IJBTT

An Over view on Vibration Analysis Techniques for the Diagnosis of Rolling Element Bearing Faults

	International Journal of Engineering Trends and Technology (IJETT)
	© 2013 by IJETT Journal
	Volume-4 Issue-5
	Year of Publication : 2013
	Authors : Shyam Patidar , Pradeep Kumar Soni

Citation 

Shyam Patidar , Pradeep Kumar Soni. "An Over view on Vibration Analysis Techniques for the Diagnosis of Rolling Element Bearing Faults". International Journal of Engineering Trends and Technology (IJETT). V4(5):1804-1809 May 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.

Abstract

Rolling element bearings comes under the critical category in many rotating machineries, mainly in chemical industry, av iation, nuclear power stations etc. Vibration monitoring and analysis is useful tool in the field of predictive maintenance. Health of rolling element bearings can be easily identified using vibration monitoring because vibration signature reveals important information about the fault development within them . Numbers of vibration analysis techniques are being used to diagnosis of rolling element bearings faults. This paper attempt s to summarize the recent research and developments in rolling bearing vibrati on analysis techniques . Bearing defects and bearing characteristic frequen cies (BCF) are also discussed.

References

[1] P. F. Al brecht , J. C. Appiarius , R. M. McCoy , J.C. Owen and D.K. Sharma , ‘Assessment of the reliability of motors in utility applications – updated’ IEEE Transactions on Energy Conversion, Vol. 1, No. 1, pp. 39 - 46, 1986.
[2] P.Y. Kim and I.R.G. Lowe , ‘A review of rolling e lement bearing health monitoring. In: Proceedings of Machinery Vibration Monitoring and Analysis Meeting’ Vibration Institute, Houston, TX, pp.145 – 54, 19 – 21 April, 1983.
[3] P.D. McFadden and J.D. Smith , ‘Vibration monitoring of rolling element bearings by the high frequency resonance technique - a review’ Tribology International, Vol. 17, No. 1, pp. 3 - 10, 1984.
[4] N. Tandon and B.C. Nakra , ‘Vibration and acoustic monitoring techniques for the detection of defects in rolling element bearings - a review’ The Shock a nd Vibration Digest, Vol. 24, No. 3, pp. 3 - 11, 1992.
[5] N. Tandon and A. Choudhury , ‘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.
[6] C.S. Sun nersjo, ‘Rolling bearing vibrations - geometrical imperfections and wear’ Journal of Sound and Vibration’ Vol. 98, No. 4, pp. 455 - 74, 1985.
[7] N. Tandon and A. Choudhury, ‘A theoretical model to predict vibration response of rolling bearings to distributed de fects under radial load’ Journal of Vibrations and Acoustics, Vol. 120, pp. 214 - 20, 1998.
[8] T.E. Tallian and O.G. Gustafsson, ‘Progress in rolling bearing vibration research and control’ ASLE Trans., Vol. 8, No. 3, pp. 195 - 207, 1965.
[9] S. Braun and B. Danter, ‘Analysis of Roller/Ball Bearing Vibration’ ASME - Journal of Mechanical Design , Vol. 101, pp 118 - 125, 1979.
[10] Y. Li and C. Zhang, ‘Dynamic Prognostic Prediction of Defect Propagation on Rolling Element Bearing’ Journal of Vibration and Acoustics , Trans of ASM E , vol. 85, no. 1, pp: 214 - 220. July 2004.
[11] N. Tandon and A. Choudhury, ‘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, No. 3, pp. 275 - 92, 199 7.
[12] H. Prasad, ‘The effect of cage and roller slip on the measured defect frequency response of rolling element bearings’ ASLE Trans., Vol. 30, No. 3, pp. 360 - 7, 1987.
[13] N. Tandon, ‘A comparison of some vibration parameters for the condition monitoring of rol ling element bearings’ Measurement , Vol. 12, pp.285 - 89, 1994 .
[14] E. Downham, ‘Vibration monitoring and wear prediction’ proceeding of 2 nd International conference on vibration in rotary machinery, IMechE , pp. 29 - 33, 1980 .
[15] T. Ingarashi, B. Noda, and E. Matsush ima, ‘A study on the prediction of abnormalities in rolling bearing’ JSLE , Vol. 1, pp. 71 - 76, 1980 .
[16] T.R. Kurfess, S. Billington and S.Y. Liang, ‘Advanced Diagnostic and Prognostic Techniques for Rolling Element Bearings’ Condition Monitoring and Control fo r Intelligent Manufacturing, pp. 137 - 165, 2006.
[17] I.E. Alguindigue, A. L. Buczak and Robert E. Uhrig, ‘Monitoring and Diagnosis of Rolling Element Bearings Using Artificial Neural Networks’ IEEE Transactions on Industrial Electronics, Vol. 40, No. 2, pp. 209 - 217, April 1993.
[18] C.Q. Li and C.J. Pickering, ‘Robustness and sensitivity of non - dimensional amplitude parameters for diagnosis of fatigue spalling’ Condition Monitoring and Diagnostic Technology, Vol. 2, No. 3, pp. 81 - 84, January 1992.
[19] Tuncay Karacay and N izami Akturk, ‘Experimental diagnostics of ball bearings using statistical and spectral methods’ Tribology International, Vol. 42, pp. 836 – 43, 2009.
[20] Steve Goldman , ‘Vibration Spectrum Analysis’ 2 nd edition, Industrial Press Inc., New York, 1999.
[21] James I. Tylor, “The vibration analysis handbook” 1 st edition, Vibration Consultants, Tampa, Florida, 1994.
[22] N.T.V. Merwe and A.J. Hoffman ‘A modified cepstrum analysis applied to vibrational signals’ in: Proceedings of 14 th International Conference on Digital Signa l Processing (DSP2002), vol. 2, pp. 873 – 76, Santorini, Greece, 2002.
[23] P.D. McFadden and J.D. Smith ‘Vibration monitoring of rolling element bearings by high frequency resonance technique — a review’ Tribology International, Vol. 17, pp. 3 – 10, 1984.
[24] H. Prashad , M. Ghosh and S. Biswas, ‘Diagnostic monitoring of rolling - element bearings by high - frequency resonance technique’ ASLE Transactions, Vol. 28, No. 4, pp 43 9 - 448, 1985 .
[25] Y.T. Su and S.J. Lin , ‘On initial fault detection of a tapered roller bearing: Frequenc y domain analysis’ Journal of Sound and Vibration, Vol. 155, No. 1, pp 75 - 84, 1992 .
[26] M.S. Lai and Z. Reif, “Prediction of ball bearing failures” Proceeding of 1 st International Machinery Monitoring and Diagnostics Conference , pp. 122 - 26, 1989 .
[27] G. White , ‘A mplitude demodulation - a new tool for predictive maintenance’ Journal of Sound and vibration, pp 14 - 19, Sep. 1991.
[28] S.W. McMahon , ‘Condition monitoring of bearing using ESP’ Condition Monitoring and Diagnostic Technology, Vol. 2, No. 1, pp 21 - 25, July 1991 .
[29] Y.A. Azovtsev, A.V. Barkov and I.A. Yudin , ‘Automatic diagnostics and condition prediction of rolling element bearing using enveloping methods’ Vibration Institute 18 th Annual Meeting, June 20 - 23, 1994.
[30] D. Kadushin, ‘Roller element bearing fault analysis using envelope detection during an experimental case study’ Proceeding of 3 rd International Machinery Monitoring and Diagnostics Conference, COMADEM 91 , pp. 132 - 41, 1991 .
[31] R. Milne, J. Aylett, S. McMahon and T. Scott, ‘Portable bearing diagnostics using en veloping and expert system’ Proceeding of 3 rd International Machinery Monitoring and Diagnostics Conference, COMADEM 91 , pp. 75 - 79, 1991 .
[32] K.F. Martin and P. Thrope, ‘Normalized spectra in monitoring of rolling bearing elements’ Wear, Vol. 159, pp. 153 - 60, 1992 .
[33] R.B. Randall, J. Antoni and S. Chobsaard, ‘The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cy clostationary machine signals ’ Mechanical Systems and Signal Processing , Vol. 15, No. 5, pp. 945 - 962, 2001 .
[34] M.A. Minnicino and H.J. Sommer, ‘Detecting and quantifying friction nonlinearity using the Hilbert transform’ in: Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological System III, vol. 5394, Bellingham, 2004, pp. 419 – 427.
[35] D. Ho and R.B. Randall, ‘Optimization of bearing diagnostic techniques using simulated and actual bearing fault signals’ Mechanical Systems and Signal Processing , Vol. 14, No. 5, pp. 763 - 88, 2000 .
[36] G. Mouroutsos Spyridon and Chatzisavvas Ioann is, ‘Study and construction of an apparatus that automatically monitors vibration and wears in radial ball bearings which are loaded in radial direction’ 2009 International Conference on Signal Processing Systems, IEEE Computer Society, pp. 292 - 96, 2009
[37] T . Kaewkongka, Y. Au, R. Rakowski and B. Jones, “A comparative study of short time Fourier transform and continuous wavelet transform f or bearing condition monitoring ” International Journal of COMADEM - 6, pp. 41 - 48, 2003.
[38] Dong Wang, Peter W. Tse and Kwok Leu ng Tsui , ‘An enhanced Kurtogram method for fault diagnosis of rolling element bearings’ Mechanical Systems and Signal Processing Vol. 35, pp. 176 – 99, 2013.
[39] G.Y. Luo, D. Osypiw and M. Irle ‘On - line vibration analysis with fast continuous wavelet algorithm f or condition monitoring of bearing’ Journal of Vibration and Control, Vol. 9, pp. 931 – 47, 2003.
[40] R. Rubini and U. Meneghetti , ‘Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings’ Mechanical Syst ems and Signal Processing , Vol. 15, No. 2, pp. 287 - 302, 2001 .
[41] G. Dalpiaz and A. Rivola , ‘Condition monitoring and diagnostics in automatic machines: Comparison of vibration analysis techniques’ Mechanical Systems and Signal Processing, Vol. 11, pp. 53 – 73, 1997.
[42] K. Mori, N. Kasashima , T. Yoshioka and Y. Ueno , ‘Prediction of spalling on a ball bearing by applying discrete wavelet transform to vibration signals’ Wear, Vol. 195, pp.162 – 68, 1996.
[43] S. Prabhakar , A.R. Mohanty and A.S. Sekhar, ‘Application of discre te wavelet transform for detection of ball bearing race fault’ Tribology International , Vol. 35, pp. 793 - 800, 2002 .
[44] C. Wang and R.X. Gao, ‘Wavelet transform with spectral post - processing for enhanced feature extraction’ IEEE Transactions on Instrumentation and Measurement, Vol. 52 pp. 1296 – 1301, 2003.
[45] Q. Sun and Y. Tang, ‘Singularity analysis using continuous wavelet transform for bearing fault diagnosis’ Mechanical Systems and Signal Processing , Vol. 16, No. 6, pp. 1025 - 1041, 2002 .
[46] Lin Jing and Liangsheng Qu , ‘Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis’ Journal of Sound and Vibration, Vol. 234, No. 1, pp. 135 – 48, 2000.
[47] G.G. Yen and K.C. Lin, ‘Wavelet Packet Feature Extraction for Vibration Monitoring’ IEEE Transactions on Industrial Electronics , Vol. 47, No. 3, pp. 650 – 667, 2000.
[48] N.G. Nikolaou and I.A. Antoniadis, “Rolling element bearing fault diagnosis using wavelet packets” NDT&E International , Vol. 35, pp.197 - 205, 2002 .
[49] H.A. Toliyat, K. Abbaszadeh, M.M. Rahimian and L.E. Olson, ‘Rail defect diagnosis using wavelet packet decomposition’ IEEE Transactions on Industry Applications Vol. 39, pp. 1454 – 1461, 2003.
[50] Yuan Yunlong and Zhang Zhenxiang , ‘Fault Diagnosis of Rolling Rearing Based on the Wavelet Analysi s’ 2 nd International Asia Conference on Informatics in Control, Automation and Robotics, IEEE , pp. 257 - 260, 2010.
[51] D.C. Baillie and J. Mathew , ‘A comparison of autoregressive modeling techniques for fault diagnosis of roller element bearings’ Mechanical Sys tems and Signal Processing , Vol. 10, No. 1, pp. 1 - 17, 1996 .
[52] T.I. Liu, J.H. Singonahalli and N.R. Iyer, ‘ Detection of Roller bearing defects using expert system and fuzzy logic’ Mechanical Systems and Signal Processing , Vol. 10, No. 5, pp. 595 - 614, 1996 .
[53] L. B. Jack, A.K. Nandi and A.C. McCormick, ‘Diagnosis of rolling element bearing faults using radial basis function networks’ Applied Signal Processing , Vol. 6, pp. 25 - 32, 1999 .
[54] Y. Fan and C.J. Li, ‘Diagnostic rule extraction from trained feedforward neural n etworks’ Mechanical Systems and Signal Processing, Vol. 16, pp. 1073 – 1081, 2002.
[55] M. Subrahmanyam and C. Sujatha, ‘Using neural networks for the diagnosis of localized defects in ball bearings’ Tribology International , Vol. 30, No. 10, pp. 739 - 752, 1997 .
[56] B. Samanta and K.R. Al - Balushi, ‘Artificial neural network based fault diagnostics of rolling element bearings using time domain features’ Mechanical Systems and Signal Processing , Vol. 17, No. 2, pp. 317 - 328, 2003 .
[57] Antoniadis and G. Glossiotis, ‘Cyclostatio nary Analysis of Rolling - element Bearing Vibration Signals’ Journal of Sound and Vibration Vol. 285 No. 5 , pp . 829 - 845, 2001.
[58] Yang Y., Dejie Y., and Junsheng C., ‘A roller bearing fault diagnosis method based on EMD energy entropy and ANN’ Journal of Sound and Vibration , Vol. 294, pp. 269 - 277, 2006 .
[59] Muruganatham B., Sanjith M.A., Krishna Kumar B. and Satya Murty S.A.V., ‘Inner Race Bearing Fault detection using Singular Spectrum Analysis’ ICCCCT, IEEE , pp. 573 - 579, 2010.
[60] P.K. Kankar, S.C. Sharma and S.P. Harsha, ‘Fault Diagnosis of Ball Bearings using Machine Learning Methods’ Expert Systems with Applications, Vol. 38, pp. 1876 – 1886, 2011.
[61] Meng Li , ‘ An intelligent fault diagnosis system of rolling bearing’ International Conference on Transportation, Mechan ical, and Electrical Engineering (TMEE), Changchun, China, pp. 544 - 547, December 16 - 18, 2011.

Keywords
Rolling Element Bearing, Vibration, Bearing Fault, Vibration Analysis, Fault Diagnosis