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The article contains an overview of methods for diagnostics of malfunctions in induction motors (IMs). Based on the review of information sources, it is shown that there are no methods, hardware or software complexes that make it possible to determine the malfunctions of windings of induction motors during their operation. In this paper, the technique that allows us to determine the location of faults in the windings of an IM, as well as to predict the development of faults, is purposed. In this paper, scientific justification for the procedure of diagnostics for the development and identification of malfunctions in the windings of AD is given. The procedure is based on recording of real phase supply voltages, consumed currents, and simulating the resultant rotating magnetic field of the motor on their basis, as well as energy characteristics and their subsequent comparison with the resulting rotating magnetic field of the engine with obviously serviceable and faulty windings on the grounds determining the distortions of the rotating magnetic field of the stator, and by the fault indicators of the windings. The investigation problem is formulated. The problem consists in developing diagnostic signs of malfunctions in the stator winding and rotor windings from the oscillograms of phase voltages and currents registered during normal operation of the electric drive. The criterion of problem solving is obtaining the identifiers (signs) of the short-circuiting malfunctions and conductor breaking of stator winding i-th phases, short-circuited rotor rod breaking and deteriorating of the motor magnetic system. The coordinates of the vector of the stator magnetic flux on the complex plane, which determine the shape of its hodograph; effective phase currents values, full, active and reactive powers, energy conversation efficiency and cos φ values are taken as identifiers. The problem is solved by mathematical modeling of the resultant rotating magnetic field and its components in terms of the magnitude of the stator phase currents, magnetizing currents and rotor currents, as well as the values of the energy conversation efficiency and cos φ of the asynchronous motor operating in symmetric and asymmetric modes. An example of the solution of the problem with the application of the proposed method and the developed software package is given.


Asynchronous motor, diagnostics, motor windings, motor winding malfunctions, simulation, identification, software complex.

Rif G. Mugalimov

D.Sc. (Eng.), Associate Professor, Professor, Department of Industrial Power Supply, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it..

Аliya R. Mugalimova

Ph.D. (Eng.), Engineer, Limited Liability Company MSTU – Energy Saving +, Magnitogorsk, Russia. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it..

Yurij А. Kalugin

Undergraduate student, Nosov Magnitogorsk State Technical Unversity, Magnitogorsk, Russia. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it..

Konstantin E. Odintsov

Ph.D. (Eng.), Associate Professor, Department of Industrial Power Supply, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia.

1. Elektrotekhnika [Electrical engineering]. Textbook for universities. Ed. V.S. Panityushin. Moscow, 1976. 560 p. (In Russian)

2. GOST 8865-93. Electrical insulation systems. Malfunction evaluation and classification. (In Russian)

3. GOST 7217-87. Electric rotating machines. The engines are asynchronous. Test methods. (In Russian)

4. Barkov А.V., Borisov А.А. Possibilities of diagnostics for machines with electric drive using motor current. Metallurgicheskie protsessy i oborudovanie [Metallurgical processes and equipment]. 2013, no. 1 (31), pp. 61-65. (In Russian)

5. Obaid R.R., Habelter T.G., Stack J.R. Stator current analysis for bearing damage detection in induction motors. The 4th IEEE International symposium on diagnostics for electrical machines, power electronics and drives, SDEMPED 2003. Proceedings. New Jersey, 2003, pp. 182-187.

6. Silva J.L.H., Cardoso A.J.M. Bearing failures diagnosis in three-phase induction motors by extended Park’s vector approach. The 31st Annual Conference of IEEE Industrial Electronics Society (IECON). 2005, pp. 2591-2596.

7. Onel I.Y., Dalci K.B., Senol I. Detection of outer raceway bearing defects in small induction motors using stator current analysis. Sadhana-Academy Proceedings in Engineering Sciences. 2005, vol. 30(6), pp. 713-722.

8. Kuptsov V.V., Petushkov M.Yu., Sarvarov А.S. Sovremennye metody diagnostirovaniya asinkhronnykh dvigatelej i ikh razvitie [Modern methods of asynchronous motor diagnostics]. Magnitogorsk: Nosov Magnitogorsk State Technical University, 2010. 247 p. (In Russian)

9. Bryakin I.V., Bochkarev I.V., Kelebaev K.K. Diagnostics of AC electrical machines. Elektrotekhnichskie sistemy i kopmleksy [Electrotechnical systems and complexes]. 2017, no. 4(37), pp. 38-44. (In Russian)

10. Malatsion А.S., Malatsion N.V. Control of power characteristics of induction motors equipped with frequency converter in manufacturing environment. Trudy IX Mezhdunarodnoj (XX Vserossijskoj) konferentsii po avtomatizirovannomu ehlektroprivodu. АEHP-2016 [Proceedings of IX (XX All Russian) conference on automatic electric drive]. Perm, 3-7 October, 2016. Perm, 2016, pp. 68-70. (In Russian)

11. Gurin YA.S., Kuznetsov V.I., Proektirovanie serij ehlektricheskikh mashin [Design of electrical machines]. Moscow: Energiya, 1978. 480 p. (In Russian)

12. Bessonov L.А. Teoreticheskie osnovy ehlektrotekhniki [Fundamentals of electrical engineering]. Moscow: Vysshaya shkola, 1964. 480 p. (In Russian)

13. Bentley J.L. Multidimensional binary search trees used for associative searching. Communications of the ACM. 1975, vol. 18 (9), pp. 509-517.

14. Breiman L., Friedman J.H., Olshen R.A., Stone C.J. Classifi-cation and regression trees. Monterey, CA: Wadsworth & Brooks/Cole Advanced Books & Software. 1984. P. 368.

15. Cortes C., Vapnik V. Support-vector networks. Machine Learning. 1995, vol. 20, pp. 273-297.

16. Kravchik А.Eh., SHlaf M.M., Аfonin V.I., Sabolenskaya E.А. Аsinkhronnye dvigateli serii 4А [Asynchronous motors of 4A series]. Moscow: Energoizdat, 1982. 504 p.