F-16 turbofan engine monitoring system
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Squadron Commander at
31st Air Force Base Poznań-Krzesiny.
Publication date: 2019-05-01
Combustion Engines 2019,177(2), 23-35
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ABSTRACT
The multirole F-16 is the most advanced aircraft in the Polish Air Forces. It has been equipped with the very modern, sophisticated and advanced turbofan engine F100-PW-229. Due to the fact, that there is only one engine, its reliability, durability, efficiency and performance are the crucial factors for the safety reasons. In the article author researched maintenance system of the F100 turbofan engines, to describe Engine Monitoring System features. Engine Monitoring System (EMS) is the key element in the engine prognostic and health monitoring. The EMS provides engine fault indicators to the pilots and technicians and with the engine performance trending affects the F-16 flight safety risk and enhanced engine maintenance management concept. The main goal of this article was to provide information on the F-16 Engine Monitoring System and its impact on the aircraft airworthiness and F-16 fleet readiness resulting from the engine reliability. It is also an introduction to the F-16 Engine Health Management concept.
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1.
Lockheed Martin STM 16-329PL (Poland Block 52) F100-PW-229 Power Plant.
2.
F100 Pratt&Whitney F100 WUC, October 2018.
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Technical Manual T.O.00-20-1 Aerospace Equipment Maintenance Inspections, Documentation, Policies and procedures.
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F100 Pratt&Whitney F100 WUC, October 2018.
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Technical Manual General System Organizational Maintenance Power Plant Model F100-PW-229 Technical Order PL1F-16CJ-2-70GS-00-21.
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Engine Management and Tracking System EMATS Maintenix.
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Technical Manual Fault Isolation Organizational Maintenance Power Plant Model F100-PW-229 Technical Order PL1F-16CJ-2-70FI-00-21.
CITATIONS (2):
1.
Aircraft Engine Remaining Useful Life Prediction using neural networks and real-life engine operational data
Slawomir Szrama, Tomasz Lodygowski
Advances in Engineering Software
2.
Turbofan engine health status prediction with neural network pattern recognition and automated feature engineering
Sławomir Szrama
Aircraft Engineering and Aerospace Technology