A Comprehensive Reliability Evaluation Model of Turbine Runner Blades under Complex Conditions

In this paper, a comprehensive method to evaluate the reliability of turbine runner blades under complex conditions has been proposed. The method takes into consideration the flow excitation parameters acting on the blades under different conditions, which present different uncertain information cha...

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Veröffentlicht in:Journal of failure analysis and prevention 2020-12, Vol.20 (6), p.2097-2105
Hauptverfasser: Li, Zhaojun, Mao, Xijun, Liu, Fuxiu, Huang, Yuyu, Heng, Xing
Format: Artikel
Sprache:eng
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Zusammenfassung:In this paper, a comprehensive method to evaluate the reliability of turbine runner blades under complex conditions has been proposed. The method takes into consideration the flow excitation parameters acting on the blades under different conditions, which present different uncertain information characteristics. The structural performance function of both vibration failure and fatigue failure of runner blades has been established, according to their vibration and fatigue characteristics. A probabilistic reliability model of the multi-failure modes of runner blades under their rated conditions has been established through application of random reliability theory, and a probabilistic non-probabilistic reliability model of the multi-failure modes of runner blades under non-rated conditions has been established by applying random reliability theory and non-probabilistic reliability theory, based on the structural performance function of both vibration failure and fatigue failure, taking into consideration the uncertain information characteristics of the flow excitation parameters that act on the runner blades under different conditions. On the basis of the two reliability models, a comprehensive model to evaluate the reliability of runner blades under complex conditions has been constructed. The reliability of the turbine runner blades under complex conditions has been analyzed through the use of examples, and the accuracy of the models has been proved using the Monte Carlo simulation (MCS).
ISSN:1547-7029
1728-5674
1864-1245
DOI:10.1007/s11668-020-01024-3