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

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

Результат исследований: Вклад в журналСтатьярецензирование

2 Цитирования (Scopus)


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.

Язык оригиналаАнглийский
Номер статьи8541
Страницы (с-по)1-13
Число страниц13
ЖурналApplied Sciences (Switzerland)
Номер выпуска23
СостояниеОпубликовано - 1 дек. 2020


Подробные сведения о темах исследования «Residual life prediction of gas-engine turbine blades based on damage surrogate-assisted modeling». Вместе они формируют уникальный семантический отпечаток (fingerprint).