Full Content is available to subscribers

Subscribe/Learn More  >

A Prognostic Modeling Approach for Predicting Recurring Maintenance for Shipboard Propulsion Systems

[+] Author Affiliations
Gregory J. Kacprzynski, Michael Gumina, Michael J. Roemer

Impact Technologies, LLC, Rochester, NY

Daniel E. Caguiat, Thomas R. Galie, Jack J. McGroarty

Naval Surface Warfare Center, Carderock Division, Philadelphia, PA

Paper No. 2001-GT-0218, pp. V001T02A003; 7 pages
  • ASME Turbo Expo 2001: Power for Land, Sea, and Air
  • Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery
  • New Orleans, Louisiana, USA, June 4–7, 2001
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-7850-7
  • Copyright © 2001 by ASME


Accurate prognostic models and associated algorithms that are capable of predicting future component failure rates or performance degradation rates for shipboard propulsion systems are critical for optimizing the timing of recurring maintenance actions. As part of the Naval maintenance philosophy on Condition Based Maintenance (CBM), prognostic algorithms are being developed for gas turbine applications that utilize state-of-the-art probabilistic modeling and analysis technologies. Naval Surface Warfare Center, Carderock Division (NSWCCD) Code 9334 has continued interest in investigating methods for implementing CBM algorithms to modify gas turbine preventative maintenance in such areas as internal crank wash, fuel nozzles and lube oil filter replacement. This paper will discuss a prognostic modeling approach developed for the LM2500 and Allison 501-K17 gas turbines based on the combination of probabilistic analysis and fouling test results obtained from NSWCCD in Philadelphia. In this application, the prognostic module is used to assess and predict compressor performance degradation rates due to salt deposit ingestion. From this information, the optimum time for on-line waterwashing or crank washing from a cost/benefit standpoint is determined.

Copyright © 2001 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In