Accession Number:

ADP013488

Title:

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

Descriptive Note:

Conference paper

Corporate Author:

IMPACT TECHNOLOGIES LLC ROCHESTER NY

Report Date:

2001-04-05

Pagination or Media Count:

11.0

Abstract:

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. NSWCCD-SSES 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 LM25OO and Allison 501-Kl7 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 costbenefit standpoint is determined.

Subject Categories:

  • Marine Engineering

Distribution Statement:

APPROVED FOR PUBLIC RELEASE