METHODS AND SYSTEMS FOR NEURAL NETWORK MODELING OF TURBINE COMPONENTS

Patent №

US 8,065,022

Granted

2011-11-22

Filed 2008

Owner

GENERAL ELECTRIC COMPANY

Lab

AI components

3

ml · kr · planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11971022

Embodiments of the invention can include methods and systems for controlling clearances in a turbine. In one embodiment, a method can include applying at least one operating parameter as an input to at least one neural network model, modeling via the neural network model a thermal expansion of at least one turbine component, and taking a control action based at least in part on the modeled thermal expansion of the one or more turbine components. An example system can include a controller operable to determine and apply the operating parameters as inputs to the neural network model, model thermal expansion via the neural network model, and generate a control action based at least in part on the modeled thermal expansion.

Machine learningKnowledge representationPlanningG05B 17/02F01D 11/20G05B 13/027F05D 2270/71Y10S 706/904Y10S 706/92

AI classification

Machine learning1.00
Planning1.00
Knowledge representation0.98
AI hardware0.13
Vision0.11
Evolutionary computation0.02
Speech0.01
Natural language0.00

Ownership

GENERAL ELECTRIC COMPANY

assignment · 203340827

Assignors

MINTO, KARL DEAN, ZHANG, JIANBO, KARACA, ERHAN

On an employer assignment, the assignors are typically the inventors.

From the same owner

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