Methods and systems for neural network modeling of turbine components

A system for controlling a turbine, the system comprising a controller operable to:

• 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.

A method for modeling turbine clearance, the method comprising:

• 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.