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Study of bearing currents in induction machine: diagnostic possibilities, fault detection, and prediction

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Abstract

Bearing failures in electrical machines pose significant challenges, attracting attention in diagnostic research. The widespread adoption of variable-speed drives across various motor applications has increased the effects of bearing currents, necessitating thorough exploration in both academic and industrial contexts. The paper contributes valuable insights into identifying and addressing bearing-related issues in electrical machines. It comprehensively investigates the matter, investigating damage types and diagnostic techniques specific to bearing currents in induction machines. Moreover, it provides insights from experiments conducted in controlled laboratory settings to replicate bearing current faults. As the industry integrates advanced technologies into manufacturing processes and gains traction, preventive maintenance is increasingly emphasized. Consequently, the paper expands its investigation into signal pre-processing to enhance fault prediction accuracy by optimizing machine signals. Given the dynamic nature of industrial standards and the growing demand for predictive maintenance strategies, this research presents a predictive method for early fault detection. Aiming for heightened efficiency, reduced downtime, and enhanced reliability, the perspectives outlined in this paper make a meaningful contribution to the evolving field of predictive maintenance.

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References

  1. Palacios RHC, Da Silva IN, Goedtel A, Godoy WF, Lopes TD (2017) Diagnosis of stator faults severity in induction motors using two intelligent approaches. IEEE Trans Ind Inform 13(4):1681–1691

    Article  Google Scholar 

  2. Turzynski M, Chrzan PJ (2020) Reducing common-mode voltage and bearing currents in quasi-resonant DC-link inverter. IEEE Trans Power Electron 35(9):9555–9564

    Article  Google Scholar 

  3. Plazenet T, Boileau T, Boileau CC, Nahid-Mobarakeh B (2021) Influencing parameters on discharge bearing currents in inverter-fed induction motors. IEEE Trans Energy Convers 36(2):940–949

    Article  Google Scholar 

  4. Zhu W, De Gaetano D, Chen X, Jewell GW, Hu Y (2022) A review of modeling and mitigation techniques for bearing currents in electrical machines with variable-frequency drives. IEEE Access 10(December):125279–125297

    Article  Google Scholar 

  5. Xu Y, Liang Y, Yuan X, Wu X, Li Y (2021) Experimental assessment of high frequency bearing currents in an induction motor driven by a SiC inverter. IEEE Access 9:40540–40549

    Article  Google Scholar 

  6. Plazenet T, Boileau T, Caironi C, Nahid-Mobarakeh B (2018) A comprehensive study on shaft voltages and bearing currents in rotating machines. IEEE Trans Ind Appl 54(4):3749–3759

    Article  Google Scholar 

  7. AEGIS (2020) Wind energy with no downtime—Study Case I

  8. AEGIS (2019) Commercial ships without bearing protection for critical systems, commercial ships can end up dead in the water—study case II

  9. AEGIS (2017) Protecting VFD—driven motors in distribution—case study III

  10. AEGIS (2017) Protecting VFD—driven motors in dairy production—case study IV

  11. Kudelina K, Vaimann T, Asad B, Rassõlkin A, Kallaste A, Demidova G (2021) Trends and challenges in intelligent condition monitoring of electrical machines using machine learning. Appl Sci 11(6):2761

    Article  Google Scholar 

  12. Raja HA, Kudelina K, Asad B, Vaimann T (2022) Fault Detection and Predictive Maintenance for Electrical Machines. In: New trends in electric machines—technology and applications, IntechOpen

  13. Senanayaka JSL, Van Khang H, Robbersmyr KG (2017) Towards online bearing fault detection using envelope analysis of vibration signal and decision tree classification algorithm. In: 2017 20th Int. Conf. Electr. Mach. Syst. ICEMS 2017, pp 13–18

  14. Pandarakone SE, Mizuno Y, Nakamura H (2017) Distinct fault analysis of induction motor bearing using frequency spectrum determination and support vector machine. IEEE Trans Ind Appl 53(3):3049–3056

    Article  Google Scholar 

  15. Zhao S, Chen C, Luo Y (2020) Probabilistic principal component analysis assisted new optimal scale morphological top-hat filter for the fault diagnosis of rolling bearing. IEEE Access 8:156774–156791

    Article  Google Scholar 

  16. Toma RN, Prosvirin AE, Kim JM (1884) Bearing fault diagnosis of induction motors using a genetic algorithm and machine learning classifiers. Sensors 20(7):2020

    Google Scholar 

  17. Zhu J, Chen N, Peng W (2019) Estimation of bearing remaining useful life based on multiscale convolutional neural network. IEEE Trans Ind Electron 66(4):3208–3216

    Article  Google Scholar 

  18. Mao W, Liu Y, Ding L, Li Y (2019) Imbalanced fault diagnosis of rolling bearing based on generative adversarial network: a comparative study. IEEE Access 7:9515–9530

    Article  Google Scholar 

  19. Zhang S, Zhang S, Wang B, Habetler TG (2020) Deep learning algorithms for bearing fault diagnosticsx—a comprehensive review. IEEE Access 8:29857–29881

    Article  Google Scholar 

  20. Tawfiq KB, Güleç M, Sergeant P (2023) Bearing current and shaft voltage in electrical machines: a comprehensive research review. Machines 11(5):550. https://doi.org/10.3390/machines11050550

    Article  Google Scholar 

  21. Berhausen S, Jarek T, Orság P (2022) Influence of the shielding winding on the bearing voltage in a permanent magnet synchronous machine. Energies (Basel) 15(21):8001. https://doi.org/10.3390/en15218001

    Article  Google Scholar 

  22. Plazenet T, Boileau T, Caironi C, Nahid-Mobarakeh B (2018) A comprehensive study on shaft voltages and bearing currents in rotating machines. IEEE Trans Ind Appl 54(4):3749–3759. https://doi.org/10.1109/TIA.2018.2818663

    Article  Google Scholar 

  23. Baldor Electric Company, Inverter-driven induction motors—shaft and bearing current solutions. Ind White Pap

  24. Kallaste A, Vaimann T, Belahcen A (2014) Possible manufacturing tolerance faults in design and construction of low speed slotless permanent magnet generator. In: 2014 16th Eur Conf Power Electron Appl EPE-ECCE Eur 2014

  25. Vaimann T, Belahcen A, Kallaste A (2014) Changing of magnetic flux density distribution in a squirrel-cage induction motor with broken rotor bars. Elektron ir Elektrotechnika 20(7):11–14

    Google Scholar 

  26. Tom Bishop (2017) Dealing with Shaft and Bearing Currents

  27. Welkon Limited, Insulated Bearing—Insulated Shaft

  28. Chen S, Lipo TA (1996) Source of induction motor bearing currents caused by PWM inverters. IEEE Trans Energy Convers 11(1):25–32

    Article  Google Scholar 

  29. Särkimäki V (2009) Radio frequency measurement method for detecting bearing currents in induction motors. Lappeenranta University of Technology, Lappeenranta

    Google Scholar 

  30. Mütze A, Binder A (2007) Calculation of motor capacitances for prediction of the voltage across the bearings in machines of inverter-based drive systems. IEEE Trans Ind Appl 43(3):665–672

    Article  Google Scholar 

  31. Mütze A, Binder A (2006) Don’t lose your bearings—mitigation techniques for bearing currents in inverter-supplied drive systems. IEEE Ind Appl Mag 12(4):22–31

    Google Scholar 

  32. Ollila J, Hammar T, Iisakkala J, Tuusa H (1997) On the bearing currents in medium power variable speed AC drives. In: International electric machines and drives conference

  33. Quabeck S, Braun L, Fritz N, Klever S, De Doncker RW (2021) A machine integrated rogowski coil for bearing current measurement. In: 13th Int Symp Diagnostics Electr Mach Power Electron Drives, pp 17–23

  34. Li J, Water W, Zhu B, Lu J (2015) Integrated high-frequency coaxial transformer design platform using artificial neural network optimization and FEM simulation. IEEE Trans Magn 51(3):1–4

    Google Scholar 

  35. Immovilli F, Bellini A, Rubini R, Tassoni C (2010) Diagnosis of bearing faults in induction machines by vibration or current signals: a critical comparison. IEEE Trans Ind Appl 46(4):1350–1359

    Article  Google Scholar 

  36. Kudelina K, Vaimann T, Rassõlkin A, Kallaste A, Demidova G, Karpovich D (2021) Diagnostic Possibilities of Induction Motor Bearing Currents. In: Int Sc. Tech Conf Altern Curr Electr Drives

  37. Lei Y, Li N, Gontarz S, Lin J, Radkowski S, Dybala J (2016) A model-based method for remaining useful life prediction of machinery. IEEE Trans Reliab 65(3):1314–1326

    Article  Google Scholar 

  38. Han P, Heins G, Patterson D, Thiele M, Ionel DM (2020) Evaluation of bearing voltage reduction in electric machines by using insulated shaft and bearings. In: ECCE 2020—IEEE energy convers congr expo, pp 5584–5589

  39. Gonda A, Capan R, Bechev D, Sauer B (2019) The influence of lubricant conductivity on bearing currents in the case of rolling bearing greases. Lubricants 7(12):108

    Article  Google Scholar 

  40. Oh HW, Willwerth A (2008) Shaft grounding—a solution to motor bearing currents. Am Soc Heating Refrig Air Cond Eng Trans 114(2):246–251

    Google Scholar 

  41. Mechlinski M, Schroder S, Shen J, De Doncker RW (2017) Grounding concept and common-mode filter design methodology for transformerless mv drives to prevent bearing current issues. IEEE Trans Ind Appl 53(6):5393–5404

    Article  Google Scholar 

  42. Kudelina K, Vaimann T, Rassolkin A, Kallaste A (2021) Possibilities of decreasing induction motor bearing currents. In: 2021 IEEE Open Conf Electr Electron Inf Sci eStream 2021—Proc

  43. Weicker M, Pöss H-J (2023) Reduction of circulating bearing currents in dependence of nanocrystalline common-mode current ring cores. In: 2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe), Aalborg, Denmark, pp 1–8. https://doi.org/10.23919/EPE23ECCEEurope58414.2023.10264251.

  44. Weicker M, Bello G, Kampen D, Binder A (2020) Influence of system parameters in variable speed AC-induction motor drives on parasitic electric bearing currents. In: 2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe), Lyon, France, pp 1–10. https://doi.org/10.23919/EPE20ECCEEurope43536.2020.9215613.

  45. Zehelein M, Fischer M, Nitzsche M, Roth-Stielow J (2019) Influence of the filter design on wide-bandgap voltage source inverters with sine wave filter for electrical drives. In: 2019 21st european conference on power electronics and applications (EPE '19 ECCE Europe), Genova, Italy, pp P.1-P.10. https://doi.org/10.23919/EPE.2019.8914968.

  46. Kudelina K, Vaimann T, Kallaste A, Asad B, Demidova G (2021) Induction motor bearing currents—causes and damages. In: 28th Int Work Electr Drives Improv Reliab Electr Drives

  47. Kudelina K, Asad B, Vaimann T, Rassõlkin A, Kallaste A (2020) Production quality related propagating faults of induction machines. In: Int Conf Electr Power Drive Syst

  48. Silva JLH, Cardoso AJM (2005) Bearing failures diagnosis in three-phase induction motors by extended Park’s Vector approach. In: IECON Proc. Industrial Electron. Conf, vol 2005, pp 2591–2596

  49. Raja HA, Kudelina K, Asad B, Vaimann T, Kallaste A, Rassõlkin A, Khang HV (2022) Signal spectrum-based machine learning approach for fault prediction and maintenance of electrical machines. Energies 15:9507. https://doi.org/10.3390/en15249507

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086, Tallinn, Estonia

    Karolina Kudelina, Hadi Ashraf Raja, Muhammad Usman Naseer, Siarhei Autsou, Bilal Asad, Toomas Vaimann & Ants Kallaste

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  1. Karolina Kudelina
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  2. Hadi Ashraf Raja
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  3. Muhammad Usman Naseer
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  4. Siarhei Autsou
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  5. Bilal Asad
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  6. Toomas Vaimann
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  7. Ants Kallaste
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Contributions

Conceptualization was performed by KK; methodology by KK, HAR; formal analysis and investigation by MUN, SA; writing—original draft preparation—by KK; writing—review and editing—by BA, AK; funding acquisition by TV; supervision by AK.

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Correspondence to Karolina Kudelina.

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Kudelina, K., Raja, H.A., Naseer, M.U. et al. Study of bearing currents in induction machine: diagnostic possibilities, fault detection, and prediction. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02411-x

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