分析了环境因素对汽轮机性能的影响,建立了与选定维修因素有关的维修周期模型

Magdalena Thielmann
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引用次数: 0

摘要

目前全球约有18000台燃气轮机在使用,有近7500个长期服务协议[1]。与此同时,新订单逐年增加,在2020年产量从353台下降到328台之后,从2022年开始,计划将产量提升到之前的增长水平。燃气轮机在全球范围内运行,并且暴露于环境条件的变化,例如湿度,温度和盐度的变化,这些变化会显着影响效率和单个组件的更快降解。根据该机组的维护报告,每年有超过1940次事件警报。需要建立一个更动态的分析和数值模型来确定环境变量对燃气轮机稳定性的影响。有必要分析和改进现有的可靠性模型,这些模型因配置和工作条件的影响而变化。第一步应分析环境因素对涡轮机性能的影响。本文描述了燃气轮机维修检测模型是如何从一个随时间平均值模型发展到一个跟踪实际退化的模型的。它包括研究中使用的三种模型的比较,考虑到选择输入参数的开发方法,它们的相关性,以及它们在进一步分析中使用的适当性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The analysis of the impact of environmental factors on turbine performance, develpoment of the models relating the periods between maintenances with selected maintenance factors
There are currently around 18,000 commissioned Gas Turbines in use worldwide, with almost 7,500 long-term service agreements[1]. At the same time, orders for new units increase year by year, and after a decrease in production in 2020 from 353 to 328 new units, from 2022 onwards, the level is planned to rise to the previous level of growth. Gas turbines operate worldwide and are exposed to variations in environmental conditions, such as changes in humidity, temperature, and salinity, which can significantly affect the efficiency and faster degradation of individual components. Based on the unit's maintenance report, there are more than 1,940 event alerts annually. A need exists to create a more dynamic analytical and numerical model that determines the impact of environmental variables on gas turbine stability. It is necessary to analyze and improve existing reliability models, which vary due to configurations and the impact of working conditions. The first step should be an analysis of the impact of environmental factors on turbine performance. This paper describes how the maintenance and inspection model developed from an average value over time model to a model tracking the actual degradation of gas turbines. It includes a comparison ofthree models used in the research, considering the developed methodology for selecting input parameters, their correlation, and their appropriateness for use in further analyses.
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