Applications of Diagnostic Algorithms for Maintenance Optimization of Marine Gas Turbines

摘要

As part of the Naval gas turbine CBM effort, diagnostic and prognostic algorithms that utilize state-of-the-art probabilistic modeling and analysis technologies are being developed and implemented onboard Navy ships. The algorithms under development and testing will enhance gas turbine preventative maintenance in such areas as compressor on-line/crank wash and fuel nozzle replacement. In one application, the prognostic module assesses and predicts compressor performance degradation due to salt ingestion. From this information, the optimum time for on-line water washing or crank washing can be determined from a cost/enefit standpoint. A second application diagnoses the severity of fuel nozzle fouling in real-time during startup. This paper discusses the diagnostic and prognostic modeling approaches to these maintenance issues and their implementation for an Allison 501-K34 gas turbine engine onboard a DDG 51 class guided missile destroyer.