Vibration Based Condition Assessment Of Rollingelement Bearings With Localized Defects

Abstract:- Rolling element bearings are one of the major machinery components used in industries like power plants, chemical plants and automotive industries that require precise and efficient performance. Condition monitoring of these bearings is important to avoid failures. Several vibration monitoring techniques are available. Vibration analysis gets much advantage in factories as a predictive maintenance technique. In this study, vibration response of the rolling bearings to the defects on outer race, inner race and the rolling elements is obtained and analyzed. It shows that every defect excites the system at its characteristic frequency. The location of the faults is indicated by the FFT spectrum. Additionally, kurtosis, one of the statistical parameters is evaluated for the above cases of the bearing. The results reveal that vibration based monitoring method is successful in detecting the faults in the bearing.

REFERENCES

[1]. Tandon N., Choudhury A., �A Review of Vibration and Acoustic Measurement Methods for the Detection of Defects in Rolling Element Bearings�, Tribology International, Vol. 32, pp.469�480, 1999.

[2]. Tandon, N., Choudhury A., �An Analytical Model for the Prediction of the Vibration Response of Rolling Element Bearings Due to a Localized Defect�, Journal of Sound and Vibration, Vol. 205(3), pp. 275-292, 1997.

[3]. Tan, A.C.C., Katie L. McNickle and Daniel L. Timms. �A practice approach to learning vibration condition monitoring�. World Transactions on Engineering and Technology Education, 2(2): pp. 217-220., 2003.

[4]. McFadden P. D. And Smith J. D., �Model for the vibration produced by a Single point defect in a rolling element bearing.� Journal of Sound and Vibration, 96(1), pp. 69-82, 1984.

[5]. A.R. Bhende, Awari.,SP Untawale., �Assessment of Bearing Fault Detection Using Vibration Signal Analysis� VSRD-TNTJ, Vol. 2 (5), 2011, pp. 249-261.

[6]. Y.G. Lei, Z.J. He, Y.Y. Zi, Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs, Mechanical Systems and Signal Processing 21., pp. 2280�2294., 2007.

[7]. Sawalhi, N., Randall, R.B., �Vibration Response of Spalled Rolling Element Bearings: Observations, Simulations and Signal Processing Techniques to Track the Spall Size�, Mechanical Systems and Signal Processing, Vol. 25, , pp. 846�870, 2011.

[8]. Yabin Dong, MingfuLiao, X.Zhang , F.Wang., �Faults diagnosis of rolling element bearings based on modified morphological method�, Mechanical Systems and Signal Processing,Vol 25, pp.1276�1286, 2011.

[9]. Bo Taoa, Limin Zhub, Han Dinga,b, Y. Xiong �An alternative time-domain index for condition monitoring of rolling element bearings�A comparison study,� Reliability Engineering and System Safety vol.92, pp.660�670, 2007.

[10]. Orhan Sadettin, Akturk Nizami, Celik Veli. �Vibration monitoring for defect diagnosis of rolling element bearings as a predictive maintenance tool: Comprehensive case studies�. NDT & E International 39:,pp.293-298., 2006.

[11]. Heng, R.B .W., and Nor M. J. M. �Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition�. Applied Acoustics, 53(1-3), pp. 211-226, 1998.

[12]. Estocq P., Bolaers F., Dron J.P. �Method of De-Noising By Spectral Subtraction Applied to the Detection of Rolling Bearing Defects�. Journal of Vibration and Control, 12(2): pp 197-211, 2006.

[13]. Tandon, N. �A comparison of some Vibration parameters for the condition monitoring of rolling element bearings�. Measurement, 12: 1994, pp. 285-289.

[14]. Su Y. T. and Lin, S. J. �On initial fault detection of a tapered roller bearing: frequency domain analysis,� Journal of Sound and Vibration, 155(1):, pp. 75-84., 1992.

[15]. Zeki Kiral, Hira Karaguille. �Simulation and analysis of vibration signals generated by rolling element bearing with defects�. Tribology International, 36: pp. 667- 678, 2003.