Abdelkarim BOURAS, Slimane BOURAS, Samir KERFALI

Prediction of the mass unbalance of a variable speed induction motor by stator current multiple approaches

Generally, rotor mass unbalance is one of the most probable causes of the majority of degradations sufferedby electric drives in an industrial environment (current pumping, rolling problem, misalignment, etc.), especially thosewith high power and variable speed. This document is an experimental contribution to the reliable detection of massunbalance and changes in its severity if, by necessity of service, the system is subjected to a speed variation. Theimplementation of the technical orbits Park, strengthened by the application of the Fourier transforms (FFT, STFT) tothe Park vector of the stator current allowed the identification of the unbalance defect at low frequency. The sequenceof current analytical approaches favors the convergence towards an unambiguous reading of the mass unbalance defect.A comparative table has been drawn up in order to observe the evolution of the gravity of this mechanical defect in thecase of a speed variation of the induction motor. The results obtained by this multifaceted approach are very satisfyingand can contribute to a self-diagnostic with the assistance of a decision-making technique.

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[1] Li W, Mechefske CK. Detection of induction motor faults: a comparison of stator current, vibration and acoustic methods. J Vib Control 2006; 12: 165-188.
[2] Kia SH, Henao H, Capolino GA. A comparative study of acoustic, vibration and stator current signatures for gear tooth fault diagnosis. In: ICEM 2012 International Conference on Electrical Machines; 2–5 September 2012; Marseille, France: ICEM. pp. 1512-1517.
[3] Iorgulescu M, Beloiu R. Faults diagnosis for electrical machines based on analysis of motor current. In: OPTIM 2014 International Conference on Optimization of Electrical and Electronic Equipment; 22–24 May 2014; Bran, Romania: OPTIM. pp. 291-297.
[4] Bl¨odt M, Granjon P, Raison B, Regnier J. Mechanical fault detection in induction motor drives through stator current monitoring - Theory and application examples. In: Zhang W, editor. Fault Detection. Rijeka, Croatia: INTECH, 2010. pp. 451-488.
[5] Choi S, Pazouki E, Baek J, Bahrami HR. Iterative condition monitoring and fault diagnosis scheme of electric motor for harsh industrial application. IEEE T Ind Electron 2015; 62: 1760-1769.
[6] Salah M, Bacha K, Chaari A. Stator current analysis of a squirrel cage motor running under mechanical unbalance condition. In: IEEE 2013 10th International Multi-Conference on Systems, Signals & Devices (SSD); 18–21 March 2013; Hammamet, Tunisia: IEEE. pp. 1-6.
[7] Granjon P, Vieira M, Sieg-Zieba S. Surveillance du d´esalignement d’un moteur asynchrone par analyse du vecteur d’espace courant. In: Workshop of GIS 2009 Surveillance, suret´e, s´ecurit´e des grands syst`emes; 3–4 June 2009; Nancy, France: GIS. pp. 1-7.
[8] Zarei J, Poshtan J. An advanced park’s vectors approach for bearing fault detection. In: IEEE 2006 Conference on Industrial Technology; 15–17 December 2006; Mumbai, India: IEEE. pp. 1472-1479.
[9] Fernao Pires AV, Martins JF, Pires AJ. Eigenvector/eigenvalue analysis of a 3D current referential fault detection and diagnosis of an induction motor. Energ Convers Manage 2010; 51: 901-907.
[10] Obaid RR, Habetler TG. Effect of load on detecting mechanical faults in small induction motors. In: SDEMPEDS 2003 Symposium on Diagnostics for Electric Machines, Power Electronics and Driver; 24–26 August 2003; Atlanta, GA, USA: IEEE. pp. 307-311.
[11] Intesar A, Manzar A, Kashif I, Shuja Khan M, Junaid Akhtar S. Detection of eccentricity faults in machine using frequency spectrum technique. International Journal of Computer and Electrical Engineering 2011; 3: 111-119.
[12] Bl¨odt M, Chabert M, Regnier J, Faucher J. Mechanical load fault detection in induction motors by stator current time-frequency analysis. IEEE T Ind Appl 2006; 42: 1454-1463.
[13] Metatla A, Benzahioul S, Bahi T, Lefebvre D. On line current monitoring and application of a residual method for eccentricity fault detection. Adv Electr Comput En 2011; 11: 69-72.
[14] Fern´andez G´omez AJ, Sobczyk TJ. Motor current signature analysis apply for external mechanical fault and cage asymmetry in induction motors. In: SDEMPED 2013 9th IEEE International Symposium; 27–30 August 2013; Valencia, Spain: IEEE. pp. 136-141.
[15] Krishna MSR, Ravi KS. Fault diagnosis of induction motor using motor current signature analysis. In: ICCPCT 2013 International conference on circuits, power and computing technologies; 20–21 March 2013; Nagercoil, India: IEEE. pp. 180-186.
[16] Leite VCMN, Borges da Silva JG, Cintra Veloso GF, Borges da Silva LE. Detection of localized bearing faults in induction machines by spectral kurtosis and envelope analysis of stator current. IEEE T Ind Electron 2015; 62: 1855-1865.
[17] Messaoudi M, Sbita L. Multiple faults diagnosis in induction motor using the MCSA method. International Journal of Signal and Image Processing 2010; 1: 190-195.
[18] Pires VF, Kadivonga M, Martins JF, Pires AJ. Motor square current signature analysis for induction motor rotor diagnosis. Elsevier Measurement 2013; 46: 942-948.
[19] Martins JF, Pires VF, Amaral T. Induction motor fault detection and diagnosis using a current state space pattern recognition. Pattern Recogn Lett 2011; 32: 321-328.
[20] Sonje DM, Chowdhury A, Kundu P. Fault diagnosis of induction motor using parks vector approach. In: ICAEE 2014 International Conference on Advances in Electrical Engineering; 9–11 January 2014; Vellore, India: IEEE. pp. 1-4.
[21] Diallo D, Benbouzid MEH, Hamad D, Pierre X. Fault detection and diagnosis in induction machine drive: a pattern recognition approach based on Concordia stator mean current vector. IEEE T Energy Conver 2005; 20: 512-519.
[22] Vieira M, Theys C, Benbouzid MEH. Induction motors faults detection and localisation using stator current advanced signal processing techniques. IEEE T Power Electr 1999; 14: 14-22.
[23] Cruz SMA, Cardoso AZJM. Stator winding fault diagnosis in three phase synchronous and asynchronous motors, by the extended Park’s vector approach. IEEE T Ind Appl 2001; 37: 1227-1233.
[24] Flandrin P. Temps – Fr´equence. Trait´e des nouvelles technologies. Paris, France: Edition Herm`es, 1993.
[25] Jianguo J, Zhiping Z, Pengshang S, Xiangheng W. Time frequency spectrum (TSF) of line current during starting process – A tool for diagnosing failure of induction motor. In: The International Conference on Electrical Machines; 15–17 September 1992; Manchester, United Kingdom: ICEM. pp. 1261-1265.
[26] Cohen L. Time Frequency Analysis. Upper Saddle River, NJ, USA: Prentice Hall, 1995.