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 …
[HTML][HTML] Intelligent fault diagnosis methods toward gas turbine: A review
LIU Xiaofeng, C Yingjie, L Xiong, W Jianhua… - Chinese Journal of …, 2024 - Elsevier
Fault diagnosis plays a significant role in conducting condition-based maintenance and
health management for gas turbines (GTs) to improve reliability and reduce costs. Various …
health management for gas turbines (GTs) to improve reliability and reduce costs. Various …
Micro Gas Turbine fault detection and isolation with a combination of Artificial Neural Network and off-design performance analysis
Abstract Recently Micro Gas Turbines deployment in smart grids is growing, which increases
engine load change during its lifecycle; consequently, lifetime reduces faster, and …
engine load change during its lifecycle; consequently, lifetime reduces faster, and …
Machine-learning-based condition assessment of gas turbines—A review
Condition monitoring, diagnostics, and prognostics are key factors in today's competitive
industrial sector. Equipment digitalisation has increased the amount of available data …
industrial sector. Equipment digitalisation has increased the amount of available data …
Aircraft engine gas-path monitoring and diagnostics framework based on a hybrid fault recognition approach
Considering the importance of continually improving the algorithms in aircraft engine
diagnostic systems, the present paper proposes and benchmarks a gas-path monitoring and …
diagnostic systems, the present paper proposes and benchmarks a gas-path monitoring and …
Integrating machine learning and thermodynamic modeling for performance prediction and optimization of supercritical CO2 and gas turbine combined power systems
The supercritical carbon dioxide (SCO 2) cycle has drawn attention to extracting energy and
generating power from low-grade heat resources due to its higher efficiency, lower cost, and …
generating power from low-grade heat resources due to its higher efficiency, lower cost, and …
Bayesian long short-term memory model for fault early warning of nuclear power turbine
G Liu, H Gu, X Shen, D You - Ieee Access, 2020 - ieeexplore.ieee.org
Fault early warning of equipment in nuclear power plant can effectively reduce unplanned
forced shutdown and avoid significant safety accidents. This paper presents a Bayesian …
forced shutdown and avoid significant safety accidents. This paper presents a Bayesian …
An innovative data-driven AI approach for detecting and isolating faults in gas turbines at power plants
This study investigated the detection and isolation of gas path faults in a power plant gas
turbine using efficiency data and fundamental quantities. First, attention is given to balancing …
turbine using efficiency data and fundamental quantities. First, attention is given to balancing …
Diagnostics and Prognostics in Power Plants: A systematic review
W Cheng, H Ahmad, L Gao, J Xing, Z Nie… - Reliability Engineering & …, 2024 - Elsevier
Failures in power plants can lead to significant power interruptions and economic losses.
Prognostics and Health Management (PHM) serves as a predictive maintenance technique …
Prognostics and Health Management (PHM) serves as a predictive maintenance technique …
The effect of physical faults on a three-shaft gas turbine performance at full-and part-load operation
A gas path analysis approach of dynamic modelling was used to examine the gas turbine
performance. This study presents an investigation of the effect of physical faults on the …
performance. This study presents an investigation of the effect of physical faults on the …