During recent decades, artificial intelligence has been employed as a powerful tool for
identification of complex industrial systems with nonlinear dynamics, such as gas turbines …

This thesis investigates novel methodologies for modelling, simulation and control of gas
turbines using ANNs. In the field of modelling and simulation, two different types of gas …

In this paper ANN (Artificial Neural Network) identification techniques are developed to
estimate a General Electric frame 9, 116MW combined cycle, single shaft heavy duty gas …

Demonstration of different utilities for industrial use of an artificial neural network (ANN)
model for a gas turbine has been reported in this paper. The ANN model was constructed …

This paper develops a machine learning-based method to predict gas turbine performance
for power generation. Two surrogate models based on high dimensional model …

Modern power plants are all strongly dependent on reliable and accurate sensor readings
for monitoring and control, thus making sensors an important part of any plant. Failing …

Micro gas turbines are considered an efficient alternative to costly generation and
transmission of electricity, especially in remote areas and in combined heat and power …

Gas turbine engines are machines of high complexity and non-linearity. Interpreting the vast
amount of data from a gas turbine and converting them into customer value requires the …

In the paper, neural network (NN) models for gas turbine diagnostics are studied and
developed. The analyses carried out are aimed at the selection of the most appropriate NN …

In this paper, the diagnosis system of power plant gas turbine has been developed to detect
the deterioration of engine performance. This system can be analyzed the gas path …