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Article

Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling

1
Central Institute of Aviation Motors, 111116 Moscow, Russia
2
Faculty of Power Engineering, Department of Gas Turbine Power Plants and Renewable Energy, Bauman Moscow State Technical University, 105005 Moscow, Russia
3
Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(23), 8541; https://doi.org/10.3390/app10238541
Received: 23 October 2020 / Revised: 23 November 2020 / Accepted: 26 November 2020 / Published: 29 November 2020
Blade damage accounts for a substantial part of all failure events occurring at gas-turbine-engine power plants. Current operation and maintenance (O&M) practices typically use preventive maintenance approaches with fixed intervals, which involve high costs for repair and replacement activities, and substantial revenue losses. The recent development and evolution of condition-monitoring techniques and the fact that an increasing number of turbines in operation are equipped with online monitoring systems offer the decision maker a large amount of information on the blades’ structural health. So, predictive maintenance becomes feasible. It has the potential to predict the blades’ remaining life in order to support O&M decisions for avoiding major failure events. This paper presents a surrogate model and methodology for estimating the remaining life of a turbine blade. The model can be used within a predictive maintenance decision framework to optimize maintenance planning for the blades’ lifetime. View Full-Text
Keywords: life; remaining useful life; condition-based maintenance; real-time prognostics; surrogate model life; remaining useful life; condition-based maintenance; real-time prognostics; surrogate model
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MDPI and ACS Style

Vasilyev, B.; Nikolaev, S.; Raevskiy, M.; Belov, S.; Uzhinsky, I. Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling. Appl. Sci. 2020, 10, 8541. https://doi.org/10.3390/app10238541

AMA Style

Vasilyev B, Nikolaev S, Raevskiy M, Belov S, Uzhinsky I. Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling. Applied Sciences. 2020; 10(23):8541. https://doi.org/10.3390/app10238541

Chicago/Turabian Style

Vasilyev, Boris, Sergei Nikolaev, Mikhail Raevskiy, Sergei Belov, and Ighor Uzhinsky. 2020. "Residual Life Prediction of Gas-Engine Turbine Blades Based on Damage Surrogate-Assisted Modeling" Applied Sciences 10, no. 23: 8541. https://doi.org/10.3390/app10238541

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