Fast prediction and sensitivity analysis of gas turbine cooling performance using supervised learning approaches
Q Wang, L Yang, K Huang - Energy, 2022 - Elsevier
Fast prediction tools for turbine cooling performance have been demanded by industry for
decades to support the iterative design process and the comprehensive response analysis …
decades to support the iterative design process and the comprehensive response analysis …
Artificial neural network–based system identification for a single-shaft gas turbine
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 …
identification of complex industrial systems with nonlinear dynamics, such as gas turbines …
A dynamic prognosis scheme for flexible operation of gas turbines
The increase in energy demand has led to expansion of renewable energy sources and
their integration into a more diverse energy mix. Consequently the operation of thermal …
their integration into a more diverse energy mix. Consequently the operation of thermal …
Gas turbine sensor validation through classification with artificial neural networks
T Palmé, M Fast, M Thern - Applied energy, 2011 - Elsevier
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 …
for monitoring and control, thus making sensors an important part of any plant. Failing …
A sequential model-based approach for gas turbine performance diagnostics
YZ Chen, XD Zhao, HC Xiang, E Tsoutsanis - Energy, 2021 - Elsevier
The gradual degradation of gas turbine components is an inevitable result of engine
operation, impacting engine availability, reliability, and operating cost. Gas path analysis …
operation, impacting engine availability, reliability, and operating cost. Gas path analysis …
Performance diagnostics of gas turbines operating under transient conditions based on dynamic engine model and artificial neural networks
E Tsoutsanis, I Qureshi, M Hesham - Engineering Applications of Artificial …, 2023 - Elsevier
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 …
amount of data from a gas turbine and converting them into customer value requires the …
Feature selection and feature learning in machine learning applications for gas turbines: A review
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 …
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
Real-time power prediction approach for turbine using deep learning techniques
L Sun, T Liu, Y Xie, D Zhang, X Xia - Energy, 2021 - Elsevier
Accurate power forecasting is of great importance to the turbine control and predictive
maintenance. However, traditional physics models and statistical models can no longer …
maintenance. However, traditional physics models and statistical models can no longer …
Prediction of operating characteristics for industrial gas turbine combustor using an optimized artificial neural network
In this study, the operating characteristics of a gas turbine combustor are predicted using
real-time data from industrial gas turbines. The turbine exhaust temperature (TET) and major …
real-time data from industrial gas turbines. The turbine exhaust temperature (TET) and major …