Naval Surface Warfare Center

About: Naval Surface Warfare Center is a facility organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Sonar & Radar. The organization has 2855 authors who have published 3697 publications receiving 83518 citations. The organization is also known as: NSWC.

A Two-Stage Filter for State Estimation in the Presence of Dynamical Stochastic Bias

Abstract: This paper provides the optimal solution of a two-stage estimation problem of state estimation in the presence of a dynamical stochastic bias driven by a white or colored process noise. It is shown that under an algebraic constraint on the statistics of the bias process, the optimal estimate of the system state can be obtained as a linear combination of the outputs of the "bias-free" and bias filters. Because the algebraic constraint can be too restrictive in practice, the results of this paper indirectly prove that all practical two-stage filters are suboptimal.

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

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 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 determinedCopyright © 2001 by ASME