Trend Monitoring of A Turbofan Engine for Long Endurance UAV Using Fuzzy Logic
Changduk Kong ¡¤ Jayoung Ki ¡¤ Seonghwan Oh ¡¤ Jihyun Kim
International Journal of Aeronautical and Space Sicences, vol. 9, no. 2, pp.64-70, 2008
Abstract : The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc.
Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude
Keyword : Trend Monitoring, Fuzzy Logic, Turbofan Engine, UAV |