Residual life prediction of gas-engine turbine blades based on damage surrogate-assisted modeling

Boris Vasilyev, Sergei Nikolaev, Mikhail Raevskiy, Sergei Belov, Ighor Uzhinsky

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number8541
Pages (from-to)1-13
Number of pages13
JournalApplied Sciences (Switzerland)
Volume10
Issue number23
DOIs
Publication statusPublished - 1 Dec 2020

Keywords

  • Condition-based maintenance
  • Life
  • Real-time prognostics
  • Remaining useful life
  • Surrogate model

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