Early detection of inter-turn short-circuit faults in the stator windings of Doubly-Fed Induction Generators (DFIGs) is essential to ensure proper maintenance planning and avoid critical failures. This paper presents a technique to detect and quantify this type of fault to assess its severity. The proposed approach consists of analyzing the rotor currents of DFIGs in Park reference frame. A theoretical study is carried out, accompanied by experimental validation using a test bench and a data acquisition (DAQ) system. This study reveals a new fault indicator based on analysis of geometric shape of rotor currents. Quantifying the evolution of this indicator enables the estimation of defect severity with a relative error of 2%. Qualitative and quantitative analysis of it facilitates the maintenance supervisor’s decision-making process. The results demonstrate the potential of this approach, which is characterized by its simplicity, reliability and effectiveness.
AbdallahHBenatmanK (2017) Stator winding inter-turn short-circuit detection in induction motors by parameter identification. IET Electric Power Applications11(2): 272–288. https://doi.org/10.1049/iet-epa.2016.0432
2.
AnbuchandranSBabuMAStephenDS, et al. (2024) DC microgrid for EV charging station with EV control by using STSM controllers. Engineering Research Express6(4): 045345. https://doi.org/10.1088/2631-8695/ad92d9
3.
AnbuchandranSStephenDSThinakaranM, et al. (2025) Dynamic voltage regulation in DC microgrids using super-twisting sliding mode controllers. Electrical Engineering107(11): 14205–14227. https://doi.org/10.1007/s00202-025-03256-8
4.
BachaKSalemSBChaariA (2012) An improved combination of Hilbert and Park transforms for fault detection and identification in three-phase induction motors. International Journal of Electrical Power & Energy Systems43(1): 1006–1016. https://doi.org/10.1016/j.ijepes.2012.06.056
5.
BenbouzidMEH (2000) A review of induction motors signature analysis as a medium for faults detection. IEEE Transactions on Industrial Electronics47(5): 984–993. Available at: https://doi.org/10.1109/41.873206
6.
BilalHHeraudNRoy SambatraEJ (2020) Detection of inter-turn short-circuit on a doubly fed induction machine with D-Q axis representation In: 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). Riga, Latvia. IEEE, pp. 1–4. https://doi.org/10.1109/RTUCON51174.2020.9316591
7.
BilalHHeraudNSambatraEJR (2021) An experimental approach for detection and quantification of short-circuit on a doubly fed induction machine (DFIM) windings. Journal of Control, Automation and Electrical Systems32(4): 1123–1130. https://doi.org/10.1007/s40313-021-00733-w
8.
BouzidMChampenoisG (2013a) An efficient, simplified multiple-coupled circuit model of the induction motor aimed to simulate different types of stator faults. Mathematics and Computers in Simulation90: 98–115. https://doi.org/10.1016/j.matcom.2013.04.005
9.
BouzidMBKChampenoisG (2013b) New expressions of symmetrical components of the induction motor under stator faults. IEEE Transactions on Industrial Electronics60(9): 4093–4102. https://doi.org/10.1109/TIE.2012.2235392
10.
CardosoAMSaraivaES (1993) Computer-aided detection of airgap eccentricity in operating three-phase induction motors by Park’s vector approach. IEEE Transactions on Industry Applications29(5): 897–901. https://doi.org/10.1109/28.245712
11.
CardosoAMCruzSMAFonsecaDSB (1999) Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park’s vector approach. IEEE Transactions on Energy Conversion14(3): 595–598. https://doi.org/10.1109/60.790920
12.
CasadeiDFilippettiFRossiC, et al. (2006) Diagnostic technique based on rotor modulating signals signature analysis for doubly fed induction machines in wind generator systems In: Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting. Tampa, FL: IEEE, Vol. 3, pp. 1525–1532. https://doi.org/10.1109/IAS.2006.256732
13.
ChenYRehmanAUZhaoY, et al. (2021) Numerical modeling, electrical characteristics analysis and experimental validation of severe inter-turn short circuit fault conditions on stator winding in DFIG of wind turbines. IEEE Access9: 13149–13158. https://doi.org/10.1109/access.2021.3050876
14.
CruzSMCardosoAM (2002) Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park’s vector approach. IEEE Transactions on Industry Applications37(5): 1227–1233. https://doi.org/10.1109/28.952496
15.
CusidCusidoJRomeralLOrtegaJA, et al. (2008) Fault detection in induction machines using power spectral density in wavelet decomposition. IEEE Transactions on Industrial Electronics55(2): 633–643. https://doi.org/10.1109/TIE.2007.911960
16.
Daneshi-FarZCapolinoGAHenaoH (2010) Review of failures and condition monitoring in wind turbine generators In: The XIX International Conference on Electrical Machines - ICEM 2010. Rome, Italy: IEEE, pp. 1–6. https://doi.org/10.1109/ICELMACH.2010.5608150
17.
DeebMKotelenetsNFAssafT, et al. (2021) Three-phase induction motor short circuits fault diagnosis using MCSA and NSC In: 2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). Moscow, Russia: IEEE, pp. 1–6. https://doi.org/10.1109/REEPE51337.2021.9388051
18.
DouglasHPillayPBarendseP (2005) The detection of interturn stator faults in doubly-fed induction generators In: Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005. Hong Kong, China: IEEE, Vol. 2, pp. 1097–1102. https://doi.org/10.1109/IAS.2005.1518493
19.
GangsarPTiwariR (2020) Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: a state-of-the-art review. Mechanical Systems and Signal Processing144: 106908. https://doi.org/10.1016/j.ymssp.2020.106908
20.
GritliYStefaniARossiC, et al. (2011) Experimental validation of doubly fed induction machine electrical faults diagnosis under time-varying conditions. Electric Power Systems Research81(3): 751–766. https://doi.org/10.1016/j.epsr.2010.11.004
21.
GrubicSAllerJLuB, et al. (2008) A survey on testing and monitoring methods for stator insulation systems of low-voltage induction machines focusing on turn insulation problems. IEEE Transactions on Industrial Electronics55(12): 4127–4136. https://doi.org/10.1109/TIE.2008.2004665
22.
HamatwiEBarendsePKhanA (2021) An investigation into the diagnosis of interturn winding faults in a scaled-down DFIG using the MCSA and DWT of the stator and rotor current In: 2021 IEEE Energy Conversion Congress and Exposition (ECCE). Vancouver, BC, Canada: IEEE, pp. 3797–3804. https://doi.org/10.1109/ECCE47101.2021.9595144
23.
HameedZHongYChoY, et al. (2009) Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renewable and Sustainable Energy Reviews13(1): 1–39. https://doi.org/10.1016/j.rser.2007.05.008
24.
HeSShenXJiangZ (2019) Detection and location of stator winding interturn fault at different slots of DFIG. IEEE Access7: 89342–89353. https://doi.org/10.1109/ACCESS.2019.2926538
25.
JiménezGAMuñozAODuarte-MermoudMA (2007) Fault detection in induction motors using Hilbert and wavelet transforms. Electrical Engineering89(3): 205–220. https://doi.org/10.1007/s00202-005-0339-6
26.
JungJHLeeJJKwonBH (2006) Online diagnosis of induction motors using MCSA. IEEE Transactions on Industrial Electronics53(6): 1842–1852. https://doi.org/10.1109/TIE.2006.885131
27.
KiaSHHenaoHCapolinoGA (2007) Digital signal processing for induction machines diagnosis - a review In: IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society. Taipei, Taiwan: IEEE, pp. 1155–1162. https://doi.org/10.1109/IECON.2007.4460325
28.
LuQBreikinTWangH (2011) Modelling and fault diagnosis of stator inter-turn short circuit in doubly fed induction generators. IFAC Proceedings Volumes44(1): 1013–1018. https://doi.org/10.3182/20110828-6-IT-1002.02217
29.
MaKZhuJSoltaniM, et al. (2020) Inter-turn short-circuit fault ride-through for DFIG wind turbines. IFAC-PapersOnLine53(2): 12757–12762. https://doi.org/10.1016/j.ifacol.2020.12.1916
30.
MaitreJGabourySBouchardB, et al. (2015) A new computational method for stator faults recognition in induction machines based on hyper-volumes In: 2015 IEEE International Conference on Electro/Information Technology (EIT). Dekalb, IL, USA. IEEE, pp. 216–220. https://doi.org/10.1109/EIT.2015.7293343
31.
Mejia-BarronATapia-TinocoGRazo-HernandezJR, et al. (2021) A neural network-based model for MCSA of inter-turn short-circuit faults in induction motors and its power hardware in the loop simulation. Computers & Electrical Engineering93: 107234. https://doi.org/10.1016/j.compeleceng.2021.107234
32.
NoureddineLHadjadjMDjoudiHCB, et al. (2024) Condition monitoring through DWT-PSD-FLS approach of faulty wind generators. Wind Engineering48(1): 55–64. https://doi.org/10.1177/0309524X231200237
33.
PiltanFKimJM (2018) Bearing fault diagnosis by a robust higher-order super-twisting sliding mode observer. Sensors18(4): 1128. https://doi.org/10.3390/s18041128
34.
RazafimahefaTDBilalHHeraudN, et al. (2019) Experimental and analytical approaches for investigating low-level inter-turn winding faults in induction machine. In: 2019 4th Conference on Control and Fault Tolerant Systems (SysTol). Casablanca, Morocco: IEEE, pp. 135–140. https://doi.org/10.1109/SYSTOL.2019.8864786
35.
Riera-GuaspMAntonino-DaviuJPineda-SanchezM, et al. (2008) A general approach for the transient detection of slip-dependent fault components based on the discrete wavelet transform. IEEE Transactions on Industrial Electronics55(12): 4167–4180. https://doi.org/10.1109/TIE.2008.2004378
36.
RoshanfekrRJalilianA (2015) Analysis of rotor and stator winding inter-turn faults in WRIM using simulated MEC model and experimental results. Electric Power Systems Research119: 418–424. https://doi.org/10.1016/j.epsr.2014.10.018
37.
ShahDNandiSNetiP (2009) Stator-interturn-fault detection of doubly fed induction generators using rotor-current and search-coil-voltage signature analysis. IEEE Transactions on Industry Applications45(5): 1831–1842. https://doi.org/10.1109/tia.2009.2027406
38.
SinghGSundaramKMatuontoM (2021) A solution to reduce overheating and increase wind turbine systems availability. Wind Engineering45(3): 491–504. https://doi.org/10.1177/0309524X20910992
39.
StefaniAYazidiARossiC, et al. (2008) Doubly fed induction machines diagnosis based on signature analysis of rotor modulating signals. IEEE Transactions on Industry Applications44(6): 1711–1721. https://doi.org/10.1109/TIA.2008.2006322
40.
StojcicGPasanbegovicKWolbankTM (2014) Detecting faults in doubly fed induction generator by rotor side transient current measurement. IEEE Transactions on Industry Applications50(5): 3494–3502. https://doi.org/10.1109/TIA.2014.2308366
41.
TallamRMLeeSBStoneGC, et al. (2007) A survey of methods for detection of stator-related faults in induction machines. IEEE Transactions on Industry Applications43(4): 920–933. https://doi.org/10.1109/TIA.2007.900448
42.
ThorsenOVDalvaM (1994) A survey of faults on induction motors in offshore oil industry, petrochemical industry, gas terminals and oil refineries. Proceedings of IEEE Petroleum and Chemical Industry Technical Conference (PCIC’94). IEEE, 1–9. Available at: https://doi.org/10.1109/PCICON.1994.347637
43.
TomaSCapocchiLCapolinoGA (2013) Wound-rotor induction generator inter-turn short-circuits diagnosis using a new digital neural network. IEEE Transactions on Industrial Electronics60(9): 4043–4052. https://doi.org/10.1109/TIE.2012.2229675
44.
UkilAChenSAndennaA (2011) Detection of stator short circuit faults in three-phase induction motors using motor current zero crossing instants. Electric Power Systems Research81(4): 1036–1044. https://doi.org/10.1016/j.epsr.2010.12.003
45.
WolkiewiczMTarchalaGOrlowska-KowalskaT, et al. (2016) Online stator interturn short circuits monitoring in the DFOC induction-motor drive. IEEE Transactions on Industrial Electronics63(4): 2517–2528. https://doi.org/10.1109/TIE.2016.2520902
