Detection of Stator and Rotor Winding Faults in Induction Motor using Park’s Vector Approach

Open Access

Year : 2023 | Volume :12 | Issue : 1 | Page : 6-15
By

Kuldeep Kumar Swarnkar

J.N. Rai

Sulochana Wadhwani

  1. Ph.D. Scholar Delhi Technological University Delhi India
  2. Professor Delhi Technological University Delhi DelhiProfessor India
  3. Professor Madhav Institute of Technology & Science Gwalior India

Abstract

The Induction Motors in every rotating machine’s heart and it’s a very important component in a much. Almost 90 percent of the Induction Motor use in industry as a prime mover. So Induction Motor is necessary to Condition Monitoring for Economic Running Cost. Condition Based Monitoring of Induction Motor has become an important and difficult task for Engineers and Researchers mainly in Industrial applications. Several Condition Monitoring Methods (Technique) including Motor Current Signature Analysis Monitoring, Vibration Monitoring, Acoustic Emission Monitoring, Stray Flux Analysis, Shock Pulse Monitoring, Instantaneous Output Power Variation Analysis, Thermograph but all of these techniques required expensive specialized tools and sensors where Motor Current Signature Analysis method does not necessary any expensive sensors. The Motor Current Signature Analysis technique helps to effectively diagnose faults such as Rotor and Stator winding, Unbalanced Voltage and Load Fault are all examples of faults. The Stator Current Park’s vector analysis is an easy and popular methodology for online discerns between healthy condition and faulty condition Induction Motors and it also tells about different faults. In this paper, Park’s vector Patterns of 3- phase stator current is analyzed for Stator and Rotor winging Fault of Induction Motor. In the presence of multiple faults, the current in the supply stator contains sideband components, causing the circular pattern to be distorted. A three-phase induction motor with 7.5 HP was used to test this technique. The simulation result validated the experimental analysis.

Keywords: Stator Current Park’s vector Approach, Analysis of Motor Current Signature, Stator and Rotor winging Fault.

[This article belongs to Journal of Control & Instrumentation(joci)]

How to cite this article: Kuldeep Kumar Swarnkar, J.N. Rai, Sulochana Wadhwani. Detection of Stator and Rotor Winding Faults in Induction Motor using Park’s Vector Approach. Journal of Control & Instrumentation. 2023; 12(1):6-15.
How to cite this URL: Kuldeep Kumar Swarnkar, J.N. Rai, Sulochana Wadhwani. Detection of Stator and Rotor Winding Faults in Induction Motor using Park’s Vector Approach. Journal of Control & Instrumentation. 2023; 12(1):6-15. Available from: https://journals.stmjournals.com/joci/article=2023/view=90682

Full Text PDF Download

Browse Figures

References

1. A.H. Bonnett and G.C. Soukup, “Cause and analysis of stator and rotor failures in three-phase squirrel-cage induction motors,” IEEE Trans. Ind. Appl., Vol. 28, No. 4, pp. 921–937, Jul./Aug. 1992.
2. A. Siddique, G.S. Yadava, and B. Singh, “A review of stator fault monitoring techniques of induction motors,” IEEE Trans. Energy Convers., Vol. 20, No. 1, pp. 106–114, Mar. 2005.
3. “Report of large motor reliability survey of industrial and commercial installations, part I and II,” IEEE Trans. Ind.Appl.,Vol. IA-21, No. 4, pp. 853–872, Jul. 1985.
4. P. Zhang, Y. Du, T.G. Habetler, and B. Lu, “A survey of condition monitoring and protection methods for medium voltage induction motors,” IEEE Trans. Ind Appl., Vol. 47, No. 1, pp. 34– 46, Jan./Feb. 2011.
5. H. Mahmoud, A.A.E. Abdallh, N. Bianchi, S.M. El-Hakim, A. Shaltout, and L. Dupr, “An inverse approach for interturn fault detection in asynchronous machines using magnetic pendulous oscillation technique,” IEEE Trans. Ind. Appl., Vol. 52, No. 1, pp. 226–233, Jan./Feb. 2016.
6. 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, Sep./Oct. 2003.
7. J.L. Kohler, J. Sottile, and F.C. Trutt, “Condition monitoring of stator windings in induction motors. I. experimental investigation of the effective negative-sequence impedance detector,” IEEE Trans. Ind. Appl., Vol. 38, No. 5, pp. 1447–1453, Sep./Oct. 2002.
8. J. Yun, K. Lee, K. W. Lee, S. B. Lee, and J. Y. Yoo, “Detection and classification of stator turn faults and high-resistance electrical connections for induction machines,” IEEE Trans. Ind. Appl., Vol. 45, No. 2, pp. 666–675, Mar./Apr. 2009.
9. T.G. Vilhekar, M. S. Ballal, and H. M. Suryawanshi, “Application of double park’s vector approach for detection of inter-turn fault in induction motor,” in International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), pp. 173–178, Dec. 2015.
10. A.J.M. Cardoso, S.M.A. Cruz, and D.S.B. Fonseca, “Inter-turn stator winding fault diagnosis in three-phase induction motors, by park’s vector approach,” IEEE Trans. Energy Convers., Vol. 14, No. 3, pp. 595–598, Sep. 1999.
11. H. Nejjari and M.E.H. Benbouzid, “Monitoring and diagnosis of induction motors electrical faults using a current park’s vector pattern learning approach,” IEEE Trans. Ind. Appl., Vol. 36, No. 3, pp. 730–735, May/Jun. 2000.
12. M.S. Ballal, D.M. Ballal, H.M. Suryawanshi, and M.K. Mishra, “Wing technique: A novel approach for the detection of stator winding inter-turn short circuit and open circuit faults in three phase induction motors,” Journal of Power Electronics, Vol. 12, No. 1, pp. 208–214, Jan. 2012.
13. M. S. Ballal, H. M. Suryawanshi, and B. N. Choudhari, “Extended wing technique approach for the detection of winding interturn faults in three phase transformers,” Journal of Power Electronics, Vol. 15, No. 1, pp. 288–297, Jan. 2015.
14. F. Filippetti, G. Franceschini, and C. Tassoni, “Neural networks aided on-line diagnostics of induction motor rotor faults,” IEEE Trans. Ind. Appl., Vol. 31, No. 4, pp. 892–899, Jul. 1995.
15. M. S. Ballal, H. M. Suryawanshi, and M. K. Mishra, “Detection of incipient faults in induction motors using FIS, ANN and ANFIS techniques,” Journal of Power Electronics, Vol. 8, No. 2, pp. 181–191, Mar. 2008.
16. J. B. Valencia, M. P. Sanchez, J. M. Roman, R. P. Panadero, and A. S. Bano, “Study of performance of several techniques of fault diagnosis for induction motors in steady-state with svm learning algorithms,” in 2nd International Conference on Artificial Intelligence,Modelling and Simulation (AIMS), pp. 3–8, Nov. 2014.
17. R. R. Schoen and T. G. Habetler, “Effects of time-varying loads on rotor fault detection in induction machines,” IEEE Trans. Ind. Appl., Vol. 31, No. 4, pp. 900–906, Jul. 1995.
18. J. Faiz, M. Keravand, M. Ghasemi-Bijan, S. M. A. Cruz, and M. Bandar-Abadi, “Impacts of rotor inter-turn short circuit fault upon performance of wound rotor induction machines,” Electric Power Systems Research, Vol. 135, pp. 48–58, Jun. 2016.
19. R. Roshanfekr and A. Jalilian, “Analysis of rotor and stator winding inter-turn faults in WRIM using simulated mec model and experimental results,” Electric PowerSystems Research, Vol. 119, pp. 418–424, Feb. 2015.
20. A. Sapena-Bano, J. Burriel-Valencia, M. Pineda-Sanchez, R. Puche-Panadero, and M. Riera- Guasp, “The harmonic order tracking analysis method for the fault diagnosis in induction motors under time-varying conditions,” IEEE Trans. Energy Convers., Vol. 32, No. 1, pp. 244–256, Mar. 2017.
21. H. Henao, C. Martis, and G. A. Capolino, “An equivalent internal circuit of the induction machine for advanced spectral analysis,” IEEE Trans. Ind. Appl., Vol. 40, No. 3, pp. 726–734, May/Jun. 2004.
22. H. Henao, H. Razik, and G. A. Capolino, “Analytical approach of the stator current frequency harmonics computation for detection of induction machine rotor faults,” IEEE Trans. Ind. Appl., Vol. 41, No. 3, pp. 801– 807, May/Jun. 2005.
23. A. Yazidi, H. Henao, G. A. Capolino, and F. Betin, “Rotor inter-turn short circuit fault detection in wound rotor induction machines,” in XIX International Conference on Electrical Machines (ICEM), pp. 1–6, Sep. 2010.
24. S. M. A. Cruz and A. J. M. Cardoso, “Rotor cage fault diagnosis in three phase induction motors by extended park’s vector approach,” Electric Machines & Power Systems, Vol. 28, No. 4, pp. 289–299, Nov. 2000.
25. J. Burriel-Valencia, A. Sapena-Bao, M. Pineda-Sanchez, and J. Martinez-Roman, “Multilayer park’s vector approach, a method for fault detection on induction motors,” in IEEE International Conference on Industrial Technology (ICIT), pp. 775–780, Mar. 2015.
26. S. M. A. Cruz, “Diagnosis of the multiple induction motor faults using extended Park’s vector approach,” 982 Journal of Power Electronics, Vol. 17, No. 4, July 2017 International Journal of Condition Monitoring and Diagnostic Engineering Management, Vol. 4, pp. 19–25,2001.
27. J. Burriel-Valencia, R. Puche-Panadero, J. Martinez- Roman, A. Sapena-Bano, and M. Pineda- Sanchez, “Short-frequency fourier transform for fault diagnosis of induction machines working in transient regime,” IEEE Trans. Instrum. Meas., Vol. 66, No. 3, pp. 432–440, Mar. 2017.
28. W. Zhou, B. Lu, T. G. Habetler, and R. G. Harley, “Incipient bearing fault detection via motor stator current noise cancellation using wiener filter,” IEEE Trans. Ind. Appl., Vol. 45, No. 4, pp. 1309–1317, Jul./Aug. 2009.
29. R. R. Schoen, T. G. Habetler, F. Kamran, and R. G. Bartfield, “Motor bearing damage detection using stator current monitoring,” IEEE Trans. Ind. Appl., Vol. 31, No. 6, pp. 1274–1279, Nov./Dec. 1995.
30. B. Yazici and G. B. Kliman, “An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current,” IEEE Trans. Ind. Appl., Vol. 35, No. 2, pp. 442–452, Mar./Apr. 1999.
31. J. M. Erdman, R. J. Kerkman, D. W. Schlegel, and G. L. Skibinski, “Effect of PWM inverters on ac motor bearing currents and shaft voltages,” IEEE Trans. Ind. Appl., Vol. 32, No. 2, pp. 250– 259, Mar./Apr. 1996.
32. J. R. Stack, T. G. Habetler, and R. G. Harley, “Fault classification and fault signature production for rolling element bearings in electric machines,” IEEE Trans. Ind. Appl., Vol. 40, No. 3, pp. 735–739, May/Jun. 2004.
33. T.G. Habetler, J.R. Stack, and R.G. Harley, “Bearing fault detection via autoregressive stator current modeling,” IEEE Trans. Ind. Appl., Vol. 40, No. 3, pp. 740–747, May/Jun. 2004.
34. F. Dalvand, A. Kalantar, and M.S. Safizadeh, “A novel bearing condition monitoring method in induction motors based on instantaneous frequency of motor voltage,” IEEE Trans. Ind. Electron., Vol. 63, No. 1, pp. 364–376, Jan. 2016.
35. R.M. Tallam, T.G. Habetler, and R.G. Harley, “Transient model for induction machines with stator winding turn faults,” IEEE Trans. Ind. Appl., Vol. 38, No. 3, pp. 632– 637, May/Jun. 2002. 36. P. Krause, Analysis of electric machinery, McGraw-Hill series in electrical and computer engineering, McGraw-Hill, 1986.
37. Y. Gritli, L. Zarri, C. Rossi, F. Filippetti, G.A. Capolino, and D. Casadei, “Advanced diagnosis of electrical faults in wound-rotor induction machines,” IEEE Trans. Ind. Electron., Vol. 60, No. 9, pp. 4012–4024, Sep. 2013.
38. M. Ballal, Z.J. Khan, H.M. Suryawanshi, and R.L. Sonolikar, “Adaptive neural fuzzy inference system for the detection of inter-turn insulation and bearing wear faults in induction motor,” IEEE Trans. Ind. Electron., Vol. 54, No. 1, pp. 250–258, Feb. 2007.


Regular Issue Open Access Article
Volume 12
Issue 1
Received May 13, 2021
Accepted May 20, 2021
Published May 20, 2023