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 …
A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling
Machine learning is a promising method to model production processes and predict product
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
Implementing data mining techniques for gas-turbine (GT) health tracking and life management: The bibliographic perspective
AI Abed, LW Ping - Expert Systems with Applications, 2024 - Elsevier
In addition to power generation, gas turbines (GT) are crucial components in many
engineering applications, including those for aircraft, ships, and other machinery that needs …
engineering applications, including those for aircraft, ships, and other machinery that needs …
Improved and accurate fault diagnostic model for gas turbine based on 2D-wavelet transform and generative adversarial network
K Yao, Y Wang, S Fan, J Fu, J Wan… - … Science and Technology, 2023 - iopscience.iop.org
Severe working environments cause gas turbines to break down, which can directly affect
their performance. Research on the diagnostic methods for gas turbine faults, such as, gas …
their performance. Research on the diagnostic methods for gas turbine faults, such as, gas …
Discrimination of rapid and gradual deterioration for an enhanced gas turbine life-cycle monitoring and diagnostics
A Fentaye, V Zaccaria… - International Journal of …, 2021 - papers.phmsociety.org
Advanced engine health monitoring and diagnostic systems greatly benefit users helping
them avoid potentially expensive and time-consuming repairs by proactively identifying …
them avoid potentially expensive and time-consuming repairs by proactively identifying …
[图书][B] A Sequential Cross-Product Knowledge Accumulation, Extraction and Transfer Framework
J Xie - 2022 - search.proquest.com
The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of engineering system modelling. However, successful implementation of ML …
to the field of engineering system modelling. However, successful implementation of ML …
[PDF][PDF] Health Monitoring Algorithm for Turbofan Engine Using Cascade Feedforward Neural Networks
M Mahmoudi, M Khazaee, S Ghezeljeh… - International Journal of …, 2024 - ijrrs.com
Today, health monitoring systems for turbine engines have become a vital requirement in
the aviation industry. In this paper, different fault detection methods of turbine engines are …
the aviation industry. In this paper, different fault detection methods of turbine engines are …
Design and Development of Fault Detection in Gas Compressor Engines
AN Mohammad, A Ashoor, F Abdullah… - 2023 IEEE 8th …, 2023 - ieeexplore.ieee.org
The process and manufacturing industries have been focusing on improving product quality,
reducing rejection rates, and meeting stringent safety and environmental regulations …
reducing rejection rates, and meeting stringent safety and environmental regulations …