A Neural Network-Based Method for Gas Turbine Blading Fault Diagnosis

Author:

Angelakis C.1,Loukis E.N.2,Pouliezos A.D.3,Stavrakakis G.S.1

Affiliation:

1. Technical University of Crete, Dept. of Electronic and Computer Engineering, Chania 73100, Crete, Greece

2. University of Aegean, Dept. of Information and Communication Systems, Karlovassi 83200, Samos, Greece

3. Technical University of Crete, Dept. of Production Engineering and Management, Chania 73100, Crete, Greece;

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Mechanics of Materials,Modeling and Simulation,Software

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence;Energies;2023-08-22

2. Feature selection and feature learning in machine learning applications for gas turbines: A review;Engineering Applications of Artificial Intelligence;2023-01

3. Blade fault diagnosis using Mahalanobis distance;Journal of Mechanical Science and Technology;2021-03-24

4. Aero Engine Gas-Path Fault Diagnose Based on Multimodal Deep Neural Networks;Wireless Communications and Mobile Computing;2020-10-03

5. Bayesian network method for fault diagnosis of civil aircraft environment control system;Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering;2019-11-07

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