Detection and Analysis of Rotor Bearing Fault in a Three Phase Induction Motor using MCSA and ANSYS® Maxwell 2D

K.C.Sindhu Thampatty*, Vishak Nathan**, Aravind Rajiv***
*Department of Electrical and Electronics Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India.
** Sioux Logena B.V, Eindhoven, Netherlands.
*** Building Services Industry, Dubai, United Arab Emirates.
Periodicity:July - September'2019
DOI : https://doi.org/10.26634/jee.13.1.16009

Abstract

Being an integral part of any engineering system, electrical machines are used in all industries. Among all these machines, very common type of machine is induction motors. Motor faults can lead to untimely shutdown of machines and consequently lead to loss of productivity. This can be avoided by the proper detection of fault in the incipient stage itself which requires a detailed analysis of the fault and clearly understand its effect on the motor. This paper presents a method to analyses the frequently occurring rotor bearing fault on an induction motor. The fault analysis is conducted using two parameters: Stator current and voltage by Motor Current Signature Analysis and the motor flux distribution using ANSYS® Maxwell 2D.

Keywords

Induction Motors; Rotor Bearing Fault; Motor Current Signature Analysis (MCSA); ANSYS® Maxwell 2D.

How to Cite this Article?

Thampatty, K., C., S., Nathan, V., & Rajiv, A. (2019). Detection and Analysis of Rotor Bearing Fault in a Three Phase Induction Motor using MCSA and ANSYS ® Maxwell 2D.i-manager’s Journal on Electrical Engineering, 13(1), 19-29. https://doi.org/10.26634/jee.13.1.16009

References

[1]. Benbouzid, M. E. H. (2000). A review of induction motors signature analysis as a medium for faults detection. IEEE Transactions on Industrial Electronics, 47(5), 984-993.
[2]. Bhattacharyya, S., Sen, D., Adhvaryyu, S., & Mukherjee, C. (2015). Induction motor fault diagnosis by motor current signature analysis and neural network techniques. Journal of Advanced Computing and Communication Technologies, 3(1), 12-18.
[3]. Chaturvedi, D. K., Iqbal, M. S., & Singh, M. P. (2013, October). Health monitoring techniques of induction motor: an overview. In 4th International Conference on Emerging Trends in Engineering and Technology (IETET- 2013) of ACEEE (pp. 469-477).
[4]. Hardik, R., Sinha, M., & Vijayaraj. (2013), Effect on Induction Motor Performance with Broken Rotor Bars using Finite Element Method. International Journal of Engineering Science and Innovative Technology (IJESIT), 2(2), 250-255.
[5]. IEEE. (1997). IEEE Recommended Practice for Design of Reliable Industrial and Commercial Power Systems. (IEEE Std.493-1997) [IEEE Gold Book]
[6]. Mehala, N. (2010). Condition Monitoring and Fault Diagnosis of Induction Motor using Motor Current Signature Analysis (Doctoral Dissertation), National Institute of Technology, Kurushetra, India.
[7]. Mehala, N., & Dahiya, R. (2007). Motor current signature analysis and its applications in induction motor fault diagnosis. International Journal of Systems Applications, Engineering & Development, 2(1), 29-35.
[8]. Saied, B., & Ali, A. J. (2013). Fault prediction of deep bar cage rotor induction motor based on FEM. Progress In Electromagnetics Research, 53, 291-314. https://doi.org/ 10.2528/PIERB13061904
[9]. Sakhalkar, N. P., & Korde, P. (2017, August). Fault detection in induction motors based on motor current signature analysis and accelerometer. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) (pp. 363- 367). IEEE. https://doi.org/10.1109/ICECDS.2017.8390117
[10]. Siddiqui, K. M., Sahay, K., & Giri, V. K. (2014). Health monitoring and fault diagnosis in induction motor-a review. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(1), 6549- 6565.
[11]. Singh, S., Kumar, A., & Kumar, N. (2014). Motor current signature analysis for bearing fault detection in mechanical systems. Procedia Materials Science, 6, 171- 177. https://doi.org/10.1016/j.mspro.2014.07.021
[12]. Singhal, A., & Khandekar, M. A. (2013). Bearing fault detection in induction motor using motor current signature analysis. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2(7), 3258-3264.
[13]. Thomson, W. T., & Gilmore, R. J. (2003). Motor current signature analysis to detect faults in induction motor drives- Fundamentals, Data Interpretation, and Industrial Case Histories. In Proceedings of the 32nd Turbomachinery Symposium. Texas A & M University, Turbomachinery Laboratories.
[14]. Vinothraj, C., Kumar, N., P., & Isha, T., B. (2018). Bearing fault analysis in induction motor drives using Finite Element Method. International Journal of Engineering and Technology (UAE). 7(3.6), 30-34. https:/doi.org/10.14419/ ijet.v7i3.6.14928
[15]. Zagirnyak, M., Romashihina, Z., & Kalinov, A. (2013). Diagnostic of broken rotor bars in induction motor on the basis of its magnetic field analysis. Acta Technica Jaurinensis, 6(1), 115-125.

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