Analysis of the features of application of vibration diagnostic methods of induction motors of transportation infrastructure using mathematical modeling

• Autorzy: Gubarevych Oleg , Gerlici Juraj , Gorobchenko Oleksandr , Kravchenko Kateryna , Zaika Denys

Identyfikatory

DOI

10.29354/diag/161308

• Języki publikacji: EN

Abstrakty

EN

In the work, studies were carried out on the use of vibration diagnostic methods for monitoring the state of induction motors with a squirrel-cage rotor, operated in electric drives of transport equipment. The most common and difficult-todiagnose damage to an induction motor is turn-to-turn short circuits in the stator winding, which require timely determination and establishment of the degree of damage to prevent an emergency shutdown of the equipment. The main purpose of the study is to establish the most effective areas of application of vibration diagnostic methods in determining the technical condition of the stator of induction motors under load. The experiments were carried out using simulation modeling for cases of turn-to-turn short circuits in one and two phases simultaneously, as well as with the influence of a low-quality supply voltage system on vibration parameters. The results of the work are relevant for further improvement of systems for diagnostic control of drives of transport equipment to increase the efficiency and reliability of their work.

Słowa kluczowe

EN

vibration diagnostics; simulation modelling; induction motor; stator field asymmetry; turn-to-turn short circuits

PL

diagnostyka drgań; modelowanie symulacyjne; silnik indukcyjny; uzwojenie stojana; zwarcia zwojowe

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2023
• Tom: Vol. 24, No. 1
• Strony: art. no. 2023111
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Gubarevych Oleg

• Department of Electromechanics and Rolling Stock of Railways, State University of Infrastructure and Technologies (04071), Ukraine

• https://orcid.org/0000-0001-7864-0831

autor

Gerlici Juraj

• Department of Transport and Handling Machines, University of Žilina, Univerzitná 8215/1 (010 26) Žilina, Slovakia

• https://orcid.org/0000-0003-3928-0567

autor

Gorobchenko Oleksandr

• Department of Electromechanics and Rolling Stock of Railways, State University of Infrastructure and Technologies (04071), Ukraine

• https://orcid.org/0000-0002-9868-3852

autor

Kravchenko Kateryna

• Department of Transport and Handling Machines, University of Žilina, Univerzitná 8215/1 (010 26) Žilina, Slovakia

• https://orcid.org/0000-0002-3775-6288

autor

Zaika Denys

• Department of Electromechanics and Rolling Stock of Railways, State University of Infrastructure and Technologies (04071), Ukraine

• https://orcid.org/0000-0003-0693-9580

Bibliografia

• 1. Choudhary A, Goyal D, Shimi SL, et al. Condition Monitoring and Fault Diagnosis of Induction Motors: A Review. Arch Computat Methods Eng. 2019;26:1221-1238. https://doi.org/10.1007/s11831- 018-9286-z.
• 2. Merizalde Y, Hernandez-Callejo L, Duque-Perez O. State of the art and trends in the monitoring, detection and diagnosis of failures in electric induction motors. Energies. 2017;10(7):1056. https://doi.org/:10.3390/en10071056.
• 3. Bazan GH, Goedtel A, Duque-Perez O, MorinigoSotelo D. Multi-fault diagnosis in three-phase induction motors using data optimization and machine learning techniques. Electronics. 2021;10:1462. https://doi.org/10.3390/electronics10121462.
• 4. ISO 13381-1:2015. Condition monitoring and diagnostics of machines - Prognostics - Part 1: General guidelines.
• 5. ISO 17359-1:2018. Condition monitoring and diagnostics of machines - General guidelines.
• 6. ISO 13379-1:2018. Condition monitoring and diagnostics of machines - Data interpretation and diagnostics techniques.
• 7. SafiullinRA. Vibration diagnostics of induction motors. 2021 International Conference on Electrotechnical Complexes and Systems (ICOECS), 2021:228-232. https://doi.org/10.1109/ICOECS52783.2021.9657352.
• 8. Hashish E, Miller K, Finley W, Kreitzer S. Vibration Diagnostic Challenges: Case Studies in Electric Motor Applications. IEEE Industry Applications Magazine. 2017;23(4):22-34. https://doi.org/10.1109/MIAS.2016.2600718.
• 9. Álvaro Souza de Araújo, Oberdan Pinheiro Rocha, Alex Álisson Bandeira Santos, Computational Model for Electrical Motors Condition Analysis and Monitoring, VI Simpósio Internacional de Inovação e Tecnologia, Blucher Engineering Proceedings. 2020; 7(2):543-550. https://doi.org/10.34178/jbth.v5i2.206.
• 10. Suechoey B, Siriporananon S, Chupun P, Boonkhun C, Chompooinwai C. Performance analysis and fault classification in a large electric motor using vibration assessment technique. International Journal of Intelligent Engineering and Systems. 2021;14(1):124-133. https://doi.org/10.22266/ijies2021.0228.13.
• 11. Arhun S, Migal V, Hnatov A, Ponikarovska S, Hnatova A, Novichonok S. Determining the quality of electric motors by vibro-diagnostic Characteristics. EAI Endorsed Transactions on Energy Web. 2020; 7(29). https://doi.org/10.4108/eai.13-7-2018.164101.
• 12. Gubarevych O, Goolak S, Daki O, Yakusevych Y. Determining an additional diagnostic parameter for improving the accuracy of assessment of the condition of stator windings in an induction motor. EasternEuropean Journal of Enterprise Technologies. 2021;5(113):21-29. https://doi.org/10.15587/1729- 061.2021.239509.
• 13. Abdelhak G, Sid Ahmed B, Djekidel R. Fault diagnosis of induction motors rotor using current signature with different signal processing techniques. Diagnostyka. 2022;23(2):2022201. https://doi.org/10.29354/diag/147462.
• 14. Goolak S, Gubarevych O, Gorobchenko O, Nevedrov O, Kamchatna-Stepanova K. Investigation of the influence of the quality of the power supply system on the characteristics of an asynchronous motor with a squirrel-cage rotor. Badanie wpływu jakości układu zasilania na charakterystyki silnika asynchronicznego z wirnikiem klatkowym. Przegląd Elektrotechniczny. 2022;98(6):142-148. https://doi.org/10.15199/48.2022.06.26.
• 15. Hegde V, Sathyanarayana Rao MG. Detection of stator winding inter-turn short circuit fault in induction motor using vibration signals by MEMS accelerometer. Electric Power Components and Systems. 2017;45(13):1463-1473. https://doi.org/10.1080/15325008.2017.1358777.
• 16. Wissam Dehina, Mohamed Boumehraz. Experimental investigation in induction motors using signal processing techniques for early detection of inter-turn short circuit faults, International Journal of Modelling and Simulation. 2022;42(5):855-867. https://doi.org/10.1080/02286203.2021.2001635.
• 17. Goolak S, Gerlici J, Gubarevych O, Lack T, Pustovetov M. Imitation modeling of an inter-turn short circuit of an asynchronous motor stator winding for diagnostics of auxiliary electric drives of transport infrastructure. Communications-Scientific letters of the University of Zilina. 2021;23(2):C65-C74. https://doi.org/10.26552/com.C.2021.2.C65-C74.
• 18. Gerlici J, Goolak S, Gubarevych O, Kravchenko K, Kamchatna-Stepanova K, Toropov A. Method for determining the degree of damage to the stator windings of an induction electric motor with an asymmetric power system. Symmetry. 2022;14:1305. https://doi.org/10.3390/sym14071305.
• 19. Muxiri ACP, Bento F, Fonseca DSB, Marques Cardoso AJ. Thermal Analysis of an Induction Motor Subjected to Inter-Turn Short-Circuit Failures in the Stator Windings. 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), IEEE. 2019:1-5. https://doi.org/10.1109/ICIEAM.2019.8743076.
• 20. Guefack FLT, Kiselev A, Kuznietsov A. Improved detection of inter-turn short circuit faults in PMSM drives using principal component analysis. In 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). 2018:154-159. https://doi.org/10.1109/speedam.2018.8445403.
• 21. Regaz A, Zegnini B, Djellali M, Boukezzi L. Detection of faults in the asynchronous machine by the use of smart materials. Diagnostyka. 2018;19(3):43- 54. https://doi.org/10.29354/diag/93230.
• 22. Sabir H, Ouassaid M, Ngote N, Benbouzid M, A Novel experimental method to detect early rotor faults in induction machines. International Journal on Energy Conversion (IRECON). 2021;9(5):191-202. https://doi.org/10.15866/irecon.v9i5.21214.
• 23. Varbanets R, Fomin O, Píštěk V, Klymenko V, Minchev D, Khrulev A, Zalozh V, Kučera P. Acoustic Method for Estimation of Marine Low-Speed Engine Turbocharger Parameters. Journal of Marine Science and Engineering. 2021;9(3):321. https://doi.org/10.3390/jmse9030321.
• 24. Lovska A, Fomin O, Pistek V, Kucera P. Dynamic load modelling within combined transport trains during transportation on a railway ferry. Applied Sciences. 2020;10(16):5710. https://www.mdpi.com/2076-3417/10/16/5710.
• 25. Goolak S, Gubarevych О, Yermolenko E, Slobodyanyuk M, Gorobchenko O. Development of mathematical model of induction motor for vehicles. Eastern-European Journal of Enterprise Technologies. 2020;2(104):24-35. https://doi.org/10.15587/1729-4061.2020.199559.
• 26. Gubarevych O, Golubieva S, Melkonova I. Comparison of the results of simulation modeling of an asynchronous electric motor with the calculated electrodynamic and energy characteristics. Przegląd Elektrotechniczny. 2022;98:61-66. https://doi.org/10.15199/48.2022.10.11.
• 27. Goolak S, Gerlici J, Sapronova S, Tkachenko V, Lack T, Kravchenko K. Determination of parameters of asynchronous electric machines with asymmetrical windings of electric locomotives. CommunicationsScientific letters of the University of Zilina. 2019;21(2):24-31. https://doi.org/10.26552/com.C.2019.2.24-31.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).