The Diagnostics of Induction Motor Broken Rotor Bars on the Basis of the Electromotive Force Analysis


, ,

Series: Energy Science, Engineering and Technology
BISAC: TEC065000

Under the conditions of increased energy resources consumption, the researchers around the world face the problem of rational energy use. One of the ways to solve this problem consists of introducing energy saving technologies into the operation of electrotechnical and electromechanical devices. The operation of electric machines (EM) is very often accompanied by the occurrence of various damages. It results in increased energy consumption, untimely failure of electromechanical systems and, consequently, growth of material expenditure. Operation efficiency of electric equipment can be improved due to timely diagnostics of EM damages at early stages of their development. It is for this reason that research in diagnostics of EMs containing induction motors (IM) is of special interest nowadays.
Researchers succeeded in searching for efficient methods of IM diagnostics that are mostly suitable for particular conditions and modes of equipment operation. There are different methods for diagnostics of induction motor broken rotor bars. However, the analysis of conventional diagnostics methods revealed that most of them require the removal of the induction motor from the operation process and its disassembling. Presently, such methods of IM broken rotor bars diagnostics in operation modes such as methods of currents spectral analysis, the analysis of zero-phase sequence voltages, and the analysis of external magnetic field parameters are known. Nevertheless, these methods do not provide satisfactory results during diagnostics under a no-load condition and do not take into account that low-quality voltage of the supply network and the fluctuation of load level influence the diagnostic results. Besides, the results of the Fourier transform of current signals does not allow for unambiguous identification of the number and relative position of IM broken rotor bars. Hence, the development of the method for diagnostics of IM broken rotor bars is a topical scientific and applied problem.
A method for diagnostics of IM broken rotor bars on the basis of the analysis of electromotive force (EMF) in the stator windings is presented in the monograph. To research IM as a diagnostics object, the circuit mathematical models and those related to the final element method have been developed. The efficiency of the use of the wavelet analysis of the EMF signal in the stator windings under IM self-running-out condition has been demonstrated. A method for EMF signal decomposition with the use reverse z-transform theory has been proposed to improve the reliability of damaged diagnostics.
The presented monograph contains theoretical and experimental research that made it possible to solve the topical scientific problem of improving the efficiency of IM broken rotor bars with the use of the signal of electromotive force wavelet analysis in the stator windings under the motor self-running-out condition. (Imprint: Nova)

Table of Contents

Table of Contents

Abbreviations List

Main Symbols


Chapter 1. The Contemporary State of the Problem of Diagnostics of Induction Motor Broken Rotor Bars

Chapter 2. Theoretical Foundation for the Research of Induction Motor Broken Rotor Bars in the Self-Running-Out Condition

Chapter 3. Mathematical Models for the Research of the Method of Induction Motor Broken Rotor Bars Diagnostics

Chapter 4. The Method of Induction Motor Broken Rotor Bars Diagnostics with the Use of Wavelet Transform

Chapter 5. The Experimental Verification of the Method for the Diagnostics of Induction Motor Broken Rotor Bars




Author Contact Information



[1] Aderiano M. da Silva, Povinelli J. Richard, Demerdash A. O. Nabeela. Induction Machine Broken Bar and Stator Short-Circuit Fault Diagnostics Based on Three-Phase Stator Current Envelopes. IEEE Transactions On Industrial Electronics. – Vol. 55, No. 3. – P. 1310–1318.
[2] Amine Y., Henao Humberto, Capolino Gérard-André. Broken Rotor Bars Fault Detection in Squirrel Cage Induction Machines. IEEE. – 2005. –P. 741–747.
[3] Zagirnyak M., Kalinov A., Melnykov V. Sensorless vector-control system with the correction of stator windings asymmetry in induction motor. Przeglad Elektrotechniczny. – 2013. – Vol. 89, No. 12. – P. 340–343.
[4] Zagirnyak М., Chumachova A., Kalinov A. Correction of operating condition of a variable-frequency electric drive with a non-linear and asymmetric induction motor. Proceedings of International IEEE Conference EUROCON. – 2013. –
P. 1033–1037.
[5] Zagirnyak M., Mamchur D., Kalinov A. Comparison of induction motor diagnostic methods based on spectra analysis of current and instantaneous power signals. Przeglad Elektrotechniczny. – 2012. – Vol. 12b. – P. 221–224.
[6] Panadero Rubén P., Llinares J. P., Alarcon V. C., Pineda S. M. Review Diagnosis Methods of Induction Electrical Machines based on Steady State Current. Department of Electrical Engineering, Polytechnic University of Valencia Campus of Vera. – Valencia (Espaсa). – 2011. – P. 45–53.
[7] Kucheruk V. Yu. Elements of the theory of building technical diagnostics systems of electric motors. Monograph. – Vinnytsya: Universam–Vinnytsya, 2003. – 195 p.
[8] Shyrnin I. G., Tkachuk A. N. Short-circuited windings of rotors of engines of underground machines. Proceedings of the Lugansk Branch of the International Academy of Informatics: Scientific Journal. – 2000.– Issue 2 (9). – P. 97–104.
[9] Ying Xie. Performance Evaluation and Thermal Fields Analysis of Induction Motor With Broken Rotor Bars Located at Different Relative Positions. College of Electrical and Electronic Engineering, Harbin University of Science and Technology, China, IEEE Transactions on Magnetics. – 2010. – Vol. 46, No. 5. – P. 1243–1250.
[10] Oviedo S. J., Quiroga J. E., Borrás C. Experimental Evaluation of Motor Current Signature and Vibration Analysis for Rotor Broken Bars Detection in an Induction Motor. Proceedings of the 2011 International Conference on Power Engineering, Energy and Electrical Drives. – May 2011. – P. 125–131.
[11] Zagirnyak M. V., Mamchur D. G., Kalinov A. P., Chumachova A. V. Diagnostics of induction motors based on analysis of the power consumption signal. Monograph. – Kremenchuk: PP Shcher-batykh O. V., 2013. – 208 p.
[12] Nemec M., Drobnič K., Nedeljković D., Fišer R., Ambrožič V. Detection of Broken Bars in Induction Motor Through the Analysis of Supply Voltage Modulation. IEEE Transactions On Industrial Electronics. – 2010. – Vol. 57, No. 8. – P. 2879–2888.
[13] Gashimov M. A., Gadzhiev G. A., Mirzoev S. M. Diagnostics of eccentricity and breakage of rotor rods in asynchronous motors without their disconnection. Elektrotekhnika. – 1998. – No. 10. – P. 46–51.
[14] Pineda-Sanchez M., Riera-Guasp M. J., Antonino-Daviu A., Roger-Folch J., Perez-Cruz J., Puche-Panadero R. Instantaneous Frequency of the Left Sideband Harmonic During the Start-Up Transient: A New Method for Diagnosis of Broken Bars. IEEE Transactions On Industrial Electronics. – 2009. – Vol. 56, No. 11. – PP. 4557–4570.
[15] Caner Aküner, Temiz Ismail. Symmetrically broken rotor bars effect on the stator current of squirrel-cage induction motor. Przegląd Elektrotechniczny (Electrical Review). – 2011. – No. 3. – P. 313–314.
[16] Calis H., Unsworth P. J. Fault diagnosis in induction motors by motor current signal analysis. Proceedings SDEMPED. – 1999. – P. 237–241.
[17] Mehala N., Dahiya R. Condition monitoring methods, failure identification and analysis for Induction machines. International Journal of Circuits, Systems and Signal Processing. – 2009. – Issue 1, Vol. 3. –P. 10–17.
[18] Mehala N., Dahiya R. Motor current signature analysis and its applications in induction motor fault diagnosis. International journal of systems applications, engineering & development. – 2007. – No. 1. – Р. 29–35.
[19] Thomson William T. On-Line Motor Current Signature Analysis Prevents Premature Failure of large Induction Motor Drives. IEEE. – 2009. – Vol. 24. – P. 30–35.
[20] Thomson William T., Gilmore Ronald J. Motor Current Signature Analysis To Detect Faults In Induction Motor Drives. Proceedings Of The Thirty-Second Turbomachinery Symposium. – 2003. – P. 145–156.
[21] Vaimann T., Ants K. Detection of broken rotor bars in three-phase squirrel-cage induction motor using fast Fourier transform//10th International Symposium “Topical Problems in the Field of Electrical and Power Engineering” Pärnu, Estonia. – 2011. – P. 52–56.
[22] Zagirnyak M., Mamchur D., Kalinov A. A comparison of informative value of motor current and power spectra for the tasks of induction motor diagnostics. Proceedings of 2014 IEEE 16th International Power Electronics and Motion Control Conference and Exposition (PEMC). – Antalya, Turkey, 2014. – P. 541–546.
[23] Zagirnyak M., Mamchur D., Kalinov A. Induction motor diagnostic system based on spectra analysis of current and instantaneous power signals. Proceedings of SOUTHEASTCON. – Lexington, USA, 2014. – P. 1–7.
[24] Kral C., Haumer A., Grabner C. Modeling and Simulation of Broken Rotor Bars in Squirrel Cage Induction Machines. Proceedings of the World Congress on Engineering. – WCE 2009, London. – Vol 1. – P. 1–6.
[25] Ceban A., Pusca R. and Romary R. Study of Rotor Faults in Induction Motors Using External Magnetic Field Analysis. IEEE Transactions on Industrial Electronics. – 2012. – Vol. 59, No. 5. – P. 2082–2093.
[26] Ordaz-Moreno Alejandro, Romero-Troncoso Rene de Jesus, Vite-Frias Jose Alberto, Rivera-Gillen Jesus Rooney, Garcia-Perez Arturo. Automatic Online Diagnosis Algorithm for Broken Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation. IEEE Transactions on Industrial Electronics. – 2008. – Vol. 55, No. 5. –P. 2193–2202.
[27] Jose Antonino-Daviu A., Riera-Guasp M., Folch José Roger, Palomares M. Pilar M. Validation of a New Method for the Diagnosis of Rotor Bar Failures via Wavelet Transform in Industrial Induction Machines. IEEE Transactions On Industry Applications. –2006. – Vol. 42, No. 4. – P. 990–996.
[28] Kechida R. Menacer A. DWT Wavelet Transform for the Rotor Bars Faults Detection in Induction Motor. Electric Power and Energy Conversion Systems (EPECS). – 2nd International Conference. – 2011. – P. 1–5.
[29] Keskes H., Braham A., Lachiri Z. Broken Rotor Bar Diagnosis in Induction Machines through Stationary Wavelet Packet Transform under Lower Sampling Rate. First International Conference on Renewable Energies and Vehicular Technology. – 2012. – P. 452–459.
[30] Khadim Main S., Giri V. K. Broken Rotor Bar Fault Detection in Induction Motors Using Wavelet Transform. International Conference on Computing, Electronics and Electrical Technologies. – 2012. – P. 1–6.
[31] Mehala N., Dahiya R. Rotor Faults Detection in Induction Motor by Wavelet Analysis. International Journal of Engineering Science and Technology. – 2009. – Vol. 1(3). – P. 90–99.
[32] Riera-Guasp M., Jose A. Antonino-Daviu, Pineda-Sanchez M., Puche-Panadero R., Perez-Cruz J. A General Approach for the Transient Detection of Slip-Dependent Fault Components Based on the Discrete Wavelet Transform. IEEE Transactions on Industrial Electronics. – 2008. – Vol. 55, No. 12. – P. 4167–4180.
[33] Wei Y., Shi B., Cui G., Yin J. Broken Rotor Bar Detection in Induction Motors via Wavelet Ridge. International Conference on Measuring Technology and Mechatronics Automation. – 2009. – P. 625–628.
[34] Faiz J., Ebrahimi B. M. Mixed fault diagnosis in three-phase squirrel-cage induction motor using analysis of air-gap magnetic field. Progress In Electromagnetics Research. – 2006. – P. 239–245.
[35] Zouzou Salah E., Khelif Samia, Halem Noura, Sahraoui M. Analysis of Induction Motor with broken rotor bars Using Finite Element Method. Electrical Engineering Laboratory of Biskra. – 2011. – P. 1–5.
[36] Matic D., Kulic F., Alarcon V. C., Puche-Panadero R. Artificial neural networks broken rotor bars induction motor fault detection. 10th Symposium on Neural Network Applications in Electrical Engineering. – 2010. doi: 10.1109/NEUREL.2010.5644051.
[37] Altug S., Yuen C. Mo, Joel Trussell H. Fuzzy Inference Systems Implementedon Neural Architectures for Motor Fault Detection and Diagnosis. IEEE Transactions On Industrial Electronics. – Vol. 4, No. 6. – 1999. –P. 1132–1136.
[38] Aroui T., Koubaa Y., Toumi A. Application of Feedforward Neural Network for Induction Machine Rotor Faults Diagnostics using Stator Current. Research Unity of Industrial Process Control. – Vol. 3, No. 4. – 2007.–P. 213–226.
[39] Bayir R., Bay O. F. Kohonen Network based fault diagnosis and condition monitoring of serial wound starter motor. IJSIT Lecture Note of International Conferense on Intelligent Knowledge Systems. – Vol. 1, No. 1. – 2004. – P. 130–136.
[40] Cupertino F., Giordano V., Mininno E., Salvatore L. Application of Supervised and Unsupervised Neural Networks for Broken Rotor Bar Detection in Induction Motors. Polytechnic University of Bari V. Orabona, Bari, Italy. – 2001. –P. 1895–1901.
[41] Mazur D. Detection of Broken Rotor Bars in Induction Motors Using Unscented Kalman Filters. Proceedings of the 2nd International Congress on Computer Applications and Computational Science. – 2011. –P. 503–511.
[42] Dias C. G., Chabu I. E., Bussab M. A. Hall Effect Sensor and Artificial Neural Networks Applied on Diagnosis of Broken Rotor Bars in Large Induction Motors. IEEE International Conference on Computational Intelligence for Measurement Systems and Applications La Coruna. – 2006. –P. 34–39.
[43] Seyed Abbas T., Malekpour M. A Novel Technique for Rotor Bar Failure Detection in Single-Cage Induction Motor Using FEM and MATLAB/SIMULINK. Mathematical Problems in Engineering. Hindawi Publishing Corporation. – 2011. – Vol. 3. – P. 14–22.
[44] Zagirnyak M. V. Electromagnetic calculations. Textbook. – Khar’kov: Typohrafyya Madryd, 2015. – 320 p.
[45] Ivanov-Smolensky A. Electrical Machines. – Мoscow: MIR Publishers, 1983. – 280 p.
[46] Zagirnyak М. V., Prus V. V., Nevzlin B. I. Functional interrelation of the parameters of electric machines, devices and transformers with a generalized linear dimension. Monograph. – Khar’kov: Izdatel’stvo «Tochka», 2014. – 188 p.
[47] Zagirnyak M. V., Almashakbeh Atef S., Qawaqzeh M. Z. Functional interrelation of the parameters of electric machines, devices and transformers. – Nova Science Publishers, 2017. –
201 p.
[48] Cupertino F., de Vanna E., Salvatore L. and Stasi S. Analysis Techniques for Detection of IM Broken Rotor Bars After Supply Disconnection. IEEE Transactions On Industry Applications. – 2004. – Vol. 40, No. 2. – P. 526–533.
[49] Vaskovskyi J. M., Kovalenko M. A. Diagnostics of latent defects of the short-circuited rotor winding of asynchronous motor by an induction method. Technical Electrodynamics. – 2013. – No. 2. – P. 69–74.
[50] Vaskovskyi J. M. Field analysis of electrical machines. Textbook. – K.: NTUU “KPI”, 2007. – 192 p.
[51] Boule O. B. Methods for calculating the magnetic systems of electrical apparatus, magnetic circuit, field and program FEMM. Textbook. – M.: Izdatel’skyy tsentr «Akademiya», 2005. – 336 p.
[52] Singiresu S. Rao. The Finite Element Method in Engineering. – Butterworth-Heinemann, 2010. – 726 p.
[53] Al-Mashakbeh Atef S., Mamchur D., Kalinov A., Zagirnyak M. A diagnostic of induction motors supplied using frequency converter basing on current and power signal analysis. Przegląd Elektrotechniczny. –2016. – No 12. – P. 5–8.
[54] Zagirnyak М., Mamchur D., Kalinov A., Al-Mashakben Atef S. Induction motors faulth detection based on instantaneous power spectrum analysis with elimination of the supply mains influence. ACEEE International Journal on Electrical and Power Engineering. – 2013. – Vol. 4, No. 3. – P. 7–17.
[55] Qawaqzeh M. Z., Kalinov A., Loyous V., Zagirnyak M. Experimental research of the loading system for an induction motor with the use of a double-fed machine. Przegląd Elektrotechniczny. – 2017. – No. 1. – P. 173–176.
[56] Zagirnyak M. V., Rodkin D. I., Romashykhin Iu. V., Chornyi O. P. Energy method identification of induction motors. – Kremenchug: ChP. Shcherbatyh A. V., 2013. – 164 p.
[57] Arezki M., Naît-Saïd Mohamed-Saïd, Benakcha A Hamid, Drid Saïd. Stator Current Analysis Of Incipient Fault Into Asynchronous Motor Rotor Bars Using Fourier Fast Transform. Journal of Electrical Engineering. – Vol. 55, No. 5–6. – 2004. – P. 122–130.
[58] Benbouzid Mohamed El Hachemi., Vieira Michelle, Theys Céline. Induction Motors’ Faults Detection and Localization Using Stator Current Advanced Signal Processing Techniques. IEEE Transactions On Power Electronics. –1998. – Vol. 14. – P. 4–11.
[59] Mallat S. A Wavelet Tour of Signal Processing: The Sparse Way. – Academic Press, 2008. – 832 p.
[60] Zagirnyak M., Romashykhina Zh., Kalinov A. Diagnostic signs of induction motor broken rotor bars in electromotive force signal. Proceedings of 17th International Conference Computational Problems of Electrical Engineering. – 2016. – P. 1–4. doi: 10.1109/CPEE.2016.7738722.
[61] Strang G., Nguyen T. Wavelets and Filter Banks. – SIAM, 1996. –490 p.
[62] Chui Charles K. An Introduction to Wavelets. – Elsevier, 2016. –278 p.
[63] Zagirnyak M., Romashihina Zh. , Kalinov A. Diagnostic of broken rotor bars in induction motor on the basis of its magnetic field analysis. Acta Technica Jaurinensis. – 2013. – Vol. 6, No. 1. – P. 115–125.
[64] Zagirnyak M., Romashykhina Zh. , Kalinov A. Analysis of the induction motor magnetic field for diagnostics of rotor bar damages. 4th Symposium on Applied Electromagnetics. – 2012. – Р. 87–88.
[65] Daubechies I. Ten Lectures on Wavelets. – Society for Industrial and Applied Mathematics, 1992. – 254 р.
[66] Cabanas F., Glez F. Pedrayes, González M. Ruiz, Melero M. G., Orcajo G. A., Cano J. M., Rojas C. H. A new On-Line Method for the Early Detection of Broken Rotor Bars in Asynchronous Motors Working under Arbitrary Load Conditions. IEEE. – 2005. – P. 662–669.
[67] Dede E. M., Lee J., Nomura T. Multiphysics Simulation: Electromechanical System Applications and Optimization. – Springer, 2014. – 212 p.
[68] Tyukov V. A., Pastuhov V. V., Korneev K. V. Three-drum model for determining the diameter of the rod of a short-circuited rotor of an induction motor. Izvestiya Tomskogo politehnicheskogo universiteta. – 2011. – Vol. 319, No. 4. – P. 99–102.
[70] Zagirnyak M, Kalinov A., Romashykhina Zh. Decomposition of electromotive force signal of stator winding in induction motor at diagnostics of the rotor broken bars. Scientific Bulletin of National Mining University. – 2016. – No. 4 (154). – P. 54–61.
[71] Zagirnyak M., Romashykhina Zh., Kalinov A. The diagnostics of induction motors rotor bar breaks based on the analysis of electromotiveforce in the stator windings. Electrical engineering & Electromechanics. – 2014, No. 6. – P. 34–42.

The presented monograph will be useful for researchers in the field of electrical engineering, research engineers, lecturers, Ph.D. students, undergraduates who deal with research in the field of diagnostics of electric machines technical condition.

Publish with Nova Science Publishers

We publish over 800 titles annually by leading researchers from around the world. Submit a Book Proposal Now!