Daniel E. Caguiat

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

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

Applied neural network for navy marine gas turbine stall algorithm development

In June 2005, Naval Surface Warfare Center (NSWC) Gas Turbine Emerging Technologies conducted testing on a general electric LM2500 gas turbine engine. This engine is the main propulsor for DDG-51 and CG-47 class United States Navy surface ships. The purpose of this testing was to induce compressor stall in order to evaluate existing algorithms for stall prediction and gather data for further algorithm development. In addition to existing sensor data, dynamic pressure sensors, with data rates ranging from 20-1000 KHz, were installed in various compressor stages for additional capability. Utilizing the data collected, in conjunction with a MATLAB-based neural network approach, NSWC has developed algorithms to detect and trend stall margin and related quantities that can eventually be used in an early stall warning system onboard ship. Algorithms can be incorporated into the recently installed full authority digital control, allowing real-time stall detection and prevention. This paper discusses the feasibility of employing a neural network approach to detect and output a compressor stall margin value and associated risk of compressor stall for U.S. Navy LM2500 gas turbine engines

Inlet Air Salt Concentration Detection on U.S. Navy Ship Service Gas Turbine Generator Sets

The Naval Surface Warfare Center, Carderock Division (NSWCCD) Gas Turbine Emerging Technologies Code 9334 has been working, in conjunction with Vibro-Meter Incorporated, to evaluate and further develop the Vibro-Meter Flame Contaminant Detector (FCD). This device has been used on various commercial gas turbine platforms to quantify the level of sodium entrained in fuel. The FCD consists of a spectrometer device, fiber optic cabling, and a lens assembly, which is mounted in an open combustor port. The combustion flame is continuously monitored for sodium wavelength intensity during gas turbine operation. The FCD was initially of interest to NSWCCD for use in fuel filtration system health monitoring. However, based on known Ship Service Gas Turbine Generator (SSGTG) hot section corrosion issues, it was believed that the FCD would also serve as useful tool for quantifying inlet air salt concentration. Testing was performed at the Philadelphia Land Based Engineering Site in 2003. It was determined that the FCD was able to detect salt concentrations as low as 0.003 parts per million. Initial indications are that airborne salt can be differentiated from fuel entrained salt based on continuous vs. intermittent sodium levels. Continuing efforts are centered on optimizing the existing FCD algorithm to properly differentiate between and quantify inlet air and fuel-entrained salt concentration.Copyright

Gas Turbine Performance and Energy Conservation on DDG-51 Class U.S. Navy Ships

On DDG-51 Class US Navy ships, maximum power and propulsion loads do not require all four main gas turbine engines nor all three electric generator engines to be operating simultaneously. U.S. Navy fleet guidance does not mandate a particular plant configuration at any given time. Therefore, the configuration being used on a given ship to support a particular mission is partially at the discretion of the ship’s crew. This paper focuses on an effort to utilize real-time data from the ship’s power and propulsion plants and auxiliary equipment to assess fuel efficiency and configuration options available, and suggest operating profiles conducive to energy savings. Current Phase I project deliverables, preliminary results, and potential way-forward topics are addressed.

Gas Turbine Online Waterwash for DDG-51 Class U.S. Navy Ships

Currently, the U.S. Navy DDG-51 class ships employ a system of piping, tanks, and nozzles for washing the four Gas Turbine Main (GTM) engines and three Ship Service Gas Turbine Generator (SSGTG) engines. The wash system employed, referred to as the crankwash system, allows the user to wash the compressor section of a gas turbine only when the turbine in question is not operating. On a DDG-51 class ship, it is possible to utilize the existing crankwash piping, tank, and overall architecture to supply water to an online water wash system. An online water wash system allows the compressor section to be cleaned while the gas turbine is in operation. This is intended to reduce the periodicity of crankwashing and associated starter cycling costs. Online water wash is also intended to maintain compressor cleanliness in the interval between crankwashes. NAVSEA Philadelphia researched appropriate online water wash system designs, methods for collecting data to address fuel savings and engine performance issues, and installation methods. GTM and SSGTG Online Water Wash Systems were then installed on USS PREBLE (DDG-88) in late 2008. USS PREBLE subsequently deployed for a period of six months beginning January 2009. During the deployment, data was collected as the systems were operated. This paper will discuss the system design, provide data analysis results, and discuss lessons learned.Copyright

Analysis of Stall Precursors and Determination of Optimum Signal Processing Methods for an LM-2500 Gas Turbine

This paper presents an analysis of data taken from several stall initiation events on a GE LM-2500 gas turbine engine. Specifically, the time series of three separate pressure signals located at compressor stages 3, 6, and 15 were analyzed utilizing various signal processing methods to determine the most reliable indicator of incipient stall for this engine. The spectral analyses performed showed that rotating precursor waves traveling around the annulus at approximately half of the rotor speed were the best indicators. Non-linear chaotic time series analyses were also used to predict stall, but it was not as reliable an indicator. Several algorithms were used and it was determined that stall wave perturbations can be reliably identified about 900 revolutions prior to the stall. This work indicates that a single pressure signal located at stage 3 on an LM-2500 gas turbine is sufficient to provide advance warning of more than 2 seconds prior to the fully developed stall event.

Gas Turbine Inlet Salt Monitoring for Filtration and Hot Section Prognostics

The Naval Surface Warfare Center, Carderock Division (NSWCCD) Gas Turbine Emerging Technologies Code 934 has been working, in conjunction with Vibro-Meter Incorporated, to evaluate and further develop the Vibro-Meter Flame Contaminant Detector (FCD). This device has been used on various commercial gas turbine platforms to quantify the level of sodium entrained in fuel. The FCD consists of a spectrometer device, fiber optic cabling, and a lens assembly, which is mounted in an open combustor port. The combustion flame is continuously monitored for sodium wavelength intensity during gas turbine operation. The FCD was initially of interest to NSWCCD for use in fuel filtration system health monitoring. However, based on known Ship Service Gas Turbine Generator (SSGTG) hot section corrosion issues, it was believed that the FCD would also serve as useful tool for quantifying inlet air salt concentration. Testing was performed at the Philadelphia Land Based Engineering Site in 2003. It was determined that the FCD was able to detect salt concentrations as low as 0.003 parts per million. Initial indications are that airborne salt can be differentiated from fuel entrained salt based on continuous vs. intermittent sodium levels. Continuing efforts are centered on optimizing the existing FCD algorithm to properly differentiate between and quantify inlet air and fuel-entrained salt concentration.

Development and improvement of compressor performance prognostics for US Navy gas turbine engines

In December 2003, Naval Surface Warfare Center Gas Turbine Emerging Technologies section conducted land-based fouling testing on a Rolls Royce/Allison 501-K17 gas turbine engine. The purpose of this testing was to collect data to improve a previously developed compressor health prognostics algorithm. For the purpose of Phase I of this testing, fouling was accomplished by injecting salt into the gas turbine inlet air stream. Phase II of this testing will consist of fouling the middle and back regions of the compressor. Influence coefficients can then be developed for each of these regions indicating how a given region affects overall performance. Typically, in a marine environment, fouling of the front stages occurs due to ingested salt while fouling in middle and rear regions occurs from a combination of ingested salt and oil seal leakage. In order to monitor engine performance, it was necessary to add several sensors to the existing test cell. In addition, hardware was added to both ingest and monitor the concentration of salt in gas turbine inlet air. Preliminary results from Phase I indicate that front stage compressor fouling causes a clear increase in inlet static pressure. This is due to the mass flow restriction through the compressor. Additional results are currently being summarized and data is being utilized to improve the 501-K17 compressor performance algorithm previously noted

Improvements to Compressor Prognostics Algorithm for US Navy Ship Service Gas Turbine Generator Sets

The Naval Surface Warfare Center Gas Turbine Emerging Technologies section conducted land-based testing on a gas turbine generator set in December 2003. The purpose of this testing, which was conducted on a Rolls Royce/Allison 501-K17 gas turbine, was to collect data that could be used to improve a previously developed computer program for predicting optimal compressor wash time intervals. For the purpose of Phase I of this testing, fouling was accomplished by injecting salt into the gas turbine inlet air stream. Phase II of this testing will consist of fouling the middle and back regions of the compressor. Influence coefficients can then be developed for each of these regions indicating how a given region affects overall performance. Typically, in a marine environment, fouling of the front stages occurs due to ingested salt while fouling in middle and rear regions occurs from a combination of ingested salt and oil seal leakage. A number of sensors, including compressor inlet and discharge condition probes, bleed air flow and fuel flow meters, were added in order to monitor engine performance during the testing. In addition, hardware was added to both ingest and monitor the concentration of salt in gas turbine inlet air. For Phase II testing, middle and rear stages of the 14-stage compressor shall be accessed through existing 5th and 10th stage bleed ports. A salt solution will be physically applied to the blades while the compressor is rotated by hand. Results from Phase I indicate that front stage compressor fouling causes a clear increase in inlet static pressure. This is due to the mass flow restriction through the compressor. Additional results are currently being summarized, and data is being utilized to improve the 501-K17 compressor wash prognostics algorithm previously noted.© 2005 ASME

USNS LCPL Roy M. Wheat: Zorya DT-59 Gas Turbine Installation and Integration

In June 1997, the U.S. Navy purchased the Soviet military cargo ship “Vladimir Vaslyaev” for conversion to the USNS LCPL Roy M. Wheat for use in the Maritime Prepositioning Force. This paper documents the efforts of NSWCCD and dB Associates in supporting the installation, startup, and integration of the ship’s controls with the two Zorya DT-59 main propulsion gas turbine engines (GTE’s). The installation documentation developed included a video record of the port and starboard gas turbine installations, as well as information that aided in the development of the Engineering Operational Procedures (EOP). The integration for the DT-59s focused on providing engine speed sensors, an engine vibration monitoring system and engine reversing protection circuits.© 2004 ASME