TURBINE DIAGNOSTIC FEATURE SELECTION SYSTEM

TURBINE DIAGNOSTIC FEATURE SELECTION SYSTEM

A turbine diagnostic machine learning system builds one or more turbine engine performance models using one or more parameter or parameter characteristics. A model of turbine engine performance includes ranked parameters or parameter characteristics, the ranking of which is calculated by a model bui...

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Hauptverfasser: AGARWAL, Anurag, GRUBER, Frank, ESCRICHE, Lorenzo, ALLA, Rajesh
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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creator AGARWAL, Anurag
GRUBER, Frank
ESCRICHE, Lorenzo
ALLA, Rajesh
description A turbine diagnostic machine learning system builds one or more turbine engine performance models using one or more parameter or parameter characteristics. A model of turbine engine performance includes ranked parameters or parameter characteristics, the ranking of which is calculated by a model builder based upon a function of AIC, AUC and p-value, resulting in a corresponding importance rank. These raw parameters and raw parameter characteristics are then sorted according to their importance rank, and selected by a selection component to form one or more completed models. The one or more models are operatively coupled to one or more other models to facilitate further machine learning capabilities by the system.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title TURBINE DIAGNOSTIC FEATURE SELECTION SYSTEM
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