Methods and Systems for Neural Network Modeling of Turbine Components
First Claim
1. A method for controlling clearance in a turbine, the method comprising:
- applying at least one operating parameter as an input to at least one neural network model;
modeling via the at least one neural network model thermal expansion of at least one turbine component; and
implementing a control action based at least in part on the modeled thermal expansion of the at least one turbine component.
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Abstract
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.
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Citations
20 Claims
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1. A method for controlling clearance in a turbine, the method comprising:
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applying at least one operating parameter as an input to at least one neural network model; modeling via the at least one neural network model thermal expansion of at least one turbine component; and implementing a control action based at least in part on the modeled thermal expansion of the at least one turbine component. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for controlling a turbine, the system comprising a controller operable to:
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determine at least one operating parameter; apply the at least one operating parameter as an input to at least one neural network model; model via the at least one neural network model thermal expansion of at least one turbine component; and generate a control action based at least in part on the modeled thermal expansion of the at least one turbine component. - View Dependent Claims (13, 14, 15, 16)
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17. A method for modeling turbine clearance, the method comprising:
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sensing a first and a second operating parameter; modeling at least one shell temperature parameter based at least in part on the first sensed operating parameter; modeling at least one rotor temperature parameter based at least in part on the second sensed operating parameter; determining a shell thermal expansion by applying the at least one shell temperature parameter as an input to a shell expansion neural network model; determining a rotor thermal expansion by applying the at least one rotor temperature parameter as an input to a rotor expansion neural network model; and determining a differential expansion based at least in part on the difference between the rotor thermal expansion and the shell thermal expansion. - View Dependent Claims (18, 19, 20)
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Specification