Observer-based IM stator fault diagnosis: Experimental validation

Khadidja El Merraoui, Abdellaziz Ferdjouni, M’hamed Bounekhla


In this paper, an experimental validation of an efficient approach to the Fault Detection and Isolation (FDI) of Induction Motor (IM) is proposed. The problem of Inter-turn short circuits (ITSC) in the stator windings is addressed. By introducing fault factors in the IM model an observer-based residual generator is designed, allowing the detection of ITSC in stator windings. The residual generator is built around an extended Kalman Filter (EKF) in order to estimate state variables and fault factors, which permits the evaluation of the severity of the fault. To overcome the problem of tuning the EKF a PSO algorithm is developed. It carries out a heuristic search of the noise matrices by optimizing a cost function. The proposed solution is validated by computer simulations and by real-time implementation on dSPACE 1104 Digital Signal Processor (DSP) test-bench under the healthy and the faulty conditions of IM. To perform tests under faulty conditions, an IM with customized design is built and the stator is rewound permitting to create ITSC. The results reveal the quick detection of the faults, the quantification of its severity and confirm the efficacy of this observer-based FDI algorithm.


Fault Detection and Isolation, Induction motor model ,Inter-turn short circuit, Extended Kalman Filter, PSO algorithm

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A.Singh, B. Grant, R. De Four, S.Chandrabhan, S.Bahadoorsinghet, "A review of induction motor fault modeling", Electric Power Systems Research, vol. 133, pp.191-197, 2016.

G.K.Singh andS.A.S. Al Kazzaz,"Induction machine drive condition monitoring and diagnostic research—a survey", Electric Power Systems Research, vol. 64, no.2, pp.145-158, 2003.

R.Sharifi andM. Ebrahimi, " Detection of stator winding faults in induction motors using three-phase current monitoring", ISA Transactions, vol. 50, no.1, pp.14-20, 2011.

M.E.H. Benbouzid, "A review of induction motors signature analysis as a medium for faults detection", IEEE Transactions on Industrial Electronics, vol. 47, no. 5, pp.984-993, 2000.

S.K. Ahmed, A.Sarkar, M.Mitra, andS. Sengupta, " Dsp implementation of a novel envelope analysis approach for the diagnosis of broken bar in induction motor ", Int. J. Modelling, Identification and Control (IJMIC), 2014, vol. 22, no. 3, pp.275-284.

X.W. Tan, L. Zhang, S.Q. Liu, "An on line broken bar fault detection method and its application to squirrel-cage ashynchronous motors", Int. J. Modelling, Identification and Control(IJMIC),vol. 19, no. 1, pp.89-97, 2013.

S.R. Huang, K.H. Huang, K.H. Chao and W-T. Chiang,"Fault analysis and diagnosis system for induction motors", Computers & Electrical Engineering, 2016, vol. 54, pp.1-15.

A. Glowacz, "Acoustic based fault didgnosis of three-phase induction motor", Elsevier, vol. 137, pp. 82-89, 2018.

M.Thirumarimurugan, N.Bagyalakshmi andP.Paarkavi, "Comparison of fault detection and isolation methods: A review", 2016 10th International Conference on Intelligent Systems and Control (ISCO), Tamilnadu, India, 2016, pp. 1-6.

R.Isermann,"Model-based fault-detection and diagnosis–status and applications", Annual Reviews in Control, 2005, vol. 29, no. 1, pp. 71-85.

X. Chang, V.Cocquempot andC. Christophe, " A model of asynchronous machines for stator fault detection and isolation", IEEE Transactions on Industrial Electronics, 2003, vol. 50, no. 3, pp. 578-584.

R.M.Tallam, T.G.Habetler, R.G. Harley, "Transient model for induction machines with stator winding turn faults", IEEE Transactions on Industry Applications, 2002, vol. 38, no. 3, pp.632-637.

C.H.D. Angelo, R. Guillermo, G.R.Bossio, María Inés Valla, J. A. Solsona, and G. O. García,"Online Model-Based Stator-Fault Detection and Identification in Induction Motors", IEEE Transactions on Industrial Electronics, 2009, vol. 56, no. 11, pp. 4671-4680.

C.S.Kallesoe, R.I.Zamanabadi, P.Vadstrup,P. Vadstrup, and H. Rasmussen," Observer-Based Estimation of Stator-Winding Faults in Delta-Connected Induction Motors: A Linear Matrix Inequality Approach", IEEE Transactions on Industry Applications, 2007, vol. 43, no. 4, pp. 1022-1031.

A.Ferdjouni, H.Salhi, M.Djemaï and K. Busawon, "Observer-based detection of inter-turn short circuit in three phase induction motor stator windings", Mediterranean Journal of Measurement and Control, 2006, vol. 2, no. 3, pp.132-143.

F.Karami, J.Poshtanand M.Poshtan, "Detection of broken rotor bars in induction motors using nonlinear Kalman filters", ISA Transactions, 2010, vol. 49, no. 2, pp. 189-195.

M.S.Naït Said, M.E.Benbouzid andA.Benchaib, "Detection of broken bars in induction motors using an extended Kalman filter for rotor resistance sensorless estimation", IEEE Transactions on Energy Conversion , 2000, vol. 15, no. 1, pp. 66-70.

K. El Merraoui andA.Ferdjouni, "Detection of inter-turn short circuits in stator windings of im by extended Kalman filters",22nd Mediterranean Conference on Control and Automation (MED), 2014, pp. 275-280.

F.Bagheri, H.Khaloozaded andK.Abbaszadeh, "Stator fault detection in induction machines by parameter estimation, using adaptive Kalman filter",Control & Automation 2007, MED'07, Mediterranean Conference on, 2007, pp.1-6.

F.Alonge, F.D'Ippolito, A.Fagiolini, A. Sferlazza, "Extended complex Kalman filter for sensorless control of an induction motor ", Control Engineering Practice, 2014, 27, pp.1-10.

Z.G. Yin, C. Zhao, R.U. Yan, Y.R.Zhong, "Research on Robust Performance of Speed-Sensorless Vector Control for the Induction Motor Using an Interfacing Multiple-Model Extended Kalman Filter", IEEE Transactions on Power Electronics, 2014, vol. 29, no. 6, pp. 3011-3019.

M.Hilairet, F.Auger andE. Berthelot, "Speed and rotor flux estimation of induction machines using a two-stage extended Kalman filter", Automatica, 2009, vol. 45, no. 8, pp. 1819-1827.

K. El Merraoui andA.Ferdjouni, "PSO parameters optimization for EKF and AKF for IM rotor speed estimation", Power Electronics and Motion Control Conference and Exposition (PEMC), 2014 16th International, 2014, pp. 82-387.

M. Moujahed, H. Ben azza, M.Jemliand M. Boussak,"Extended Kalman Filter for Tolerant Vector Control of PMSM with stator resistance estimation ", International Journal on Electrical and Informatics, 2017, vol. 9, no. 1, pp. 207-221.

Y. Dan Huo, Z.H.Cai, W.Yin Gong andQ. Liu,"The parameter Optimiwation of Kalman Filter Based on Multi-Objective Memetic Algorithm", Proceedings of the 2014 Genetic and Evolutionary Computation Conference (GECCO 2014), pp:613-620.

K.L. Shi, Y.K.Wong and S.L. Ho, "Speed estimation of an Induction motor drive using an optimized extended Kalman filter", IEEE Trans. Ind. Electron, 2002, vol. 49, pp.124-133.

P.L. Alger, "Induction Machines: Their Behavior and Uses"(Ed.) CRC Press,1995, New York, USA.

M.S.Grewal and A.P. Andrews, "Kalman Filtering: Theory and Practice Using Matlab", in John Wiley & Sons (Ed), 2008, N.Y, USA.

J. Kennedy andR.C.Eberhart,"Particle swarm optimization", inProceedings of the IEEE international conference on neural networks, Piscataway, USA, 1995, pp. 1942-1948.

M. E.Zaïm, K.Dakhouche andM.Bounekhla, "Using two PSO-structures approaches to estimate induction machine parameters",Power Electronics and Applications, EPE '09, Barcelona, Conf. 2009, pp.1189-1192.



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Copyright (c) 2020 khadidja El Merraoui, Abdellaziz Ferdjouni, M’hamed Bounekhla

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ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License