Improved Fault Detection by Appropriate Control of Signal Bandwidth of the TSA

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Eric Bechhoefer Xinghui Zhang

Abstract

Vibration analysis is perhaps the longest serving technology used in condition monitoring. It is usually assumed that higher sampling rates improve fault detection due to the increased bandwidth of the acquisition. That said, increased bandwidth may decrease the signal to noise, impairing fault detection. Alternatively, if the fault features’ bandwidth is greater than the system bandwidth, the fault cannot be observed. One tool of vibration analysis is the Time Synchronous Average (TSA) analysis. Statistics of the TSA itself can be used as a fault feature, or statistics based on analysis performed on the TSA (energy operator, residual analysis, amplitude/frequency modulation analysis) are used as fault features. Additionally, the computation of the TSA requires a tachometer signal for zero crossing, which has its own bandwidth effect on the TSA analysis. This paper discusses bandwidth control techniques to improve fault detection using the TSA. The techniques are validated using real world pinion data. These techniques have other advantages for embedded condition monitoring systems.

How to Cite

Bechhoefer , E., & Zhang, X. . (2015). Improved Fault Detection by Appropriate Control of Signal Bandwidth of the TSA. Annual Conference of the PHM Society, 7(1). https://doi.org/10.36001/phmconf.2015.v7i1.2760
Abstract 4 | PDF Downloads 3

##plugins.themes.bootstrap3.article.details##

Keywords

vibration analysis, TSA, signal to noise, bandwidth

References
Bechhoefer, E., &Fang, A., (2012) Algorithms for Embedded PHM, IEEE Conference on Prognostics and Health Management, June 18-21, Denver, Co.doi:10.1109/ICPHM.2012.6299539

Decker, H.J., & Zakrajsek, J.J., Comparison of interpolation methods as applied to time synchronous averaging. NASA/TM-1999-209086, 1999.

Lebold, M., McClintic, K., Campbell, R., Byington, C., & Maynard, K.,(2000) Review of vibration analysis methods for gearbox diagnostics and prognostics, Proceedings of the 54th
Meeting of the Society for Machinery Failure Prevention Technology, May 1-4, Virginia Beach, V A.http://personal.psu.edu/staff/k/p/kpm128/pubs/Feat ureTutorialBody18.PDF

McFadden, P., (1986). Detecting fatigue cracks in gears by amplitude and phase demodulation of the meshing vibration. American Society of Mechanical Engineering Transaction, Journal of Vibration, Acoustics, Stress and Design, 108, 165-170.

McFadden, P., (1987) A revised model for the extraction of periodic waveforms by time domain averaging. Mechanical Systems and Signal Processing, vol. 1(1), pp. 83-95

McInerny, S.A., Hardman, B., Keller, J.A. & Bednarczyk, R., (2003) Detection of a cracked-planet Carrier, Tenth International Congress on Sound and Vibration. July 2003, Stockholm, Sweden.

Press, W., Teukolsky, S., Vetterling, W., and Flannery, B., (1992) Numerical Recipes in C, Cambridge University Press

Samuel, P.D., & Pines, D.J.,(2005) A review of vibration- based techniques for helicopter transmission diagnostics. Journal of Sound and Vibration, vol. 282, pp. 475-508.
Section
Technical Papers