Research Article

Spectral Ratio Method for Fault Detection in Rotating Machines

Volume: 6 Number: 2 April 30, 2018
  • Jelena Dıkun
  • Lione Urmonıene
  • Daiva Stanelyte
EN

Spectral Ratio Method for Fault Detection in Rotating Machines

Abstract

This study presents the ratio, which is defined between two vibration signals in the spectral domain, to be used in extracting the fault signatures from the signals. These two signals are considered as two different cases of the electric motor of 5 HP in terms of the faulty and healthy motor cases and hence, the comparison between two spectral variations is used as a method to show the fault characteristic. In this manner, the bearing damage of the electric motor of 5 HP are given within the range of 0-4 kHz and its J-curve is presented as an indication of the motor aging.

Keywords

References

  1. [1] Şeker S., Ayaz E., A Study on Condition Monitoring for Induction Motors Under the Accelerated Aging Processes, IEEE Power Engineering Review, V.22, N.7, pp.35-37, July2002. [2] Seker, S; Ayaz, E Feature extraction related to bearing damage in electric motors by wavelet analysis Journal of Franklin Institute-Engineering and Mathematics, 340 (2), 2003, pp.125-134. [3] Ozturk A.; Seker S. “On the Frequency Resolution of Improved Empirical Mode Decomposition Method” International Review of Electrical Engineering-IREE, Vol. 5, No. 4, pp. 1798-1805, Part b, 2010. [4] Seker, S; Ayaz, E; Turkcan, E Elman's recurrent neural network applications to condition monitoring in nuclear power plant and rotating machinery Engineering Application of Artificial Intelligence, 16 (7-8): pp.647- 656 Oct-Dec 2003 [5] Senguler Tayfun; Karatoprak Erinc; Seker Serhat “A New MLP Approach for the Detection of the Incipient Bearing Damage”, Advances in Electrical and Computer Engineering, Vol.10, No. 3, pp. 34-39, DOI: 10.4316/AECE.2010.03006, 2010. [6] D. Sonmez, S. Seker, M. Gokasan, “Entropy-based fault detection approach for motor vibration signals under accelerated aging process” Journal of Vibroengineering Paper # 851, Vol.14, No.3, September 2012. [7] D. Bayram, S. Şeker, “ Redundancy Based Predictive Fault Detection on Electric Motors by Stationary Wavelet Transform”, IEEE, Transaction on Industrial Applications, vol. 53, pp.2997-3004, 2017. [8] A.H. Bonnet and G.C. Soukup, "Cause and Analysis of Stator and Rotor Failures in Three Phase Squirrel-Cage Induction Motors", IEEE Transactions on Industry Applications, Vol.28, No.4, pp. 921-937, August 1992. [9] K.R. Cho, J.H. Lang, and S.D. Umas, "Detection of Broken Rotor Bars in Induction Motors Using State and Parameter Estimation", IEEE Transaction on Industry Applications, Vol.28, No.3, pp. 702-709, May/June 1992. [10] S.W. Bowers, K.R. Piety, and R.J. Colsher, "Evaluation of the Field Application of Motor Current Analysis", Proceedings of the Meeting of the Vibration Institute, 1993. [11] R. Schoen, T.G. Habetler, F. Kamran, and R.G. Bartheld, "Motor Bearing Damage Detection Using Stator Current Monitoring", 1994 IEEE Industrial Application Meeting, Vol.1, pp.110- 116, 1994. [12] M.J. Costello, “Shaft Voltages and Rotating Machinery,” IEEE Transaction on Industry Applications, Vol. 29, No. 2, pp. 419-425, 1993. [13] S.V. Bowers and K.R. Piety, "Proactive Motor Monitoring Through Temperature Shaft Current and Magnetic Flux Measurements", CSI 1993 Users Conference, September 20-24, 1993, pp.2-3. [14] J.R. Nicholas, "Predictive Condition Monitoring of Electric Motors", P/PM Technology, pp. 28-32, August 1993. [15] G.A. Bisbee, "Why Do Motor Shaft and Bearing Fail", TAPPI Journal, Vol. 77, No. 9, pp. 251-252, September 1994.

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Jelena Dıkun This is me

Lione Urmonıene This is me

Daiva Stanelyte This is me

Publication Date

April 30, 2018

Submission Date

August 25, 2017

Acceptance Date

October 16, 2017

Published in Issue

Year 2018 Volume: 6 Number: 2

APA
Dıkun, J., Urmonıene, L., & Stanelyte, D. (2018). Spectral Ratio Method for Fault Detection in Rotating Machines. Balkan Journal of Electrical and Computer Engineering, 6(2), 129-131. https://doi.org/10.17694/bajece.419642
AMA
1.Dıkun J, Urmonıene L, Stanelyte D. Spectral Ratio Method for Fault Detection in Rotating Machines. Balkan Journal of Electrical and Computer Engineering. 2018;6(2):129-131. doi:10.17694/bajece.419642
Chicago
Dıkun, Jelena, Lione Urmonıene, and Daiva Stanelyte. 2018. “Spectral Ratio Method for Fault Detection in Rotating Machines”. Balkan Journal of Electrical and Computer Engineering 6 (2): 129-31. https://doi.org/10.17694/bajece.419642.
EndNote
Dıkun J, Urmonıene L, Stanelyte D (April 1, 2018) Spectral Ratio Method for Fault Detection in Rotating Machines. Balkan Journal of Electrical and Computer Engineering 6 2 129–131.
IEEE
[1]J. Dıkun, L. Urmonıene, and D. Stanelyte, “Spectral Ratio Method for Fault Detection in Rotating Machines”, Balkan Journal of Electrical and Computer Engineering, vol. 6, no. 2, pp. 129–131, Apr. 2018, doi: 10.17694/bajece.419642.
ISNAD
Dıkun, Jelena - Urmonıene, Lione - Stanelyte, Daiva. “Spectral Ratio Method for Fault Detection in Rotating Machines”. Balkan Journal of Electrical and Computer Engineering 6/2 (April 1, 2018): 129-131. https://doi.org/10.17694/bajece.419642.
JAMA
1.Dıkun J, Urmonıene L, Stanelyte D. Spectral Ratio Method for Fault Detection in Rotating Machines. Balkan Journal of Electrical and Computer Engineering. 2018;6:129–131.
MLA
Dıkun, Jelena, et al. “Spectral Ratio Method for Fault Detection in Rotating Machines”. Balkan Journal of Electrical and Computer Engineering, vol. 6, no. 2, Apr. 2018, pp. 129-31, doi:10.17694/bajece.419642.
Vancouver
1.Jelena Dıkun, Lione Urmonıene, Daiva Stanelyte. Spectral Ratio Method for Fault Detection in Rotating Machines. Balkan Journal of Electrical and Computer Engineering. 2018 Apr. 1;6(2):129-31. doi:10.17694/bajece.419642

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