Hybrid Data-Driven and Physics-Based Modelling for Prescriptive Maintenance of Gas-Turbine Power Plant
2019; Springer Science+Business Media; Linguagem: Inglês
10.1007/978-3-030-42250-9_36
ISSN1868-422X
AutoresS. Nikolaev, Sergei Belov, M. P. Gusev, Ighor Uzhinsky,
Tópico(s)Reservoir Engineering and Simulation Methods
ResumoThe methodology for prescriptive maintenance of complex technical systems is presented. The proposed methodology is based on a hybrid physics-based and data-driven modelling of complex systems. This approach integrates traditional physics-based simulation techniques such as finite-element modelling, finite-volume modelling, bond-graph modelling and data-driven models, with machine learning algorithms. Combined implementation of the both approaches results in the development of a set of reliable, fast and continuously updating models of technical systems applicable for predictive and prescriptive analytics. The methodology is demonstrated on the jet-engine power plant preventive maintenance case-study.
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