Gear Health Threshold Setting Based On a Probability of False Alarm

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

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

Published Sep 25, 2011
Eric Bechhoefer David He Paula Dempsey

Abstract

There is no established threshold or limit for gear vibration based condition indicators (CI) that indicates when a gear is in need of maintenance. The best we can do is set CI thresholds statistically, based on some small probability of false alarm. Further, to the best of our knowledge, there is no single CI that is sensitive to every failure mode of a gear. This suggests that any condition based maintenance system for gears will have some form of sensor fusion.Three statistical models were developed to define a gear health indicator (HI) as a function of CI: order statistics (max of n CIs), sum of CIs and normalized energy. Since CIs tend to be correlated, a whitening process was developed to ensure the HI threshold is consistent with a defined probability of false alarm. These models were developed for CIs with Gaussian or Rayleigh (skewed) distributions. Finally, these functions, used to generate HIs, were tested on gear test stand data and their performance evaluated as compared to the end state of the gear (e.g. photos of damage). Results show the HIs performed well detecting pitting damage to gears.

How to Cite

Bechhoefer, E. ., He, D. ., & Dempsey, P. (2011). Gear Health Threshold Setting Based On a Probability of False Alarm. Annual Conference of the PHM Society, 3(1). https://doi.org/10.36001/phmconf.2011.v3i1.2059
Abstract 602 | PDF Downloads 250

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

Keywords

Thresholding, probability of false alarm, function of distribution, gear condition indicator

References
McFadden, P., Smith, J., (1985), A Signal Processing Technique for detecting local defects in a gear from a signal average of the vibration. Proc Instn Mech Engrs Vol 199 No C4

Zakrajsek, J. Townsend, D., Decker, H., (1993). An Analysis of Gear Fault Detection Method as Applied to Pitting Fatigue Failure Damage. NASA Technical Memorandum 105950.

Lewicki, D., Dempsey, P., Heath, G., and Shanthakumaran P. (2010), Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage, Gear Technology, November/December 2010.

Wemhoff, E., Chin, H., Begin, M., (2007), Gearbox Diagnostics Development Using Dynamic Modeling, AHS 63rd Annual Forum, Virginia Beach, 2007

Byington, C., Safa-Bakhsh, R., Watson., M., Kalgren, P., (2003), Metrics Evaluation and Tool Development for Health and Usage Monitoring System Technology, HUMS 2003 Conference, DSTO-GD-0348

Wackerly, D., Mendenhall, W., Scheaffer, R.,(1996), Mathematical Statistics with Applications, Buxbury Press, Belmont, 1996

Fukunaga, K., (1990), Introduction to Statistical Pattern Recognition, Academic Press, London, 1990, page 75.

Bechhoefer, E., Bernhard, A., (2007), A Generalized Process for Optimal Threshold Setting in HUMS, IEEE Aerospace Conference, Big Sky.
group.com/en/certification/renewables/CertificationGuidelines.php

Bechhoefer, E., Bernhard, A., (2006), Use of Non- Gaussian Distribution for Analysis of Shaft Components, IEEE Aerospace Conference, Big Sky.

Dempsey, P., Handschuh, R., Afjeh, A. (2002), Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis, NASA/TM-2002-211814

GL Renewables, (2007), Guidelines for the Certification of Condition Monitoring Systems for Wind Turbines, http://www.glgroup.com/en/certification/renewables/Certification
Guidelines.php

Bechhoefer, E., Bernhard, A., (2006), Use of Non- Gaussian Distribution for Analysis of Shaft Components, IEEE Aerospace Conference, Big Sky.

Dempsey, P., Handschuh, R., Afjeh, A. (2002), Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis, NASA/TM-2002-211814
Section
Technical Research Papers

Most read articles by the same author(s)

1 2 3 > >>