A Survey of Broken Rotor Bar Fault Diagnostic Methods of Induction Motor

Abstract Electrical machines, induction motors in particular, play a key role in domestic and industrial applications. They act as a work horse in almost every industry and are responsible for a big proportion of total generated electricity consumption worldwide. The faults in induction motors are degenerative in nature and can lead to a catastrophic situation if not diagnosed earlier. The failures can cause considerable financial loss in the form of unexpected downtime. Broken rotor bar is a very common and frequently occurring fault in most of industrial induction motors. To select a better, more accurate and reliable fault diagnostic technique, this paper presents a comprehensive literature survey on the existing motor current signature analysis (MCSA) based fault diagnostic techniques. Different well-known MCSA based fault diagnostic techniques are summarized in the form of basic theories, considering complexity of their implementation, merits and demerits.

[1]  Zeljko Kanovic,et al.  Low-Cost Diagnosis of Rotor Asymmetries in Induction Machines Working at a Very Low Slip Using the Reduced Envelope of the Stator Current , 2015, IEEE Transactions on Energy Conversion.

[2]  Rastko Fiser,et al.  Application of a finite element method to predict damaged induction motor performance , 2001 .

[3]  Vicente Climente-Alarcon,et al.  Reliable Detection of Rotor Winding Asymmetries in Wound Rotor Induction Motors via Integral Current Analysis , 2017, IEEE Transactions on Industry Applications.

[4]  António J. Marques Cardoso,et al.  Open-Circuit Fault Diagnosis in PMSG Drives for Wind Turbine Applications , 2013, IEEE Transactions on Industrial Electronics.

[5]  Dragan Matic,et al.  Support vector machine classifier for diagnosis in electrical machines: Application to broken bar , 2012, Expert Syst. Appl..

[6]  Hubert Razik,et al.  On the Use of Slot Harmonics as a Potential Indicator of Rotor Bar Breakage in the Induction Machine , 2009, IEEE Transactions on Industrial Electronics.

[7]  Y. Gritli,et al.  Diagnosis of mechanical unbalance for double cage induction motor load in time-varying conditions based on motor vibration signature analysis , 2013, 2013 International Conference on Renewable Energy Research and Applications (ICRERA).

[8]  Martin Riera-Guasp,et al.  Harmonic Order Tracking Analysis: A Speed-Sensorless Method for Condition Monitoring of Wound Rotor Induction Generators , 2016, IEEE Transactions on Industry Applications.

[9]  Farhad Haghjoo,et al.  Flux-based turn-to-turn fault protection for power transformers , 2016 .

[10]  B. Mirafzal,et al.  Effects of load magnitude on diagnosing broken bar faults in induction motors using the pendulous oscillation of the rotor magnetic field orientation , 2005, IEEE Transactions on Industry Applications.

[11]  C. Koley,et al.  Performance of a load-immune classifier for robust identification of minor faults in induction motor stator winding , 2014, IEEE Transactions on Dielectrics and Electrical Insulation.

[12]  Martin Riera-Guasp,et al.  The Harmonic Order Tracking Analysis Method for the Fault Diagnosis in Induction Motors Under Time-Varying Conditions , 2017, IEEE Transactions on Energy Conversion.

[13]  Don-Ha Hwang,et al.  High-Resolution Parameter Estimation Method to Identify Broken Rotor Bar Faults in Induction Motors , 2013, IEEE Transactions on Industrial Electronics.

[14]  Antonio J. Marques Cardoso,et al.  Active and Reactive Power Spectra-Based Detection and Separation of Rotor Faults and Low-Frequency Load Torque Oscillations , 2017, IEEE Transactions on Industry Applications.

[15]  A. Bellini,et al.  Quad Demodulation: A Time Domain Diagnostic Method for Induction Machines , 2007, 2007 IEEE Industry Applications Annual Meeting.

[16]  R. Bojoi,et al.  Maximum Efficiency per Torque Direct Flux Vector Control of Induction Motor Drives , 2015, IEEE Transactions on Industry Applications.

[17]  P. Granjon.  Electromagnetic vibrations estimation of an induction motor by nonlinear optimal filtering , 2005, 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[18]  R. Puche-Panadero,et al.  Cost-effective on-line fault diagnosis of induction motors using the reduced modulus of the current park's vector , 2017, 2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).

[19]  Sang Bin Lee,et al.  Influence of blade pass frequency vibrations on MCSA-based rotor fault detection of induction motors , 2017, 2016 IEEE Energy Conversion Congress and Exposition (ECCE).

[20]  H. M. Suryawanshi,et al.  Application of double Park's vector approach for detection of inter-turn fault in induction motor , 2015, 2015 International Conference on Condition Assessment Techniques in Electrical Systems (CATCON).

[21]  He Liu,et al.  Diagnosis of broken rotor bar fault in open- and closed-loop controlled wye-connected induction motors using zero-sequence voltage , 2017 .

[22]  A.J. Marques Cardoso,et al.  Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park's vector approach , 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).

[23]  M. Malekpour,et al.  Stator current envelope extraction for analysis of broken rotor bar in induction motors , 2017, 2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).

[24]  N. Mariun,et al.  Assessment of different voltage sags on performance of induction motors operated with shunt FACTS , 2012, 2012 3rd Power Electronics and Drive Systems Technology (PEDSTC).

[25]  Martin Riera-Guasp,et al.  Harmonic Order Tracking Analysis: A Novel Method for Fault Diagnosis in Induction Machines , 2015, IEEE Transactions on Energy Conversion.

[26]  Wilson Wang,et al.  A Spectrum Synch Technique for Induction Motor Health Condition Monitoring , 2015, IEEE Transactions on Energy Conversion.

[27]  Toomas Vaimann,et al.  Necessity for implementation of inverse problem theory in electric machine fault diagnosis , 2015, 2015 IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).

[28]  Jose Antonino-Daviu,et al.  Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories , 2017, IEEE Transactions on Industry Applications.

[29]  Hubert Razik,et al.  Detection and Diagnosis of Faults in Induction Motor Using an Improved Artificial Ant Clustering Technique , 2013, IEEE Transactions on Industrial Electronics.

[30]  B. Mirafzal,et al.  Induction machine broken-bar fault diagnosis using the rotor magnetic field space-vector orientation , 2004, IEEE Transactions on Industry Applications.

[31]  Arturo Garcia-Perez,et al.  FPGA-Based Online Detection of Multiple Combined Faults in Induction Motors Through Information Entropy and Fuzzy Inference , 2011, IEEE Transactions on Industrial Electronics.

[32]  R. Puche-Panadero,et al.  Improved Resolution of the MCSA Method Via Hilbert Transform, Enabling the Diagnosis of Rotor Asymmetries at Very Low Slip , 2009, IEEE Transactions on Energy Conversion.

[33]  Bimal K. Bose,et al.  Modern Power Electronics and AC Drives , 2001 .

[34]  Alessandro Goedtel,et al.  Diagnosis of Stator Faults Severity in Induction Motors Using Two Intelligent Approaches , 2017, IEEE Transactions on Industrial Informatics.

[35]  Dragan Matic,et al.  Fault Diagnosis of Rotating Electrical Machines in Transient Regime Using a Single Stator Current’s FFT , 2015, IEEE Transactions on Instrumentation and Measurement.

[36]  Misael Lopez-Ramirez,et al.  Novel FPGA-based Methodology for Early Broken Rotor Bar Detection and Classification Through Homogeneity Estimation , 2017, IEEE Transactions on Instrumentation and Measurement.

[37]  Luis Romeral,et al.  Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition , 2008, IEEE Transactions on Industrial Electronics.

[38]  Howard W. Penrose.  Test Methods for Determining the Impact of Motor Condition on Motor Efficiency and Reliability , 2001 .

[39]  Guillermo R. Bossio,et al.  Separating Broken Rotor Bars and Load Oscillations on IM Fault Diagnosis Through the Instantaneous Active and Reactive Currents , 2009, IEEE Transactions on Industrial Electronics.

[40]  Toomas Vaimann,et al.  Broken Rotor Bar Fault Diagnostic of Inverter Fed Induction Motor Using FFT, Hilbert and Park's Vector Approach , 2018, 2018 XIII International Conference on Electrical Machines (ICEM).

[41]  C. Koley,et al.  Application of wavelet transform to identify faulty IGBTs in 3-phase induction motor drives , 2014, Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC).

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

[43]  Gaëtan Didier,et al.  Rotor cage fault detection in induction motor using global modulation index on the instantaneous power spectrum , 2003, 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003..

[44]  Mohsen Bandar Abadi,et al.  Fault diagnostic algorithm for three-level neutral point clamped AC motor drives, based on the average current Park's vector , 2014 .

[45]  Angel Sapena-Bano,et al.  Multilayer Park's vector approach, a method for fault detection on induction motors , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).

[46]  Luo Yingli,et al.  Finite-Element Analysis of Field Distribution and Characteristic Performance of Squirrel-Cage Induction Motor With Broken Bars , 2006, IEEE Transactions on Magnetics.

[47]  Thomas A. Lipo,et al.  Modeling and Design of Controlled Current Induction Motor Drive Systems , 1977, IEEE Transactions on Industry Applications.

[48]  Mo-Yuen Chow,et al.  On the Use of a Lower Sampling Rate for Broken Rotor Bar Detection With DTFT and AR-Based Spectrum Methods , 2008, IEEE Transactions on Industrial Electronics.

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