Fault Detection and Diagnosis of Broken Bar Problem in Induction Motors Base Wavelet Analysis and EMD Method: Case Study of Mobarakeh Steel Company in Iran
Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.2643626Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 201
 Austin H. Bonnet; George G. Soukup, “Cause and analysis of stator and rotor failures is 3 phase squirrel cage induction motors” IEEE trans-on Industry application vol 28, no. 7, july 2003.pp 921-237.
 G. Eason, B. Noble, and I.N. Sneddon, “On certain integrals of Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529-551, April 1955.
 Yavanda and Bhim Singh "Identification of Three Phase Induction Motor Incipient Faults "19-22 Septamber 2004.
 Ricardo Carvalho J. O. "Dynamic Performance of Induction Motor Under Non Sinousoidal Condition"2002ieee.
 A. Bellini, F. Filippetti, G. Franceschini, C. Tassoni, and G. B. Kilman, “Quantitative evaluation of induction motor broken bars by means of electrical signature analysis,” IEEE Trans. Industry Applications, vol. 37, no. 5, pp. 1248-1255, Sep/Oct 2001.
 J. Faiz, and B. M. Ebrahimi, “Determination of number of rotor broken bars and static eccentricity degree in induction motor under mixed fault,” Electromagnetics, vol. 28, no. 6, pp. 433-449, August 2008.
 G. Didier, E. Ternisien, O. Caspary, and H. Razik, “Fault detection of broken rotor bars in induction motor using a global fault index,” IEEE Trans. Ind. Appl., vol. 42, no. 1, pp. 79-88, Jan./Feb. 2006.
 Riera-Guasp, M, et al., “A General Approach for the Transient Detection of Slip -Dependent Fault Components Based on the Discrete Wavelet Transform,” IEEE Transactions on Industrial Electronics, vol. 55, no. 12, pp. 4167-4180, 2008.
 Siau, J, et al., “Broken Bar Detection in Induction Motors using, New Zealand, 2003.
 S. M. Shashidhara1"Tradeoff Analysis of Wavelet Transform Techniques for the Detection of Broken Rotor Bars in Induction Motors" © Research India Publications, Advance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 3, Number 8 (2013), pp. 1019-1030.
 Norden E. Huang, Zheng Shen, Steven R. Long, Manli C. Wu, Hsing H. Shih, Quanan Zheng," The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis" Published 8 March 1998.DOI: 10.1098/rspa.1998.0193.