Bearing Fault Feature Extraction by Recurrence Quantification Analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32813
Bearing Fault Feature Extraction by Recurrence Quantification Analysis

Authors: V. G. Rajesh, M. V. Rajesh

Abstract:

In rotating machinery one of the critical components that is prone to premature failure is the rolling bearing. Consequently, early warning of an imminent bearing failure is much critical to the safety and reliability of any high speed rotating machines. This study is concerned with the application of Recurrence Quantification Analysis (RQA) in fault detection of rolling element bearings in rotating machinery. Based on the results from this study it is reported that the RQA variable, percent determinism, is sensitive to the type of fault investigated and therefore can provide useful information on bearing damage in rolling element bearings.

Keywords: Bearing fault detection, machine vibrations, nonlinear time series analysis, recurrence quantification analysis.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1082919

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1802

References:


[1] F.K. Choy, J. Zhou, M.J. Braun, and L.Wang, "Vibration monitoring and damage quantification of faulty ball bearings," Transactions of the ASME, Journal of Tribology, vol. 127, pp. 776-783, Oct 2005.
[2] Antoni and R.B Randall, "Differential diagnosis of gear and bearing faults," Transactions of the ASME, Journal of Vibration and Acoustics, , vol. 124(2), pp. 165-171, 2002.
[3] T. Xinmin, D. Baoxiang, and X. Yong, "Bearings fault diagnosis based on HMM and fractal dimensions spectrum," in Proc. of the 2007 IEEE Int. Conf. on Mechatronics and Automation, China, 2007, pp. 1671- 1676.
[4] K.R. Al-Balushi and B. Samanta, "Gear fault diagnosis using energybased features of acoustics emission signals" in Proc. of the I. Mech. E. Part 1, Journal of Systems and Control Engineering, vol. 216(3), 2002, pp. 249-263.
[5] J.P. Eckmann, S.O. Kamphorst, and D. Ruelle, "Recurrence plots of dynamical systems," Europhysics Letters, vol. 5, pp. 973-977, 1987
[6] J.P. Zbilut and C.L. Webber Jr., "Embeddings and delays as derived from quantification of recurrence plots," Physics Letters A, vol. 171 (3- 4), pp. 199-203, 1992.
[7] C.L. Webber Jr. and J.P. Zbilut, "Dynamical assessment of physiological systems and states using recurrence plot strategies," Journal of Applied Physiology, vol. 76-2, pp. 965-973, 1994.
[8] N. Marwan, N. Wessel, U. Meyerfeldt, A. Schirdewan, and J. Kurths, "Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data," Physical Review E, vol. 66(2), 026702, 2002.
[9] F. Takens, "Detecting strange attractors in turbulence," Dynamical Systems and Turbulence, Warwick, Lecture Notes in Mathematics 898, Springer-Verlag, pp. 366-81, 1981.
[10] H. D. I. Abarbanel, Analysis of the observed chaotic data, Springer- Verlag, Telos, 1996
[11] M.B. Kennel, R. Brown, and H.D.I. Abarbanel, "Determining embedding Dimension from phase-space reconstruction using a geometrical construction", Physical Review A, vol. 25, pp. 3403-3411, 1992.
[12] A.M. Fraser and H.L. Swinney, "Independent Coordinates for strange attractors from mutual information," Physical Review A, vol. 33, pp. 1134-1140, 1986.
[13] N. Marwan, "Encounters with Neighbors - Current developments of concepts based on recurrence plots and their applications", Ph.D. Thesis, University of Potsdam, ISBN 3-00-012347-4, 2003.
[14] C.L. Webber Jr, and J.P. Zbilut, "Recurrence quantification analysis of nonlinear dynamical systems," Tutorials in contemporary nonlinear methods for the behavioral sciences, (Chapter 2, pp. 26-94), M.A. Riley, G. Van Orden, eds. Retrieved December 1, 2004.