Induction Motor Stator Fault Diagnosis by Rotor Slots Harmonics Tracking Using Prony Improved Approach
The short-circuit fault diagnosis is essential in order to avoid irreversible damages that could affect the stator circuit of the induction motor. For this purpose, this paper addresses a new approach based on Prony's high resolution spectral analysis method to avoid the drawbacks of the well-known method based on the power spectral density estimation by Periodogram technique. This new approach, called Root-Prony, allows a better frequency resolution even on a very short acquisition time as well as a better detection even on very small magnitudes. Moreover, and in order to reduce the computation time of this approach, this paper proposes to analyze only the band around the first rotor slot frequencies. The choice of this band allows avoiding any confusion with the frequency signatures of external phenomena which appear most often in very low frequencies. The experimental results obtained show the efficiency and the reliability of this new approach in tracking the induction motor stator winding degradation.
Copyright © 2017 Praise Worthy Prize - All rights reserved.
X. Yang, R. Yan, R. X. Gao, Induction motor fault diagnosis using multiple class feature selection, IEEE International Instrumentation and Measurement Technology Conference (12MTC), pp. 256 – 260, Piza, Italy, May 2015.
H. A. Toliyat, S. Nandi, S. Choi, H. Meshgin-Kelm, Electric Machines: Modeling, Condition Conitoring, and Fault Diagnosis (Taylor & Francis Group Eds., 2012).
A. G.Perez, R. J. R.Troncoso, E. C.Yepez, and R. A. O.Rios, The Application of High-Resolution Spectral Analysis for Identifying Multiple Combined Faults in Induction Motors, IEEE Transactions on Industrial Electronics, Vol. 58, (Issue 5): 447-464, May 2014.
Gentile, G., Meo, S., Ometto, A., Induction motor current signature analysis to diagnostics, of stator short circuits, (2003) IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2003 - Proceedings, art. no. 1234545, pp. 47-51.
E.H.E. Bouchikhi, V. Choqueuse, M. Benbouzid , A parametric spectral estimator for faults detection in induction machines, Inductrial Electronic Society (IECON 2013) IEEE Conference, pp. 7358 - 7363, Austria, November 2013.
D. Pei, S. Yang, H. Yan, Q. Wang, M. Li, High Efficient and Real-Time Realization of Zoom FFT Based on FPGA, Computer Application and System Modeling (ICCASM) Conference, Vol. 2, pp. 669-673, Taiyuan, November 2010.
H. Ma, Q. Xu, J. Song, J. Han, The Application of Zoom FFT Technique to the Extraction of Fault Character of Induction Motor, Condition Monitoring and Diagnosis Conference, pp. 221-225,Beijing, July 2008.
B.Al Qudsi, N. Joram, A. Strobel, F. Ellinger, Zoom FFT for Precise Spectrum Calculation in FMCW Radar using FPGA, Ph.D. Research in Microelectronics and Electronics (PRIME) Conference, pp. 337-340, Villach, September 2013.
S.Chen, R.Zivanovic, Estimation of Frequency Components in Stator Current for the Detection of Broken Rotor Bars in Induction Machines, Measurement, Vol. 43, (Issue 7): 887-900, August 2010.
A.H. Boudinar, N. Benouzza, A. Bendiabdellah and M.A.Khoudja, Induction Motor Bearing Fault Analysis Using Root-MUSIC Method, IEEE Transactions on Industry applications, Vol. 52, (Issue 5): 3851-3860, June 2016.
D.H. Hwang, Y.W. Youn, J.H. Sun and Y.H. Kim, Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors, Journal of Electrical Engineering & Technology, Vol. 9, (Issue 1): 37-44, January 2014.
Amirat, Y., Choqueuse, V., Benbouzid, M., Turri, S., Hilbert transform-based bearing failure detection in DFIG-based wind turbines, (2011) International Review of Electrical Engineering (IREE), 6 (3), pp. 1249-1256.
A.G. Espinosa, J. A. Rosero, J. Cusido, L. Romeral, and J. A. Ortega, Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM with Demagnetization, IEEE Transactions on Energy Conversion, vol. 25, (Issue 2):312-318, June 2010.
J. A. Antonino-Daviu, M. Riera-Guasp, M. Pineda-Sanchez and R. B. Pérez, A Critical Comparison Between DWT and Hilbert–Huang-Based Methods for the Diagnosis of Rotor Bar Failures in Induction Machines, IEEE Transactions on Industrial Electronics, Vol. 45, (Issue 5):1794-1803, September-october 2009.
R. Yan , R. X. Gao, Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring, IEEE Transactions on Instrumentation and Measurement, Vol.55, (Issue 6):2320-2329, December 2006.
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 transactions on industrial electronics, Vol. 60, (Issue 9):4103-4117, September 2013.
M. Sahraoui, A. J. M. Cardoso and A. Ghoggal, The Use of a Modified Prony Method to Track the Broken Rotor Bar Characteristic Frequencies and Amplitudes in Three-Phase Induction Motors, IEEE Transactions on Industry applications, vol. 51, (Issue 3): 2136 – 2147, May-June 2015.
F. Cong, A. K Nandi, Z. He, A. Cichocki, T. Ristaniemi, Fast and Effective Model Order Selection Method to Determine the Number of Sources in a Linear Transformation Model, European Signal Processing conference (EUSIPCO), pp. 1870-1874, Bucharest, 2012.
S. Das, P. Purkait, S. Chakravorti, Characterization of Short Circuit Faults and Incipient Insulation Degradation Between Stator Winding Turns of Induction Motor, Condition Assessment Techniques in Electrical Systems (CATCON) IEEE Conference, pp. 54-59, Kolkata,2013.
A.Stavrou, H.Sedding and J.Penman, Current Monitoring for Detecting Inter-Turn Short Circuits in Induction Motors, IEEE Transactions on Energy Conversion, Vol.16, (Issue 1):32-37, March 2001.
A. Yazidi, H. Henao, G.A. Capolino, F. Betin, L. Capocchi, Experimental Inter-Turn Short Circuit Fault Characterization of Wound Rotor Induction Machines, IEEE International symposium on Industrial Electronics, pp. 2615-2620, Bari, Italy, July 2010.
G.M. Joksimovic´, J. Penman, The Detection of Inter-Turn Short Circuits in the Stator Windings of Operating Motors, IEEE Transactions on Industrial Electronics, Vol. 47, (Issue 5): 1078-1084, October 2000.
S. Nandi, H. A. Toliyat, Novel Frequency Domain Based Technique to Detect Incipient Stator Inter-Turn in Induction Machines Using Stator Induced Voltages After Switch Off, IEEE Transactions on Industry Applications, Vol. 38, (Issue 1): 101-109, 2002.
P.S. Bhowmik, S. Pradhan and M. Prakash, Fault Diagnostic and Monitoring Methods of Induction Motor: A Review, International Journal of Applied Control, Electrical and Electronics Engineering, Vol. 1, (Issue 1): 1-18, May 2013.
M. Benbouzid, G. B. Kliman, What Stator Current Processing Based Technique to Use for Induction Motor Rotor Faults Diagnosis?, IEEE Transactions on Energy Conversion, Vol. 18, (Issue 2): 238-244, June 2003.
Meo, S., Ometto, A., Rotondale, N., Diagnostic-oriented modelling of induction machines with stator short circuits, (2012) International Review on Modelling and Simulations (IREMOS), 5 (3), pp. 1202-1209.
Meo, S., Ometto, A., Rotondale, N., Influence of closed-loop control operations on detecting induction machine stator faults, (2012) International Review of Electrical Engineering (IREE), 7 (3), pp. 4359-4365.
Filippetti, F., Franceschini, G., Ometto, A., Meo, S., Survey of neural network approach for induction machine on-line diagnosis, (1996) Proceedings of the Universities Power Engineering Conference, 1, pp. 17-20.
Filippetti, F., Franceschini, G., Tassoni, C., Meo, S., Ometto, A., Neural network aided on-line diagnostics of induction machine stator faults, (1995) Proceedings of the Universities Power Engineering Conference, 1, pp. 148-151.
M.H. Hayes, Statistical Digital Signal Processing and Modelling, (John Wiley & Sons, 1991).
T. JinRui, Y. XiangGen, Z. Zhe, H. ZhiQin, Y. Lei, W. Yuxue, Fault Location in Distribution Networks Using Prony Analysis , Advanced Power System Automation and Protection Conference, pp. 54-59, Beijing, China, October 2011.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2020 Praise Worthy Prize