公开(公告)号：US12106235B2

公开(公告)日：2024-10-01

申请号：US16360480

申请日：2019-03-21

Applicant: United Technologies Corporation

Inventor： Sharath B. Nagaraja ,  Mathew R. Greco

IPC: G06Q10/04 ,  B64F5/60 ,  G05B23/02 ,  G06F18/25 ,  G06N3/04 ,  G08G5/00 ,  H04W4/029

CPC classification number: G06Q10/04 ,  B64F5/60 ,  G05B23/0281 ,  G05B23/0283 ,  G06F18/25 ,  G06N3/04 ,  G08G5/0026 ,  G08G5/0039 ,  G08G5/006 ,  H04W4/029

Abstract: A method for forecasting aircraft engine deterioration includes creating a first fused data set corresponding to a first actual aircraft engine. The first fused data set 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, and external flight tracking data. 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.

公开(公告)号：US20200301406A1

公开(公告)日：2020-09-24

申请号：US16360480

申请日：2019-03-21

Applicant: United Technologies Corporation

Inventor： Sharath B. Nagaraja ,  Mathew R. Greco

IPC: G05B23/02 ,  B64F5/60 ,  G06K9/62 ,  G06N3/04 ,  G08G5/00 ,  H04W4/029

Abstract: A method for forecasting aircraft engine deterioration includes creating a first fused data set corresponding to a first actual aircraft engine. The first fused data set 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, and external flight tracking data. 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.