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Structural diagram of the built-in diagnostic system for electric drives of vehicles

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Currently, in transport systems, as part of the main and auxiliary equipment, a large number of induction motors with a squirrel-cage rotor of different capacities are used. Their wide application in the transport industry is associated with the main advantages over other types of machines – a fairly high reliability, low cost and ease of maintenance. However, during the operation of these motors, a number of malfunctions can occur that affect the deterioration of the performance of the entire drive, the accuracy of its functions, or accelerate an emergency stop. To ensure proper control of the technical condition of electric motors, modern diagnostic systems are required that operate in real-time and operational loading mode with the transmission of data on the instantaneous state of the main control elements. The paper proposes a block diagram of the diagnostic built-in system and developed a modular unit for it to set the type and degree of the most complex damage - inter-turn short circuit in the stator winding.
Czasopismo
Rocznik
Strony
art. no. 2022406
Opis fizyczny
Bibliogr. 36 poz., rys.
Twórcy
  • Department of Electromechanics and Rolling Stock of Railways, State University of Infrastructure and Technologies (04071), Ukraine
  • Department of Electromechanics and Rolling Stock of Railways, State University of Infrastructure and Technologies (04071), Ukraine
  • Department of Electrical Engineering, Volodymyr Dahl East Ukrainian National University, (93400), Ukraine
  • Faculty of Management and Technology, State University of Infrastructure and Technologies (04071), Ukraine
Bibliografia
  • 1. Sheikh MA, Bakhsh ST, Irfan M, Nor NBM, Nowakowski G. A Review to Diagnose Faults Related to Three-Phase Industrial Induction Motors. J Fail. Anal. And Preven. 2022:1-12. https://doi.org/10.1007/s11668-022-01445-2.
  • 2. Hussein AM, Obed AA, Zubo RA, Al-Yasir YI, Saleh AL, Fadhel H, Sheikh-Akbari A, Mokryani G, AbdAlhameed RA. Detection and Diagnosis of Stator and Rotor Electrical Faults for Three-Phase Induction Motor via Wavelet Energy Approach. Electronics. 2022;11(8):1253. https://doi.org/10.3390/electronics11081253.
  • 3. Choudhary A, Goyal D, Shimi SL, Akula A. Condition monitoring and fault diagnosis of induction motors: A review. Archives of Computational Methods in Engineering. 2019;26(4):1221-1238. https://doi.org/10.1007/s11831-018-9286-z.
  • 4. Regaz A, Zegnini B, Djellali M, Boukezzi L. Detection of faults in the induction machine by the use of smart materials. Diagnostyka. 2018;19(3):43-54. https://doi.org/10.29354/diag/93230.
  • 5. 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.
  • 6. 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.
  • 7. Dehina W, Boumehraz M. Experimental investigation in induction motors using signal processing techniques for early detection of inter-turn short circuit faults. International Journal of Modelling and Simulation, 2021:855-867. https://doi.org/10.1080/02286203.2021.2001635.
  • 8. Gubarevych O, Goolak S, Daki O, Tryshyn V. Investigation of turn-to-turn closures of stator windings to improve the diagnostics system for induction motors. Problemele energeticii regionale. 2021;2(50):10-24. https://doi.org/10.52254/1857- 0070.2021.2-50.02.
  • 9. 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/10.15587/1729-4061.2021.239509.
  • 10. Haiba1 AS, ElFaraskoury AA, ElKoshairy AD, Halawa MM. Modeling and simulation of partial discharge measurement for defected solid dielectrics. Journal of Measurement Science and Applications (JMSA). 2022;2(1):43-53. https://doi.org/10.21608/JMSA.2022.219865.
  • 11. Tsyokhla A, Griffo I, Wang J. On-line motor insulation capacitance monitoring using low-cost sensors. 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019:6996-7003. https://doi.org/10.1109/ECCE.2019.8912241.
  • 12. Kuncan M, Kaplan K, Minaz MR, Kaya Y, Ertunc H M. A novel feature extraction method for bearing fault classification with one dimensional ternary patterns. ISA transactions. 2020;100:346-357. https://doi.org/10.1016/j.isatra.2019.11.006.
  • 13. Pusca R, Sbaa S, Bessous N, Romary R, Bousseksou R. Mechanical failure detection in induction motors using stator current and stray flux analysis techniques. Eng. Proc. 2022;14:19. https://doi.org/10.3390/engproc2022014019.
  • 14. Safiullin RA. 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.
  • 15. Benbouzid MEH. Signal processing for fault detection and diagnosis in electric machines and systems. IET, London. 2020:284. https://doi.org/10.1049/PBPO153E_itr.
  • 16. Asad B, Vaimann T, Belahcen A, Kallaste A. Broken rotor bar fault diagnostic of inverter fed induction motor using FFT, Hilbert and Park's vector approach. In 2018 XIII International Conference on Electrical Machines (ICEM). IEEE, 2018:2352-2358. https://doi.org/10.1109/ICELMACH.2018.8506957.
  • 17. Goktas T. Evaluation and Classification of Double Bar Breakages Through Three-Axes Vibration Sensor in Induction Motors. In IEEE Sensors Journal, 1 July1, 2022;22(13):13602-13611. https://doi.org/10.1109/JSEN.2022.3176059.
  • 18. 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.
  • 19. 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.
  • 20. Almounajjed A, Sahoo AK, Kumar MK, Assaf T. Fault diagnosis and investigation techniques for induction motor. International Journal of Ambient Energy. 2022:1-21. https://doi.org/10.1080/01430750.2021.2016483.
  • 21. Muxiri AC, Bento F, Fonseca DSB, Cardoso AJM. Thermal analysis of an induction motor subjected to inter-turn short-circuit failures in the stator windings. In 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). 2019:1-5. https://doi.org/10.1109/ICIEAM.2019.8743076.
  • 22. Varbanets R, Fomin O, Píštěk V, Klymenko V, Minchev D, Khrulev A, Zalozh V, Kučera P. Acoustic method for estimation of marine low-speed motor turbocharger parameters. Journal of Marine Science and Engineering. 2021;9(3):321. https://www.mdpi.com/2077-1312/9/3/321/htm.
  • 23. Asfani DA, Negara IMY, Hernanda IGNS, Fahmi D, Muljadi E, Nelms RM. Methods to Deter006Dine the Stator Inter-turn Short Circuit in an Induction Motor with Installed Rotor. In: 2020 IEEE Energy Conversion Congress and Exposition (ECCE). 2020: 7-13. https://doi.org/10.1109/ECCE44975.2020.9236051.
  • 24. 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.
  • 25. Singh G, Kumar TCA, Naikan VNA. Induction motor inter turn fault detection using infrared thermographic analysis. Infrared Physics & Technology. 2016;77: 277-282. https://doi.org/10.1016/j.infrared.2016.06.010.
  • 26. Adouni A, J Marques Cardoso A. Thermal analysis of low-power three-phase induction motors operating under voltage unbalance and inter-turn short circuit faults. Machines. 2021;9(1):2-11. https://doi.org/10.3390/machines9010002.
  • 27. 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.
  • 28. 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 induction motor with a squirrel-cage rotor. Przegląd Elektrotechniczny, 2022; 98(6(1)):142–148. https://doi.org/10.15199/48.2022.06.26.
  • 29. Goolak S, Tkachenko V, Šťastniak P, Sapronova S, Liubarskyi B. Analysis of control methods for the traction drive of an alternating current electric locomotive. Symmetry. 2022;14(1):150. https://doi.org/10.3390/sym14010150.
  • 30. Muxiri AC, Bento F, Fonseca DSB, Cardoso AJM. Thermal analysis of an induction motor subjected to inter-turn short-circuit failures in the stator windings. In 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). IEEE. 2019:1-5. https://doi.org/10.1109/ICIEAM.2019.8743076.
  • 31. Singh G, Kumar TCA, Naikan VNA. Induction motor inter turn fault detection using infrared thermographic analysis. Infrared Physics & Technology. 2016;77: 277-282. https://doi.org/10.1016/j.infrared.2016.06.010.
  • 32. Sha M, Luo M. Online identification technology based on variation mechanism of traction motor parameters. In 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). IEEE. 2021:77-82. https://doi.org/10.1109/AEMCSE51986.2021.00023.
  • 33. Benbouzid MEH. A review of induction motors signature analysis as a medium for faults detection, IEEE Transactions on Industrial Electronics, 2000; 47(5): 984-993. https://doi.org/10.1109/41.873206.
  • 34. 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.
  • 35. Goolak S, Gerlici J, Gubarevych O, Lack T, Pustovetov M. Imitation modeling of an inter-turn short circuit of an induction 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.
  • 36. Gubarevych O, Golubieva S, Melkonova I. Comparison of the results of simulation modeling of an induction electric motor with the calculated electrodynamic and energy characteristics. Przegląd Elektrotechniczny. 2022;98(10):61-66. https://doi.org/10.15199/48.2022.10.11.
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).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6e39ff5a-2c84-478d-be0b-a5da0f27d36c
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