Abstract
This paper presents a method for the diagnosis of induction machines faults. The proposed method is capable to detect the presence of both dynamic eccentricity and broken rotor bar faults. Several studies have attempted to model an induction machine with isolated faults and provide methods for detecting them. However, the challenge begins, with the occurrence of combined defects which produce fault signatures that are difficult to separate. The novel proposed method is based on the measured air-gap magnetic flux density spectrum, which allows for the detection of combined faults. A finite element method is used for modelling the induction machine under faulty conditions, where the faults of rotor bars are created by a deleting operation of the boundary condition which is added to the air-gap part. Then, the dynamic eccentricity is formed by the movements of the rotating rotor’s centre with different ratings. From a modelling perspective, the contribution of the current work is the establishment of the relation of the air-gap of the rotor for modelling this kind of eccentricity fault. In addition, the proposed model of the air-gap includes two parts; one related to the stator and another one to the rotor, called statoric air-gap and rotoric air-gap respectively. The rotoric air-gap is employed for the dynamic eccentricity modelling. Computer simulations are presented using the air-gap magnetic vector and the magnetic field in X and Y components, to confirm the robustness of the proposed technique. Finally, the air-gap magnetic flux density spectrum is used for the analysis of combined rotor faults.
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References
Antonino-Daviu J, Jover Rodriguez P, Riera-Guasp M et al (2009) Detection of combined faults in induction machines with stator parallel branches through the DWT of the startup current. Mech Syst Signal Process 23:2336–2351. doi:10.1016/j.ymssp.2009.02.007
Arkkio A (1990) Finite element analysis of cage induction motors fed by static frequency converters. IEEE Trans Magn 26:551–554. doi:10.1109/20.106376
Baccarini LMR, de Menezes BR, Caminhas WM (2010) Fault induction dynamic model, suitable for computer simulation: simulation results and experimental validation. Mech Syst Signal Process 24:300–311. doi:10.1016/j.ymssp.2009.06.014
Benbouzid M (2000) A review of induction motors signature analysis as a medium for faults detection. IEEE Trans Industr Electron 47:984–993. doi:10.1109/41.873206
Bessous N, Zouzou SE, Bentrah W et al (2016) Diagnosis of bearing defects in induction motors using discrete wavelet transform. Int J Syst Assur Eng Manag. doi:10.1007/s13198-016-0459-6
Bhattacharya A, Dan PK (2014) Recent trend in condition monitoring for equipment fault diagnosis. Int J Syst Assur Eng Manag 5:230–244. doi:10.1007/s13198-013-0151-z
Boudinar AH, Benouzza N, Bendiabdellah A (2015) Bearing fault diagnosis of induction motor [Diagnostic des défauts de roulements d’un moteur asynchrone]. Rev Roum des Sci Tech Ser Electrotech et Energ 60:39–48
Boughrara K, Takorabet N, Ibtiouen R et al (2015) Analytical analysis of cage rotor induction motors in healthy, defective, and broken bars conditions. IEEE Trans Magn 51:1–17. doi:10.1109/TMAG.2014.2349480
Camarena-Martinez D, Osornio-Rios R, Romero-Troncoso RJ, Garcia-Perez A (2015) Fused empirical mode decomposition and music algorithms for detecting multiple combined faults in induction motors. J Appl Res Technol 13:160–167. doi:10.1016/S1665-6423(15)30014-6
Cameron JR, Thomson WT, Dow AB (1986) Vibration and current monitoring for detecting airgap eccentricity in large induction motors. IEEE Proc B Electr Power Appl 133:155. doi:10.1049/ip-b.1986.0022
Ceban A, Pusca R, Romary R (2010) Eccentricity and broken rotor bars faults-Effects on the external axial field. In: The XIX international conference on electrical machines-ICEM 2010. IEEE, pp 1–6
Ceban A, Pusca R, Romary R (2012) Study of rotor faults in induction motors using external magnetic field analysis. IEEE Trans Industr Electron 59:2082–2093. doi:10.1109/TIE.2011.2163285
Chattopadhyaya A, Sengupta S, Chattopadhyay S et al (2013) Analysis of stator current of induction motor used in transport system at single phasing by measuring phase angle, symmetrical components, Skewness, Kurtosis and harmonic distortion in Park plane. IET Electr Syst Transp 4:1–8. doi:10.1049/iet-est.2012.0048
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 27:71–84. doi:10.1109/TEC.2011.2178027
Dorrell DG, Thomson WT, Roach S (1997) Analysis of airgap flux, current, and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors. IEEE Trans Ind Appl 33:24–34. doi:10.1109/28.567073
Faiz J, Ebrahimi BM (2009) Locating rotor broken bars in induction motors using finite element method. Energy Convers Manag 50:125–131. doi:10.1016/j.enconman.2008.08.025
Faiz J, Moosavi SMM (2016) Eccentricity fault detection—from induction machines to DFIG—A review. Renew Sustain Energy Rev 55:169–179. doi:10.1016/j.rser.2015.10.113
Faiz J, Ojaghi M (2009) Unified winding function approach for dynamic simulation of different kinds of eccentricity faults in cage induction machines. IET Electr Power Appl 3:461. doi:10.1049/iet-epa.2008.0206
Faiz J, Ebrahimi BM, Akin B, Toliyat HA (2010) Dynamic analysis of mixed eccentricity signatures at various operating points and scrutiny of related indices for induction motors. IET Electr Power Appl 4:1. doi:10.1049/iet-epa.2008.0224
Goktas T, Zafarani M, Akin B (2016) Discernment of broken magnet and static eccentricity faults in permanent magnet synchronous motors. IEEE Trans Energy Convers 31:578–587. doi:10.1109/TEC.2015.2512602
Guedidi S, Zouzou SE, Laala W et al (2013) Induction motors broken rotor bars detection using MCSA and neural network: experimental research. Int J Syst Assur Eng Manag 4:173–181. doi:10.1007/s13198-013-0149-6
Halem N, Zouzou SE, Srairi K et al (2013) Static eccentricity fault diagnosis using the signatures analysis of stator current and air gap magnetic flux by finite element method in saturated induction motors. Int J Syst Assur Eng Manag 4:118–128. doi:10.1007/s13198-013-0164-7
Hanafy HH, Abdo TM, Adly AA (2014) 2D finite element analysis and force calculations for induction motors with broken bars. Ain Shams Eng J 5:421–431. doi:10.1016/j.asej.2013.11.003
Hernandez-Vargas M, Cabal-Yepez E, Garcia-Perez A (2014) Real-time SVD-based detection of multiple combined faults in induction motors. Comput Electr Eng 40:2193–2203. doi:10.1016/j.compeleceng.2013.12.020
Ho SL, Fu WN, Wong HC (1998) Estimation of stray losses of skewed rotor induction motors using coupled 2-D and 3-D time stepping finite element methods. IEEE Trans Magn 34:3102–3105. doi:10.1109/20.717726
Huangfu Y, Wang S, Qiu J et al (2014) Transient performance analysis of induction motor using field-circuit coupled finite-element method. IEEE Trans Magn 50:873–876. doi:10.1109/TMAG.2013.2281314
Iamamura BAT, Le Menach Y, Tounzi A et al (2010) Study of static and dynamic eccentricities of a synchronous generator using 3-D FEM. IEEE Trans Magn 46:3516–3519. doi:10.1109/TMAG.2010.2043347
Iamamura BAT, Le Menach Y, Tounzi A, et al (2012) Study of synchronous generator static eccentricities FEM results and measurements. In: Proceedings—2012 20th international conference on electrical machines, ICEM 2012. pp 1829–1835. doi: 10.1109/ICElMach.2012.6350130
Iga Y, Takahashi K, Yamamoto Y (2016) Finite element modelling of turbine generator stator end windings for vibration analysis. IET Electr Power Appl 10:75–81
Kaikaa MYMY, Hadjami M, Khezzar A (2014) Effects of the simultaneous presence of static eccentricity and broken rotor bars on the stator current of induction machine. IEEE Trans Industr Electron 61:2942. doi:10.1109/TIE.2013.2288899
Kaltenbacher M (2015) Electromagnetic field. In: Numerical simulation of mechatronic sensors and actuators. Springer, Berlin, pp 227–283
Kettunen L, Kurz S, Tarhasaari T et al (2014) Modeling rotation in electrical machines. IEEE Trans Magn 50:1–10. doi:10.1109/TMAG.2013.2290101
Kim U, Lieu DK (1998) Magnetic field calculation in permanent magnet motors with rotor eccentricity: without slotting effect. IEEE Trans Magn 34:2243–2252. doi:10.1109/20.703862
Kim J, Shin S, Bin Lee S et al (2015) Power spectrum-based detection of induction motor rotor faults for immunity to false alarms. IEEE Trans Energy Convers 30:1123–1132. doi:10.1109/TEC.2015.2423315
Labiod C, Bahri M, Srairi K et al (2017) Static and dynamic analysis of non-linear magnetic characteristics in switched reluctance motors based on circuit-coupled time stepping finite element method. Int J Syst Assur Eng Manag 8:47–55. doi:10.1007/s13198-014-0294-6
Lee SS, Hong J, Lee SSB et al (2013) Evaluation of the influence of rotor axial air ducts on condition monitoring of induction motors. IEEE Trans Ind Appl 49:2024–2033. doi:10.1109/TIA.2013.2259132
Li S, Li Y, Sarlioglu B (2016) Rotor unbalanced magnetic force in flux-switching permanent magnet machines due to static and dynamic eccentricity. Electr Power Compon Syst 44:336–342. doi:10.1080/15325008.2015.1111469
Mabrouk AE, Zouzou SE, Khelif S, Ghoggal A (2017) On-line fault diagnostics in operating three-phase induction motors by the active and reactive currents. Int J Syst Assur Eng Manag 8:160–168. doi:10.1007/s13198-015-0364-4
Naderi P, Fallahi F (2016) Eccentricity fault diagnosis in three-phase-wound-rotor induction machine using numerical discrete modeling method. Int J Numer Model Electron Networks Devices Fields 29:982–997. doi:10.1002/jnm.2157
Nandi S, Ahmed S, Toliyat HA (2001) Detection of rotor slot and other eccentricity related harmonics in a three phase induction motor with different rotor cages. IEEE Trans Energy Convers 16:253–260. doi:10.1109/60.937205
Park J-K, Hur J (2016) Detection of inter-turn and dynamic eccentricity faults using stator current frequency pattern in IPM-type BLDC motors. IEEE Trans Industr Electron 63:1771–1780. doi:10.1109/TIE.2015.2499162
Rodríguez PVJ, Negrea M, Arkkio A (2008) A simplified scheme for induction motor condition monitoring. Mech Syst Signal Process 22:1216–1236. doi:10.1016/j.ymssp.2007.11.018
Romary R, Corton R, Thailly D, Brudny JF (2005) Induction machine fault diagnosis using an external radial flux sensor. Eur Phys J Appl Phys 32:125–132. doi:10.1051/epjap:2005079
Romero-Troncoso RJ, Saucedo-Gallaga R, Cabal-Yepez E et al (2011) FPGA-based online detection of multiple combined faults in induction motors through information entropy and fuzzy inference. IEEE Trans Industr Electron 58:5263–5270. doi:10.1109/TIE.2011.2123858
Sahraoui M, Ghoggal A, Guedidi S, Zouzou SE (2014) Detection of inter-turn short-circuit in induction motors using Park-Hilbert method. Int J Syst Assur Eng Manag 5:337–351. doi:10.1007/s13198-013-0173-6
Sakhara S, Saad S, Nacib L (2016) Diagnosis and detection of short circuit in asynchronous motor using three-phase model. Int J Syst Assur Eng Manag. doi:10.1007/s13198-016-0435-1
Seghiour A, Seghier T, Zegnini B (2014) Defects rotor identification by magnetic spectrum analyzing in a squirrel-cage asynchronous machine. In: 2014 International conference on electrical sciences and technologies in Maghreb (CISTEM). IEEE, pp 1–6
Seghiour A, Seghier T, Zegnini B (2015a) Diagnostic of the simultaneous of dynamic eccentricity and broken rotor bars using the magnetic field spectrum of the air-gap for an induction machine. In: 2015 3rd International conference on control, engineering & information technology (CEIT). IEEE, pp 1–6
Seghiour A, Seghier T, Zegnini B (2015b) diagnostic of rotor faults using spectrum magnetic field for an induction machine. In: 2015 1st International conference on applied automation and industrial diagnostics, (ICAAID). Djelfa, pp 1–10
Seghiour A, Seghier T, Zegnini B (2016) Induction machine diagnosis of the broken rotor bars based on air-gap magnetic flux density. In: 2016 8th International conference on modelling, identification and control (ICMIC). IEEE, pp 180–185
Silva AM, Povinelli RJ, Member S et al (2013) Rotor bar fault monitoring method based on analysis of air-gap torques of induction motors. IEEE Trans Industr Inf 9:2274–2283
Tavner PJ (2008) Review of condition monitoring of rotating electrical machines. IET Electr Power Appl 2:215–247. doi:10.1049/iet-epa
Vitek O, Janda M, Hajek V (2010) Effects of eccentricity on external magnetic field of induction machine. In: Melecon 2010–2010 15th IEEE mediterranean electrotechnical conference. IEEE, pp 939–943
Wang X, Xie D (2009) Analysis of induction motor using field-circuit coupled time-periodic finite element method taking account of hysteresis. IEEE Trans Magn 45:1740–1743. doi:10.1109/TMAG.2009.2012802
Wang X, Zhu C, Zhang R et al (2006) Performance analysis of single-phase induction motor based on voltage source complex finite-element analysis. IEEE Trans Magn 42:587–590. doi:10.1109/TMAG.2006.871454
Yang C, Kang T-J, Hyun D et al (2014) Reliable detection of induction motor rotor faults under the rotor axial air duct influence. IEEE Trans Ind Appl 50:2493–2502. doi:10.1109/TIA.2013.2297448
Yang C, Kang T-J, Bin Lee S et al (2015) Screening of false induction motor fault alarms produced by axial air ducts based on the space-harmonic-induced current components. IEEE Trans Industr Electron 62:1803–1813. doi:10.1109/TIE.2014.2331027
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Seghiour, A., Seghier, T., Zegnini, B. et al. Diagnosis of the combined rotor faults using air gap magnetic flux density spectrum for an induction machine. Int J Syst Assur Eng Manag 8 (Suppl 2), 1503–1519 (2017). https://doi.org/10.1007/s13198-017-0621-9
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DOI: https://doi.org/10.1007/s13198-017-0621-9