59. Vibration and motor current analysis of induction motors to diagnose mechanical faults

Hakan Çalış

Suleyman Demirel University, Faculty of Technology, Department of Electrical-Electronics Engineering,
Isparta, Turkey

E-mail: hakancalis@sdu.edu.tr

(Received 8 April 2014; received in revised form 25 May 2014; accepted 23 October 2014)

Abstract. Electric motors play an important role in industry, and the induction motors are the most widely used among them. Any motor failure interrupts the process, causes loss of productivity, and may also damages to other machinery. Therefore, to prevent sudden failure of motor (such as on the large or critical motor) it is essential to have an early fault detection mechanism. The work presented in this paper is concerned with the detection of the mechanical faults in three phased induction motors. Motor current signal analysis (MCSA) is used in identification of artificially induced mechanical faults, and it is also supported with vibration signal analysis. The most common mechanical problems; mechanical unbalance, shaft misalignment, and bearing failures are investigated experimentally. The efficacy of MCSA based monitoring for the detection of mechanical faults is demonstrated. Matlab based an automatic peak detection algorithm is also used in this study for determination of changes in signal spectrums.

Keywords: condition monitoring, motor current signal analysis, vibration monitoring, mechanical faults, bearing faults, peak detection.


[1]        Bate A. H. Vibration Diagnostics for Industrial Electric Motor Drives. Bruel & Kjaer Application Note.

[2]        Farag S. F., Bartheld R. G., Habetler T. G. An integrated, on-line, motor protection system. IEEE Industry Applications Society Annual Meeting, 1994, p. 117‑122.

[3]        Schoen R. R., et al. Motor bearing damage detection using stator current monitoring. IEEE Industry Applications Society Annual Meeting, Vol. 1, 1994, p. 110‑116.

[4]        Schoen R. R., et al. An unsupervised, on-line system for induction motor fault detection using stator current monitoring. IEEE Industry Applications Society Annual Meeting, Vol. 1, 1994, p. 103‑109.

[5]        Thomson W. T. On-line current monitoring to detect rotor winding and electromechanical problems in induction motor drives. IEE Colloquium on Condition Monitoring of Electrical Machines (Digest No. 1995/019), p. 8/1‑6.

[6]        Thomson W. T., Rankin D., Dorrell D. G. On line current monitoring to diagnose airgap eccentricity in large three-phase induction motors – industrial case histories verify the predictions. IEEE Transaction on Energy Conversion, Vol. 14, Issue 4, 1999, p. 1372‑1378.

[7]        Shahjamal Khan A. A., et al. Monitoring and detecting health of a single phase induction motor using data acquisition interface (DAI) module with artificial neural network. WSEAS Transactions on Systems and Control, Vol. 9, 2014, p. 229‑237.

[8]        Naseer A., Raghied A. Cost-effective wireless-controlled motor failure prediction for HVAC system in large buildings using demodulated current signature analysis. Life Science Journal, Vol. 11, Issue 10s, 2014, p. 33‑39.

[9]        Bouras A. K., et al. Investigation on the diagnosis of simple and combines mechanical faults in asynchronous motor based electric drives. American Journal of Applied Sciences, Vol. 11, Issue 6, 2014, p. 994‑1004.

[10]     Šiljak H., Subasi A. A novel approach to Hurst analysis of motor vibration data in aging processes. Journal of Vibroengineering, Vol. 16, Issue 5, 2014, p. 2244‑2250.

[11]     Šiljak H., Şeker S. Hurst analysis of induction motor vibrations from aging process. Balkan Journal of Electrical and Computer Engineering, Vol. 2, Issue 1, 2014, p. 16‑19.

[12]     Beuschel M. Detection of Faults in Centrifugal and Positive Displacement Pumps by Digital Signal Analysis of Flow and Pressure Measurements. Final year project, University of Sussex, 1996.

[13]     Gurevich G. Misalignment and vibration. The Shock and Vibration Digest, Vol. 28, Issue 2, 1996, p. 15‑1.

[14]     Sahraoui M., et al. Dynamic eccentricity in squirrel cage induction motors – simulation and analytical study of its spectral signatures on stator currents. Simulation Modelling Practice and Theory, Vol. 16, 2008, p. 1503‑1513.

Cite this article

Çalış Hakan Vibration and motor current analysis of induction motors to diagnose mechanical faults. Journal of Measurements in Engineering, Vol. 2, Issue 4, 2014, p. 190‑198.


Journal of Measurements in Engineering. December 2014, Volume 2, Issue 4
© JVE International Ltd. ISSN Print 2335-2124, ISSN Online 2424-4635, Kaunas, Lithuania