A Model-based Approach to Detect an Under-Lubricated Condition in a Ball Bearing
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Bearings with an insufficient amount of lubricant can lead to early field failures, especially in applications which fail due to lubricant degradation, such as cooling fans used for thermal management of electronics. A reduced amount of lubricant can accelerate the wear process in the bearing, since there is not enough lubricant film thickness to support the operating load on the bearing. Qualification of bearings in cooling fans is carried out by time-truncated tests, where cooling fans have to operate without failure for a pre-determined period of time. Under-lubricated bearings can survive without failure in these tests leading to the usage of these bearings in the field resulting in field returns and warranty claims.
A non-linear dynamic model of a ball bearing is developed to simulate the transfer of load from the inner race to the outer race of the bearing as well as the acceleration signal as a function of time. An under-lubricated bearing condition is simulated in this model by changing the load transmitted to the outer race due to the reduced amount of lubricant. The simulated acceleration signal of the under-lubricated bearing condition is compared with that from the normal bearing to develop a fault-characteristic feature. The changes observed in the fault-characteristic feature from the simulation is validated by comparing with that obtained from experiments conducted on bearings with varying amounts of grease, ranging from none to the nominal amount specified by the manufacturer. The vibration level of these bearings was monitored at various operating speeds during the experiment. The changes observed in the fault-characteristic feature from the experiment due to a reduction of the lubricant in the bearing were similar to that observed in the simulations. This study resulted in the development of an experimental methodology and a fault-characteristic feature which can be used as a method for rapid acceptance testing of bearings. The dynamic model developed in this study can be used to determine the fault-characteristic feature for any bearing design.
How to Cite
##plugins.themes.bootstrap3.article.details##
bearing fault detection, vibration-based diagnostics, lubrication, dynamic model
Eschmann, P., Hasbargen, L., Weigand, K., & Brändlein, J. (1985). Ball and roller bearings: Theory, design, and application. Munich, Germany: R. Oldenbourg.
Kim, S., Vallarino, C., & Claassen, A. (1996). Review of fan life evaluation procedures. International Journal of Reliability, Quality and Safety Engineering (IJRQSE), 03(01), 75–96. doi:10.1142/S0218539396000077
Machado, M., Moreira, P., Flores, P., & Lankarani, H. M. (2012). Compliant contact force models in multibody dynamics: Evolution of the Hertz contact theory. Mechanism and Machine Theory, 53, 99–121. doi:10.1016/j.mechmachtheory.2012.02.010
Morinigo-Sotelo, D., Duque-Perez, O., & Perez-Alonso, M. (2010). Assessment of the lubrication condition of a bearing using spectral analysis of the stator current. In 2010 International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM) (pp. 1160–1165). doi:10.1109/SPEEDAM.2010. 5544958
Nandi, S., Toliyat, H. A., & Li, X. (2005). Condition monitoring and fault diagnosis of electrical motors-a review. Energy Conversion, IEEE Transactions on, 20(4), 719 – 729. doi:10.1109/TEC.2005.847955
Ribrant, J., & Bertling, L. (2007). Survey of failures in wind power systems with focus on Swedish wind power plants during 1997-2005. In Power Engineering Society General Meeting, 2007. IEEE (pp. 1–8). doi:10.1109/PES.2007.386112
Sawalhi, N., & Randall, R. B. (2008). Simulating gear and bearing interactions in the presence of faults: Part I. The combined gear bearing dynamic model and the simulation of localised bearing faults. Mechanical Systems and Signal Processing, 22(8), 1924–1951. doi:10.1016/j.ymssp.2007.12.001
Stachowiak, G., & Batchelor, A. W. (2014). Engineering Tribology (4th ed.). Oxford, U.K.: Butterworth-Heinemann.
Tandon, N., & Choudhury, A. (1999). A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International, 32(8), 469–480. doi:10.1016/S0301-679X(99)00077-8
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.