Classification and prediction of gas turbine gas path degradation based on deep neural networks
Author:
Affiliation:
1. School of Energy and Environment Southeast University Nanjing China
2. Equipment Department Huadian Hangzhou Banshan Power Generation Co., Ltd Hangzhou China
3. Equipment Department Huaneng Gas Turbine Power Generation Co., Ltd Nanjing China
Publisher
Wiley
Subject
Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.6539
Reference33 articles.
1. Thermo-economic-environmental multiobjective optimization of a gas turbine power plant with preheater using evolutionary algorithm
2. Gas turbine performance prognostic for condition-based maintenance
3. Modelling micro-turbines using Hammerstein models
4. Modelling of heat transfer and fluid flow in the hot section of gas turbines used in power generation: A comprehensive survey
5. A big data driven sustainable manufacturing framework for condition-based maintenance prediction
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