i-manager Publications

An FFT Based Approach to Detect the Bearing and Rotor Fault in a Single Phase Induction Motor on Load

Jayanta Kumar Sahni*, Kuldeep Sahay**, Satyendra Singh***

* Senior Research Assistant, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, U.P., India.

** Professor and Head, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, U.P., India.

*** Associate Professor, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, U.P., India.

Periodicity:April - June'2017
DOI : https://doi.org/10.26634/jdp.5.2.13736

Abstract

This paper demonstrates the experimental setup to acquire the stator current of single phase induction motor; and applies FFT technique to detect the fault in motor. The faults created in motor are bearing and rotor fault. Using current sensor, the signal under healthy state and faulty state is acquired from the motor, then using MATLAB signal processing toolbox the spectrum of the corresponding signal is obtained. The spectrum of the signal under fault is compared with the spectrum of the healthy signal and it is expected that the fault will be detected. The spectrum of the motor under healthy state is called the signature of the machine. This is unique for each machine. The central idea is that the signature of any machine under healthy and fault condition will be different. And, this forms the basis of condition monitoring and fault detection.

Keywords

Motor Current Signature Analysis (MCSA), Fast Fourier Transforms (FFT), Spectrum, Current Sensor, Analog to Digital Converter (ADC).

How to Cite this Article?

Sahni, J, K., Sahay, K., & Singh, S. (2017). An FFT Based Approach to Detect the Bearing and Rotor Fault in a Single Phase Induction Motor on Load. i-manager’s Journal on Digital Signal Processing, 5(2), 15-21. https://doi.org/10.26634/jdp.5.2.13736

References

[1]. Bhavsar, R. C., & Patel, R. A. (2013). Various Techniques for Condition Monitoring of Three Phase Induction Motor- A Review. International Journal of Engineering Inventions, 3(4), 22-26.

[2]. Chaturvedi, D. K., Iqbal, M. S., & Singh, M. P. (2015, March). Condition monitoring of induction motor. In Recent Developments in Control, Automation and Power Engineering (RDCAPE), 2015 International Conference on (pp. 135-140). IEEE.

[3]. Harlisca, C., & Szabó, L. (2012). Bearing faults condition monitoring- A literature survey. Journal of Computer Science and Control Systems, 5(2), 19-22.

[4]. Jung, J. H., Lee, J. J., & Kwon, B. H. (2006). Online diagnosis of induction motors using MCSA. IEEE Transactions on Industrial Electronics, 53(6), 1842-1852.

[5]. Mais, J. (2002). Spectrum analysis: The key features of analyzing spectra. SKF Reliability Systems, USA.

[6]. 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.

[7]. Mohanty, A. R., (n.d.). Machinery fault diagnosis and signal processing. NPTEL Video Lecture Series, IIT Kharagpur.

[8]. Sahay, K., & Pathak, S. (2006). Basic Concepts of Electrical Engineering (pp. 245-253). New Delhi: New Age International (P) Ltd.

[9]. 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.

[10]. Thomson, W. T., & Gilmore, R. J. (2003, September). Motor current signature analysis to detect faults in induction motor drives– fundamentals, data interpretation, and industrial case histories. In Proceedings of the Thirty-second Turbomachinery Symposium (pp. 145-156).

[11]. Trutt, F. C., Sottile, J., & Kohler, J. L. (2001, September). On-line condition monitoring of induction motors. In Industry Applications Conference, 2001. Thirty-Sixth IAS Annual Meeting Conference Record of the 2001 IEEE (Vol. 2, pp. 1369-1375). IEEE.

[12]. Vicente, P., Rodriguez, J., Negrea, M., & Arkkio, A. (2005, September). A general scheme for induction motor condition monitoring. In Diagnostics for Electric Machines, Power Electronics and Drives, 2005. SDEMPED 2005. 5^th IEEE International Symposium on (pp. 1-6). IEEE.

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.