for Induction Machines Based on a Current Harmonic Spectral Estimation Scheme , 2008, IEEE Transactions on Industrial Electronics.

[9]  J. L. Kohler,et al.  Condition monitoring of stator windings in induction motors. II. Experimental investigation of voltage mismatch detectors , 2002 .

[10]  Jawad Faiz,et al.  Diagnosis methods for stator winding faults in three‐phase squirrel‐cage induction motors , 2014 .

[11]  Rastko Zivanovic,et al.  Condition Monitoring of an Induction Motor Stator Windings Via Global Optimization Based on the Hyperbolic Cross Points , 2015, IEEE Transactions on Industrial Electronics.

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

[13]  Derek A. Paice,et al.  Motor Thermal Protection by Continuous Monitoring of Winding Resistance , 1980, IEEE Transactions on Industrial Electronics and Control Instrumentation.

[14]  J. Sottile,et al.  Condition monitoring of stator windings in induction motors. I. Experimental investigation of the effective negative-sequence impedance detector , 2002 .

[15]  Thomas G. Habetler,et al.  A Remote and Sensorless Stator Winding Resistance Estimation Method for Thermal Protection of Soft-Starter-Connected Induction Machines , 2008, IEEE Transactions on Industrial Electronics.

[16]  T.G. Habetler,et al.  An on-line stator winding resistance estimation technique for temperature monitoring of line-connected induction machines , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[17]  D.G. Dorrell,et al.  Detection of inter-turn stator faults in induction motors using short term averaging of forwards and backwards rotating stator current phasors for fast prognostics , 2017, 2017 IEEE International Magnetics Conference (INTERMAG).

[18]  F.C. Trutt,et al.  On-line condition monitoring of induction motors , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[19]  Seyed Abbas Taher,et al.  A Novel Technique for Rotor Bar Failure Detection in Single-Cage Induction Motor Using FEM and MATLAB/SIMULINK , 2011 .

[20]  M. Riera-Guasp,et al.  Validation of a new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines , 2006, IEEE Transactions on Industry Applications.

[21]  Mohamed Sahraoui,et al.  Induction motors broken rotor bars detection using MCSA and neural network: experimental research , 2013, Int. J. Syst. Assur. Eng. Manag..

[22]  Mohammad Ebrahimi,et al.  Detection of stator winding faults in induction motors using three-phase current monitoring. , 2011, ISA transactions.

[23]  Alessandro Goedtel,et al.  A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors , 2015 .

[24]  Yukio Mizuno,et al.  Distinct Fault Analysis of Induction Motor Bearing Using Frequency Spectrum Determination and Support Vector Machine , 2017, IEEE Transactions on Industry Applications.

[25]  M. Ikeda,et al.  Simulation Studies of the Transients of Squirrel-Cage Induction Motors , 2007, IEEE Transactions on Energy Conversion.

[26]  D. Morinigo-Sotelo,et al.  Broken rotor bar detection in VSD-fed induction motors at startup by high-resolution spectral analysis , 2014, 2014 International Conference on Electrical Machines (ICEM).

[27]  Luis Romeral,et al.  Signal Injection as a Fault Detection Technique , 2011, Sensors.

[28]  Abderrezak Rezzoug,et al.  An induction motor model including the first space harmonics for broken rotor bar diagnosis , 2005 .

[29]  N. Tandon,et al.  A comparison of some condition monitoring techniques for the detection of defect in induction motor ball bearings , 2007 .

[30]  Sulochana Wadhwani,et al.  Fault classification for Rolling Element Bearing in Electric Machines , 2008 .

[31]  Thomas G. Habetler,et al.  A survey of condition monitoring and protection methods for medium voltage induction motors , 2009, 2009 IEEE Energy Conversion Congress and Exposition.

[32]  Andrea Cavagnino,et al.  Contribution to Offline Measurements of PMSM and SyRM Inductances , 2019, IEEE Transactions on Industry Applications.

[33]  Yi Wang,et al.  Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network , 2013, J. Intell. Manuf..

[34]  Kil To Chong,et al.  Vibration signal analysis for electrical fault detection of induction machine using neural networks , 2011, 2007 International Symposium on Information Technology Convergence (ISITC 2007).

[35]  Arturo Garcia-Perez,et al.  Automatic Online Diagnosis Algorithm for Broken-Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation , 2008, IEEE Transactions on Industrial Electronics.

[36]  T.G. Habetler Current-based motor condition monitoring: Complete protection of induction and PM machines , 2007, 2007 International Aegean Conference on Electrical Machines and Power Electronics.

[37]  Chrysostomos D. Stylios,et al.  A Symbolic Representation Approach for the Diagnosis of Broken Rotor Bars in Induction Motors , 2015, IEEE Transactions on Industrial Informatics.

[38]  Braz de Jesus Cardoso Filho,et al.  Evaluation of electrical insulation in three-phase induction motors and classification of failures using neural networks , 2016 .

[39]  Elhoussin Elbouchikhi,et al.  Induction Machines Fault Detection Based on Subspace Spectral Estimation , 2016, IEEE Transactions on Industrial Electronics.

[40]  Xin Wang,et al.  Research on Broken rotor bar Fault Diagnosis of Induction Motor Based on LabVIEW , 2011 .

[41]  T.G. Habetler,et al.  Fault classification and fault signature production for rolling element bearings in electric machines , 2004, IEEE Transactions on Industry Applications.

[42]  Chee Peng Lim,et al.  Fault Detection and Diagnosis of Induction Motors Using Motor Current Signature Analysis and a Hybrid FMM–CART Model , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[43]  Adel Ghoggal,et al.  Dynamic eccentricity in squirrel cage induction motors - Simulation and analytical study of its spectral signatures on stator currents , 2008, Simul. Model. Pract. Theory.

[44]  Thomas G. Habetler,et al.  Magnetic Effects of DC Signal Injection on Induction Motors for Thermal Evaluation of Stator Windings , 2011, IEEE Transactions on Industrial Electronics.

[45]  Ying Wu,et al.  Induction-motor stator and rotor winding temperature estimation using signal injection method , 2006, IEEE Transactions on Industry Applications.

[46]  V. Fernao Pires,et al.  Motor square current signature analysis for induction motor rotor diagnosis , 2013 .

[47]  Norman Mariun,et al.  Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review , 2011 .