Document Type : Original Article


School of Mechanical Engineering, Iran University of Science and Technology, Iran


The lack of lubricant in bearing surfaces could be considered as the main cause of wear and faults in bearing surfaces. To avoid unexpected failures, special emphasis on adequate evaluation of lubrication mode (lubricated/dry) on the bearing surfaces is demanded. To that end, the proper use of reliable techniques and tools, including sensory information from acoustic emission (AE) signals is among popular methods when real-time condition monitoring evolves. The current work intends to evaluate the sensitivity of AE parameters to different levels of process parameters on the basis of statistical analysis. In this context, rotational speed and radial load were used as the main experimental parameters. Following that, adequacy of a new AE signal parameter for real-time condition monitoring of rolling element bearing is presented. Experimental and statistical results confirmed the great capability of AE signals to differentiate between two types of bearing modes, in particular, dry and lubricated. Signal processing and statistical analysis conducted in this study exhibited that several time series AE parameters, in particular, Std, Max, Mean, and Variance are sensitive to the variation radial load and rotational speed. It was observed that radial load has insignificant effects on computed values of AE parameters from both bearing modes. The statistical analysis revealed that rotational speed (A) has a significant effect on all computed AE parameters from the dry bearing.


Main Subjects

[1]     Tonphong, K., Bearing Condition Monitoring Using Acoustic Emission and Vibration, Ph.D. Thesis, Brunel University, UK, 2002.
[2]     Nisbet, T. S., and Mullet, G., Rolling Bearings in Service: Interpretation of Types of Damage: Hutchinson, 1978.
[3]     Li, Y., Billington, S., Zhang, C., Kurfess., Danyluk, T., and Liang, S., Adaptive Prognostics for Rolling Element Bearing Condition, Mechanical Systems and Signal ProcessingVol. 13, No. 1, 1999, pp. 103-113.
[4]     Tandon, T., Nakra, B., Comparison of Vibration and Acoustic Measurement Techniques for the Condition Monitoring of Rolling Element Bearings, Tribology InternationalVol. 25, No. 3, 1992, pp. 205-212.
[5]     James, C., Li, S., Acoustic Emission Analysis for Bearing Condition Monitoring, WearVol. 185, No.1, 1995, pp. 67-74.
[6]     Yoshioka, T., Fujiwara, T., A New Acoustic Emission Source Locating System for the Study of Rolling Contact Fatigue, WearVol. 81, No. 1, 1982, pp. 183-186.
[7]     McFadden, p., Smith, J., Acoustic Emission Transducers for the Vibration Monitoring of Bearings at Low Speeds, Proceedings of the Institution of Mechanical Engineers, Journal of Mechanical Engineering Science, Vol. 198C, No. 2, 1984, pp. 127-130.
[8]     Tandon, N., Choudhury, A., A Review of Vibration and Acoustic Measurement Methods for the Detection of Defects in Rolling Element Bearings, Tribology InternationalVol. 32, No. 8, 1999, pp. 469-480.
[9]     Yoshioka, T., Fujiwara, T., Application of Acoustic Emission Technique to Detection of Rolling Bearing Failure, American Society of Mechanical EngineersVol. 14, 1984, pp. 55-76.
[10]  Tandon, N., Nakara, B., Defect Detection in Rolling Element Bearings by Acoustic Emission Method, Acoustic Emission, Vol. 9, No. 3, 1990, pp. 25-28.
[11]  Matthews, J. R., Acoustic Emission, Gordon and Breach, New York, 1983.
[12]  Bansal, V., Gupta, B., Parkash, A., and Eshwar, V., Quality Inspection of Rolling Element Bearing Using Acoustic Emission Technique, Acoustic Emission, Vol. 9, No. 2, 1990, pp. 142-146.
[13]  Jamaludin, N., Mba, D., and Bannister, R., Condition Monitoring of Slow-Speed Rolling Element Bearings Using Stress Waves, Proceedings of the Institution of Mechanical Engineers, Journal of Process Mechanical Engineering, Vol. 215E, No. 4, 2001, pp. 245-271.
[14]  Mba, D., Bannister, R., and Findlay, G., Condition Monitoring of Low-Speed Rotating Machinery Using Stress Waves Part 1, Proceedings of the Institution of Mechanical Engineers, Journal of Process Mechanical Engineering, Vol. 213E, No. 3, 1999, pp. 153-170.
[15]  Miettinen, J., Andersson, P., Acoustic Emission of Rolling Bearings Lubricated with Contaminated Grease, Tribology International, Vol. 33, No. 11, 2000, pp. 777-787.
[16]  Heng, R., Nor, M., Statistical Analysis of Sound and Vibration Signals for Monitoring Rolling Element Bearing Condition, Applied Acoustics, Vol. 53, No. 1, 1998, pp. 211-226.
[17]  Kim, E. Y., Tan, A. C. C., Yang, B. S., and Kosse, V., Experimental Study on Condition Monitoring of Low Speed Bearings: Time Domain Analysis, in 5th Australasian Congress on Applied Mechanics, ACAM 2007, Brisbane, Australia, 2007, pp. 108-113.
[18]  Al Ghamd, A. M., Mba, D., A Comparative Experimental Study on the Use of Acoustic Emission and Vibration Analysis for Bearing Defect Identification and Estimation of Defect size, Mechanical Systems and Signal ProcessingVol. 20, No. 7, 2006, pp. 1537-1571.
[19]  Yoon, D. J. I. N., Kwon, O. H. Y., Chung, M. I. H. W. A., and Kim, K. W., Early Detection of Damages in Journal Bearings by Acoustic Emission Monitoring, Journal of Acoustic Emission, Vol. 13, No. 1-2, 1995, pp. 1-10.
[20]  Niknam, S. A., Au, Y. H., and Songmene, V., Proposing a New Acoustic Emission Parameter for Bearing Condition Monitoring in Rotating Machines, Transactions of the Canadian Society for Mechanical Engineering, Vol. 37, No. 4, 2013, pp. 11051114.
[21]  Kim, E. Y., Tan, A. C. C., Yang, B. S., and Kosse, V., Experimental Study on Condition Monitoring of Low Speed Bearings: Time Domain Analysis, 2007, pp. 108-113.
[22]  Sikorska, J., Mba, D., Challenges and Obstacles in the Application of Acoustic Emission to Process Machinery, Proceedings of the Institution of Mechanical Engineers, Journal of Process Mechanical Engineering, Vol. 222E, No. 1, 2008, pp. 1-19.
[23]  Mba,D, Acoustic Emissions and monitoring bearing health, Tribology Transactions, Vol. 46, pp. 447-451, 2003.
[24]  Liang, S., Dornfeld, D., Tool Wear Detection Using Time Series Analysis of Acoustic Emission, J. Eng. Ind. (Trans. ASME), Vol. 111, 1989, pp. 199-205.
[25]  Lee, D., Hwang, I., Valente, C., Oliveira, J., and Dornfeld, D., Precision Manufacturing Process Monitoring with Acoustic Emission, International Journal of Machine Tools and Manufacture, Vol. 46, No. 2, 2006, pp. 176-188.
[26]  Lee, S. H., Lee, D., In-process Monitoring of Drilling Burr Formation Using Acoustic Emission and a Wavelet-Based Artificial Neural Network, International Journal of Production Research, Vol. 46, No. 17, 2008, pp. 4871-4888.
[27]  Marinescu, I., Axinte, D. A., A Critical Analysis of Effectiveness of Acoustic Emission Signals to Detect Tool and Workpiece Malfunctions in Milling Operations, International Journal of Machine Tools and ManufactureVol. 48, No. 10, 2008, pp. 1148-1160.
[28]  Niknam, S. A., Kamguem, R., Songmene, V., and Kenne, J. P., Machining Factors Influence on Acoustic Emission Parameters, International Journal of Advances in Machining and Forming Operations, Vol. 2, No. 2, 2010, pp. 91-114.
[29]  Mian, A., Driver, N., and Mativenga, P., Chip Formation in Microscale Milling and Correlation with Acoustic Emission Signal, The International Journal of Advanced Manufacturing TechnologyVol. 56, No. 1, 2011, pp. 63-78.
[30]  Niknam, S. A., Tiabi, A., Kamguem, R., Zaghbani, I., and Songmene, V., Milling Burr Size Estimation Using Acoustic Emission and Cutting Forces, Proceedings of the ASME 2011 International Mechanical Engineering Congress & Exposition IMECE 2011, Denver, Col, USA, 2011.
[31]  Xiao Qi, C., Hao, Z., and Wildermuth, D., In-process Tool Monitoring through Acoustic Emission Sensing, Automated Material Processing Group, Automation Technology Division, Vol. 1, 2001.
[32]  Niknam, S. A., Bearing Condition Monitoring Using Acoustic Emission, M.Sc Thesis, Brunel University, UK, 2008.
[33]  Phadke, M. S., Quality Engineering Using Robust Design, Prentice Hall Englewood Cliffs, NJ, 1989.