Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review
With the privatization and intense competition that characterize the volatile energy sector,
the gas turbine industry currently faces new challenges of increasing operational flexibility …
the gas turbine industry currently faces new challenges of increasing operational flexibility …
A review on gas turbine gas-path diagnostics: State-of-the-art methods, challenges and opportunities
Gas-path diagnostics is an essential part of gas turbine (GT) condition-based maintenance
(CBM). There exists extensive literature on GT gas-path diagnostics and a variety of …
(CBM). There exists extensive literature on GT gas-path diagnostics and a variety of …
Convolutional neural network-based deep transfer learning for fault detection of gas turbine combustion chambers
Gas turbine combustion chambers work in highly adverse environment and thus malfunction
more easily compared to other components. Fault detection of gas turbine combustion …
more easily compared to other components. Fault detection of gas turbine combustion …
Abnormality detection and failure prediction using explainable Bayesian deep learning: Methodology and case study with industrial data
Mistrust, amplified by numerous artificial intelligence (AI) related incidents, is an issue that
has caused the energy and industrial sectors to be amongst the slowest adopter of AI …
has caused the energy and industrial sectors to be amongst the slowest adopter of AI …
Gas path fault diagnosis for gas turbine group based on deep transfer learning
Gas turbines are widely used in power generation. To ensure reliability, data-driven
diagnosis has become increasingly popular. However, sufficient historical data are …
diagnosis has become increasingly popular. However, sufficient historical data are …
Fault detection and isolation of aeroengine combustion chamber based on unscented Kalman filter method fusing artificial neural network
Z Long, M Bai, M Ren, J Liu, D Yu - Energy, 2023 - Elsevier
Continuously improving the operational efficiency of aeroengine is an important part to
reduce the use of fossil energy and environmental pollution. This makes the combustion …
reduce the use of fossil energy and environmental pollution. This makes the combustion …
Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling
The main purpose of the present work is to propose an effective tool which allows to ensure
the protection and the safety measures against the instability phenomena in a gas turbine …
the protection and the safety measures against the instability phenomena in a gas turbine …
[HTML][HTML] Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Classification is an essential task for many applications, including text classification, image
classification, data classification, and so on. The present study investigates the accuracy of …
classification, data classification, and so on. The present study investigates the accuracy of …
Long short-term memory network-based normal pattern group for fault detection of three-shaft marine gas turbine
M Bai, J Liu, Y Ma, X Zhao, Z Long, D Yu - Energies, 2020 - mdpi.com
Fault detection and diagnosis can improve safety and reliability of gas turbines. Current
studies on gas turbine fault detection and diagnosis mainly focus on the case of abundant …
studies on gas turbine fault detection and diagnosis mainly focus on the case of abundant …
Improved hybrid modeling method with input and output self-tuning for gas turbine engine
M Xu, J Liu, M Li, J Geng, Y Wu, Z Song - Energy, 2022 - Elsevier
Gas-path model (GPM) plays a key role in the application of sensor fault tolerant control for
the gas turbine engine (GTE). However, the modeling accuracy of traditional physics-based …
the gas turbine engine (GTE). However, the modeling accuracy of traditional physics-based …