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http://dx.doi.org/10.5370/JEET.2014.9.1.037

Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors  

Hwang, Don-Ha (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Youn, Young-Woo (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Sun, Jong-Ho (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Kim, Yong-Hwa (Dept. of Electronic Engineering, Myongji University)
Publication Information
Journal of Electrical Engineering and Technology / v.9, no.1, 2014 , pp. 37-44 More about this Journal
Abstract
This paper proposes a new diagnosis algorithm to detect broken rotor bars (BRBs) faults in induction motors. The proposed algorithm is composed of a frequency signal dimension order (FSDO) estimator and a fault decision module. The FSDO estimator finds a number of fault-related frequencies in the stator current signature. In the fault decision module, the fault diagnostic index from the FSDO estimator is used depending on the load conditions of the induction motors. Experimental results obtained in a 75 kW three-phase squirrel-cage induction motor show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to a zoom multiple signal classification (ZMUSIC) and a zoom estimation of signal parameters via rotational invariance techniques (ZESPRIT).
Keywords
Broken rotor bar; Induction motor; Fault diagnosis; Current signal;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 W. T. Thomson and M. Fenger, "Current signature analysis to detect induction motor faults," IEEE Ind. Appl. Mag., vol. 7, no. 4, pp. 26-34, July/Aug. 2001.
2 A. Bellini, F. Filippetti, G. Franceschini, C. Tassoni, and G. B. Kliman, "Quantitative evaluation of induction motor broken bars by means of electrical signature analysis," IEEE Trans. Ind. Appl., vol. 37, no. 5, pp.1248-1255, Sept./Oct. 2001.   DOI   ScienceOn
3 J.-H. Jung, J.-J Lee, and B.-H. Kwon, "Online diagnosis of induction motors using MCSA," IEEE Trans. Ind. Electron., vol. 53, no. 6, pp. 1842-1852, Dec. 2006.   DOI   ScienceOn
4 H. Henao, C. Demian, and G.-A. Capolino, "A frequency-domain detection of stator winding faults in induction machines using an external flux sensor," IEEE Trans. Ind. Appl., vol. 39, no. 5, pp. 1272-1279, Sept./Oct. 2003.   DOI   ScienceOn
5 J. L. Zarader, M. Garnier, and M. Nicollet, "New frequency-filtering zoom," Int. J. Adapt. Control Signal Process., vol. 6, no. 6, pp. 547-560, Jun. 1992.   DOI
6 A. Yazidi, H. Henao, G. A. Capolino, M. Artioli, and F. Filippetti, "Improvement of frequency resolution for three-phase induction machine fault diagnosis," in Proc. 40th IAS Annu. Meeting. Conf. Rec., 2005, vol. 1, pp. 20-25.
7 M. R. W. Group, "Report of large motor reliability survey of industrial and commercial installation, Part II," IEEE Trans. Ind. Appl., vol. IA-21, no. 4, pp. 865-872, July/Aug. 1985.   DOI   ScienceOn
8 M. E. H. Benbouzid, "A review of induction motors signature analysis as a medium for faults detection," IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984-993, Oct. 2000.   DOI   ScienceOn
9 A. Bellini, A. Yazidi, F. Filippetti, C. Rossi, and G.-A. Capolino, "High frequency resolution techniques for rotor fault detection of induction machines," IEEE Trans. Ind. Electron., vol. 55, no. 12, pp. 4200-4209, Dec. 2008.   DOI   ScienceOn
10 A. Ordaz-Moreno, R. de Jesus Romero-Troncoso, J. A. Vite-Frias, J. R. Rivera-Gillen, and A. Garcia-Perez, "Automatic online diagnosis algorithm for broken-bar detection on induction motors based on discrete wavelet transform for FPGA implementation," IEEE Trans. Ind. Electron., vol. 55, no. 5, pp. 2193-2202, May 2008.   DOI   ScienceOn
11 A. Bouzida, O. Touhami, R. Ibtiouen, A. Belouchrani, M. Fadel, and A. Rezzoug, "Fault diagnosis in industrial induction machines through discrete wavelet transform," IEEE Trans. Ind. Electron., vol. 58, no. 9, pp. 4385-4395, Sept. 2011.   DOI   ScienceOn
12 J. Pons-Llinares, J. A. Antonino-Daviu, M. Riera-Guasp, M. Pineda-Sanchez, and V. Climente-Alarcon, "Induction motor diagnosis based on a transient current analytic wavelet transform via frequency Bsplines," IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1530-1544, May 2011.   DOI   ScienceOn
13 M. E. H. Benbouzid, M. Vieira, and C. Theys, "Induction motors' faults detection and localization using stator current advanced signal processing techniques," IEEE Trans. Power Electron., vol. 14, no. 1, pp. 14-22, Jan. 1999.   DOI   ScienceOn
14 F. Cupertino, E. de Vanna, L. Salvatore, and S. Stasi, "Analysis techniques for detection of IM broken rotor bars after supply disconnection," IEEE Trans. Ind. Appl., vol. 40, no. 2, pp. 526-533, Mar./Apr. 2004.   DOI   ScienceOn
15 S. H. Kia, H. Henao, and G.-A. Capolino, "A high-resolution frequency estimation method for three-phase induction machine fault detection," IEEE Trans. Ind. Electron., vol. 54, no. 4, pp. 2305-2314, Aug. 2007.   DOI   ScienceOn
16 Y.-Y. Youn, S.-H. Yi, D.-H. Hwang, J.-H. Sun, D.-S. Kang, and Y.-H. Kim, "MUSIC-based diagnosis algorithm for identifying broken rotor bar faults in induction motors using flux signal," Journal of Electrical Engineering and Technology, vol. 8, no. 2, pp. 288-294, Mar. 2013.   과학기술학회마을   DOI   ScienceOn
17 M. Kristensson, M. Jansson, and B. Ottersten, "Further results and insights on subspace based sinusoidal frequency estimation," IEEE Trans. Signal Process., vol. 49, no. 12, pp. 2962-2974, Dec. 2001.   DOI   ScienceOn
18 Y.-H. Kim, Y.-W. Youn, D.-H. Hwang, J.-H. Sun, and D.-S. Kang, "High-resolution parameter estimation method to identify broken rotor bar faults in induction motors," IEEE Trans. Ind. Electron., will be published.
19 M. Wax and T. Kailath, "Detection of signals by information theoretic criteria," IEEE Trans. Acoust., Speech and Signal Process., vol. ASSP-33, no. 2, pp. 387-392, Apr. 1985.
20 G. Strang, Calculus. Wellesley-Cambridge, 1991.
21 S. M. Kay, Fundamentals of statistical signal processing: detection theory. Englewood Cliffs, NJ: Prentice-Hall, 1993.
22 K. M. Siddiqui, and V. K. Giri, "Broken rotor bar fault detection in induction motors using wavelet transform," in Proc. Computing, Electronics and Electrical Technologies (ICCEET), 2012, pp. 1-6.
23 V. Rashtchi, and R. Aghmasheh, "A new method for identifying broken rotor bars in squirrel cage induction motor based on particle swarm optimization method," World academy of science, engineering and technology, vol. 43, pp. 694-698, July 2010.