Advertisement

Rotor Electrical Fault Detection of Wind Turbine Induction Generators Using an Unscented Kalman Filter

  • Zhale HashemiEmail author
  • Akbar Rahideh
Research Paper
  • 12 Downloads

Abstract

This paper presents a fault detection method for induction generators using an unscented Kalman filter. In some applications such as wind turbine energy conversion systems, the induction generators experience oscillations caused by wind speed variation; therefore, the fault detection method should be able to detect fault in the presence of these oscillations. On the other hand, the induction generator may operate in islanded mode of operation, the situation that does not happen in motor application. In the present paper, the type of fault is the rotor electrical asymmetry and the proposed method is able to detect the fault in both grid-connected and islanded modes of operation. Several scenarios are simulated, and the efficacy of the proposed technique is evaluated by means of simulation results. Moreover, experiments are performed to validate the ability of the proposed method.

Keywords

Induction generator Fault detection Kalman filter Grid-connected Islanded 

References

  1. Antonino-Daviu J, Quijano-Lopez A, Climente-Alarcon V, Garin-Abellan C (2017) Reliable detection of rotor winding asymmetries in wound rotor induction motors via integral current analysis. IEEE Trans Ind Appl 53(3):2040–2048CrossRefGoogle Scholar
  2. Chan CC, Wang H (1990) An effective method for rotor resistance identification for high-performance induction motor vector control. IEEE Trans Ind Electron 37(6):477–482CrossRefGoogle Scholar
  3. Cheng F, Wang J, Qu L, Qiao W (2017) Rotor current-based fault diagnosis for DFIG wind turbine drivetrain gearboxes using frequency analysis and a deep classifier. In: 2017 IEEE industry applications society annual meeting, IAS 2017, pp 1–9Google Scholar
  4. Cruz SMA (2012) An active-reactive power method for the diagnosis of rotor faults in three-phase induction motors operating under time-varying load conditions. IEEE Trans Energy Convers 27(1):71–84MathSciNetCrossRefGoogle Scholar
  5. Dalvand F, Kalantar A, Safizadeh MS (2016) A novel bearing condition monitoring method in induction motors based on instantaneous frequency of motor voltage. IEEE Trans Ind Electron 63(1):364–376CrossRefGoogle Scholar
  6. Duvvuri S, Detroja K (2016) Model-based broken rotor bars fault detection and diagnosis in squirrel-cage induction motors. In: 2016 3rd conference on control and fault-tolerant systems (SysTol), pp 537–539Google Scholar
  7. Elbouchikhi E, Amirat Y, Feld G, Benbouzid M (2019) Generalized likelihood ratio test-based approach for stator faults detection in a PWM inverter-fed induction motor drive. IEEE Trans Ind Electron 66(8):6343–6353CrossRefGoogle Scholar
  8. Faiz J, Moosavi SMM (2017) Detection of mixed eccentricity fault in doubly-fed induction generator based on reactive power spectrum. IET Electr Power Appl 11(6):1076–1084CrossRefGoogle Scholar
  9. Ghanbari T (2016) Autocorrelation function-based technique for stator turn-fault detection of induction motor. IET Sci Meas Technol 10(2):100–110CrossRefGoogle Scholar
  10. Gyftakis KN, Kappatou JC (2014) The zero-sequence current as a generalized diagnostic mean in Δ-connected three-phase induction motors. IEEE Trans Energy Convers 29(1):138–148CrossRefGoogle Scholar
  11. Ibrahim RK, Watson SJ, Djurović S, Crabtree CJ (2018) An effective approach for rotor electrical asymmetry detection in wind turbine DFIGs. IEEE Trans Ind Electron 65(11):8872–8881CrossRefGoogle Scholar
  12. Immovilli F, Bianchini C, Cocconcelli M, Bellini A, Rubini R (2013) Bearing fault model for induction motor with externally induced vibration. IEEE Trans Ind Electron 60(8):3408–3418CrossRefGoogle Scholar
  13. Kim J, Shin S, Bin Lee S, Gyftakis KN, Drif M, Cardoso AJM (2015) Power spectrum-based detection of induction motor rotor faults for immunity to false alarms. IEEE Trans Energy Convers 30(3):1123–1132CrossRefGoogle Scholar
  14. Kumar S, Prakash J, Kanagasabapathy P (2011) A critical evaluation and experimental verification of Extended Kalman Filter, Unscented Kalman Filter and Neural State Filter for state estimation of three phase induction motor. Appl Soft Comput J 11(3):3199–3208CrossRefGoogle Scholar
  15. Ojaghi M, Yazdandoost N, Gholmohammadzadeh S (2016) Oil whirl fault detection in sleeve bearing of induction motor by using instantaneous power harmonics. Tabriz J Electr Eng 4:6Google Scholar
  16. Oumaamar MEK, Maouche Y, Boucherma M, Khezzar A (2017) Static air-gap eccentricity fault diagnosis using rotor slot harmonics in line neutral voltage of three-phase squirrel cage induction motor. Mech Syst Signal Process 84:584–597CrossRefGoogle Scholar
  17. Panagiotou PA, Arvanitakis I, Lophitis N, Antonino-Daviu J, Gyftakis KN (2019) A new approach for broken rotor bar detection in induction motors using frequency extraction in stray flux signals. IEEE Trans Ind Appl 55(4):3501–3511CrossRefGoogle Scholar
  18. Park Y et al (2019) Stray flux monitoring for reliable detection of rotor faults under the influence of rotor axial air ducts. IEEE Trans Ind Electr 66(10):7561–7570CrossRefGoogle Scholar
  19. Qiao W, Cheng F, Qu L, Hao L, Wei C (2019) Fault diagnosis of wind turbine gearboxes based on DFIG stator current Envelope analysis. IEEE Trans Sustain Energy 10(3):1044–1053CrossRefGoogle Scholar
  20. Ramirez-nunez JA et al (2018) Evaluation of the detectability of electromechanical faults in induction motors via transient analysis of the stray flux. IEEE Trans Ind Appl 54(5):4324–4332CrossRefGoogle Scholar
  21. Rayyam M, Zazi M, Hajji Y (2015) Detection of broken bars in induction motor using the Extended Kalman Filter (EKF). In 2015 Third world conference on complex systems (WCCS), pp 1–5Google Scholar
  22. Riera-Guasp M, Pineda-Sanchez M, Perez-Cruz J, Puche-Panadero R, Roger-Folch J, Antonino-Daviu JA (2012) Diagnosis of induction motor faults via gabor analysis of the current in transient regime. IEEE Trans Instrum Meas 61(6):1583–1596CrossRefGoogle Scholar
  23. Sadeghi R, Samet H, Ghanbari T (2018) Detection of stator short-circuit faults in induction motors using the concept of instantaneous frequency. IEEE Trans Ind Inf.  https://doi.org/10.1109/TII.2018.2881921 CrossRefGoogle Scholar
  24. Said MSN, Benbouzid MEH, Benchaib A (2000) Detection of broken bars in induction motors using an extended Kalman filter for rotor resistance sensorless estimation. IEEE Trans Energy Convers 15(1):66–70CrossRefGoogle Scholar
  25. Sapena-Bano A et al (2015) Harmonic order tracking analysis: a novel method for fault diagnosis in induction machines. IEEE Trans Energy Convers 30(3):833–841CrossRefGoogle Scholar
  26. Sapena-Bano A, Riera-Guasp M, Puche-Panadero R, Martinez-Roman J, Perez-Cruz J, Pineda-Sanchez M (2016) Harmonic order tracking analysis: a speed-sensorless method for condition monitoring of wound rotor induction generators. IEEE Trans Ind Appl 52(6):4719–4729CrossRefGoogle Scholar
  27. Seshadrinath J, Singh B, Panigrahi BK (2014) Investigation of vibration signatures for multiple fault diagnosis in variable frequency drives using complex wavelets. IEEE Trans Power Electron 29(2):936–945CrossRefGoogle Scholar
  28. Shah D, Nandi S, Neti P (2009) Stator-interturn-fault detection of doubly fed induction generators using rotor-current and search-coil-voltage signature analysis. IEEE Trans Ind Appl 45(5):1831–1842CrossRefGoogle Scholar
  29. Stojcic G, Pasanbegovic K, Wolbank TM (2014) Detecting faults in doubly fed induction generator by rotor side transient current measurement. IEEE Trans Ind Appl 50(5):3494–3502CrossRefGoogle Scholar
  30. St-Onge X, Cameron JAD, Saleh SAM, Scheme EJ (2019) A symmetrical component feature extraction method for fault detection in induction machines. IEEE Trans Ind Electron 66(9):7281–7289CrossRefGoogle Scholar
  31. Wang J, Cheng F, Qiao W, Qu L (2018) Multiscale filtering reconstruction for wind turbine gearbox fault diagnosis under varying-speed and noisy conditions. IEEE Trans Ind Electron 65(5):4268–4278CrossRefGoogle Scholar
  32. Yang T, Pen H, Wang Z, Chang CS (2016) Feature knowledge based fault detection of induction motors through the analysis of stator current data. IEEE Trans Instrum Meas 65(3):549–558CrossRefGoogle Scholar
  33. Zarei J, Poshtan J (2007) Bearing fault detection using wavelet packet transform of induction motor stator current. Tribol Int 40:763–769CrossRefGoogle Scholar
  34. Zarei J, Kowsari E, Razavi-Far R (2019) Induction motors fault detection using square-root transformed cubature quadrature Kalman filter. IEEE Trans Energy Convers 34(2):870–877CrossRefGoogle Scholar

Copyright information

© Shiraz University 2019

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran

Personalised recommendations