SYSTEM FOR FORECASTING AIRCRAFT ENGINE DETERIORATION USING RECURRENT NEURAL NETWORKS

A method for forecasting aircraft engine deterioration includes creating a first fused data set (130) corresponding to a first actual aircraft engine (20). The first fused data set (130) includes at least one as manufactured parameter of the actual aircraft engine, expected operating parameters of t...

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Bibliographische Detailangaben
Hauptverfasser:	NAGARAJA, Sharath B, GRECO, Matthew R
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	AIR INTAKES FOR JET-PROPULSION PLANTS BLASTING CALCULATING COMBUSTION ENGINES COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING CONTROLLING FUEL SUPPLY IN AIR-BREATHING JET-PROPULSION PLANTS COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES FUNCTIONAL ELEMENTS OF SUCH SYSTEMS GAS-TURBINE PLANTS HEATING HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL LIGHTING MECHANICAL ENGINEERING MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR WEAPONS
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Beschreibung
Zusammenfassung:	A method for forecasting aircraft engine deterioration includes creating a first fused data set (130) corresponding to a first actual aircraft engine (20). The first fused data set (130) includes at least one as manufactured parameter of the actual aircraft engine, expected operating parameters of the first actual aircraft engine, and actual operating parameters of the actual aircraft engine. The actual operating parameters of the actual aircraft engine include internal aircraft sensor data (110), and external flight tracking data (114). The method further includes predicting an expected engine deterioration of the first actual engine based on the expected operating parameters and the actual operating parameters of the first actual aircraft engine by applying the first fused data set to a forecasting model. The forecasting model is a recurrent neural network based algorithm, and the recurrent neural network based algorithm is trained via a plurality of second fused data sets corresponding to actual aircraft engines.