… of gas turbine condition monitoring, diagnostics, and prognostics using machine-learning …
The initial search query was: “gas turbine” AND (“soft sensor” OR “machine learning” OR “…

… The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …

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

… By looking at the enhanced data, we will also have better understanding of whether
additional sensors in the gas turbine can help in future machine learning algorithms. …

… The different steps of a machine learning pipeline, starting from data … machine learning
algorithms, real-time data integration, and explainable AI techniques to enhance gas turbine …

… of machine learning strategies that are applied to fault diagnosis problems, in this paper we
propose hybrid machine learning … The term hybrid indicates that both supervised learning (ie, …

… of different machine learning classification algorithms with three different data smoothing
techniques for gas turbine fault detection and isolation task. The gas turbine performance …

… This study compares machine learning tools to predict gas turbine performance over …
recuperated gas turbine power system designed for hybrid configuration. The LSTM turbine model …

… in industrial gas turbines (IGT) is the turbine blade. The design of turbine blades needs to …
, we demonstrate a probabilistic inverse design machine learning (PMI) framework to carry …

… gas turbine engine has been experimentally studied for different engine speeds and throttle
position. The gas turbine … experimental calibrations, machine learning has been applied to …