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Maintenance Analysis of Boiler Feed Pump Turbine Using Failure Mode Effect Analysis (FMEA) Methods

机译:失效模式影响分析法对锅炉给水泵汽轮机的维护分析

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The boiler feed pump turbine is a multistage pump driven by a boiler feed pump steam turbine on a steam power plant. A Boiler feed pump turbine has many failures, the example are high temperature and vibration in bearing and mechanical seal, leak in valve and line connection, etc. The failure in every component in the boiler feed pump turbine could be reduced by maintenance analysis. There were many methods for maintenance analysis, one of that was FMEA (Failure Mode Effect Analysis). FMEA was an engineering technique to define, identifying, and eliminate known and/or potential failures, problems, error by the ranked of risk priority number. The result of FMEA analysis could be made in the Pareto chart, from the Pareto chart could be conclude there are 9 of 14 components to did the maintenance first. The highest risk priority number (RPN) was turning gear with the RPN valued 392, the second risk priority number (RPN) was bearing with RPN value 294 and the third risk priority number (RPN) was a mechanical seal with RPN value 252. RPN value in every component could be used to determine a recommendation type of maintenance, the recommendation type of maintenance for turning gear was predictive maintenance, a bearing was preventive maintenance and a mechanical seal was preventive maintenance. Predictive maintenance was based on the condition of component, the example of preventive maintenance was cleaning, inspection, etc, and the example of corrective maintenance was changing the part had been broken, etc.
机译:锅炉给水泵涡轮机是由蒸汽发电厂上的锅炉给水泵蒸汽涡轮机驱动的多级泵。锅炉给水泵水轮机有许多故障,例如轴承和机械密封件的高温和振动,阀门和管路连接处的泄漏等。通过维护分析可以减少锅炉给水泵水轮机中每个组件的故障。维护分析的方法很多,其中之一就是FMEA(故障模式影响分析)。 FMEA是一种工程技术,用于通过风险优先级数字的排名来定义,识别和消除已知和/或潜在的故障,问题和错误。 FMEA分析的结果可以在帕累托图中得出,从帕累托图可以得出结论,在14个组件中有9个是首先进行维护的。最高风险优先级数字(RPN)是RPN值为392的旋转齿轮,第二风险优先级数字(RPN)带有RPN值294的轴承,而第三风险优先级数字(RPN)是RPN值为252的机械密封。RPN每个组件中的值都可以用来确定建议的维护类型,对于旋转齿轮的建议维护类型是预测性维护,轴承是预防性维护,而机械密封是预防性维护。预测性维护基于组件的状况,预防性维护的示例是清洁,检查等,而纠正性维护的示例是更改损坏的零件等。

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