The Air Force current operations continue to undergo significant changes compelled by decreasing fiscal appropriations, aging aircraft, and personnel drawdown. The Air Force must effectively improve current maintenance operations in part to deal with these challenges. This study will explore the area of the A-10 aircraft fleet's TF34-100 high-pass turbo-fan engine sensor data to seek its deterioration modelling and prognostics capability. In futurity this will allow for achievement of greater confidence in predicting the compressor stall which leads to engine performance deterioration and a costly repair in maintenance. By utilizing an innovative method to forecast the probability of compressor stall, according to individual engine sensor data which has recently become available, it will be possible to achieve significant benefits in both maintenance planning and mission scheduling (which will greatly reduce the associated costs of maintenance servicing).
Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data
2015
100 pages
Report
No indication
English
Aeronautics , Business & Economics , Statistical Analysis , Aircraft maintenance , Jet aircraft , Linear regression analysis , Preventive maintenance , Turbofan engines , Aging(materials) , Air force operations , Air force personnel , Compressors , Confidence level , Cost analysis , Forecasting , Jet engines , Mathematical prediction , Performance(engineering) , Probability , Real time , Scheduling , Sensor fusion , Systems analysis , Theses , Turbines , Engine compressor stall , Predict , Arima(autoregressive integrated moving average) , A-10 aircraft , Engine sensor data
Design Considerations of the TF34-GE-2 High Bypass Turbofan Engine
SAE Technical Papers | 1969
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