公开(公告)号：US20180268288A1

公开(公告)日：2018-09-20

申请号：US15458340

申请日：2017-03-14

Applicant: General Electric Company

Inventor： John Lawrence Vandike ,  Kenneth Lee Dale

IPC: G06N3/08 ,  F01D21/00 ,  B64D45/00 ,  G07C5/08

CPC classification number: G07C5/0816 ,  F01D21/003 ,  F05D2260/80 ,  F05D2260/81 ,  F05D2270/20 ,  F05D2270/30 ,  F05D2270/709 ,  F05D2270/80 ,  G05B23/024 ,  G06N3/04 ,  G06N3/082 ,  G06N3/084

Abstract: Systems and methods that include and/or leverage a neural network to approximate the steady-state performance of a turbine engine are provided. In one exemplary aspect, the neural network is trained to model a physics-based, steady-state cycle deck. When properly trained, novel input data can be input into the neural network, and as an output of the network, one or more performance indicators indicative of the steady-state performance of the turbine engine can be received. In another aspect, systems and methods for approximating the steady-state performance of a “virtual” or target turbine engine based at least in part on a reference neural network configured to approximate the steady-state performance of a “fielded” or reference turbine engine are provided.