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Fatigue damage assessment method of turbine shafts' torsional vibrations under SSO incidents

机译:SSO事件下涡轮轴扭转振动的疲劳损伤评估方法

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摘要

Sub-Synchronous Oscillation (SSO) can pose severe threat to the steam turbine shafting system, which in particular is the torsional vibrations leading to the hazard or shut down of the power units. A method is developed to evaluate fatigue damage under SSO incidents, which utilizes field data and modal decomposition and superposition concepts, and combines the structural full-size FEA (finite element analysis) modal analysis with refined finite element structural analysis of specific parts. Applying such method to a 330 MW steam turbine shafting system, our study illustrates its torsional vibration characteristics under different modes of SSO incidents. The results indicate that the proposed method is faster than conventional full-size transient analysis, decreasing the computational cost. We find that coupling shrinkage structure is the most vulnerable part, which is consistent with engineering practice and thus perfects our traditional understanding that connecting parts in journals are the only vulnerable parts. At the end of this paper, we also point out that with the presence of SSO incident, decreasing the load on shafts in time would help alleviate the damage.
机译:子同步振荡(SSO)可以对蒸汽轮机刮板系统构成严重威胁,特别是导致电力单元的灾害或关闭的扭转振动。开发了一种方法来评估SSO事件下的疲劳损伤,它利用现场数据和模态分解和叠加概念,并结合了结构全尺寸FEA(有限元分析)模态分析与特定部件的精制有限元结构分析。将这种方法应用于330 MW汽轮机备件系统,我们的研究说明了其在不同模式下的扭转振动特性。结果表明,该方法比传统的全尺寸瞬态分析更快,降低计算成本。我们发现耦合收缩结构是最脆弱的部分,这与工程实践一致,因此完善了我们的传统理解,即期刊中的零件是唯一的脆弱部件。在本文的末尾,我们还指出,随着SSO事件的存在,及时降低轴上的负荷将有助于缓解损坏。

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