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Method for use of in service inspection data in predicting future inspection intervals for seam welded steam pipes

机译:在使用中的检查数据预测焊缝蒸汽管道未来检查间隔的方法

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摘要

The dominant crack initiation and growth mechanisms for reheat steam pipes include creep and creep-fatigue, and the seam welds are particularly vulnerable. With historical data consisting of operating temperatures, pressures, average operating time between starts and stops, etc., and an extensive database of relevant material properties, an accurate model can be created that can be used to assess the risk of fracture in critical components and subsequent inspection strategies that mitigate the risks and lower them to acceptable levels. Physics based model predictions for material degradation combined with service experience based predictive approaches that constantly correct the model predictions using the experience base on specific machines can be used to create an approach that can produce highly reliable predictions. Such an approach requires the capability to solve inverse problems. This paper presents the capabilities of such a hybrid approach using reheat seam welded steam pipes as an example. It is demonstrated how the service database from successive previous inspections are used to reduce the variability encountered in weldment material properties to make more accurate inspection interval predictions.
机译:再热蒸汽管的主要裂纹萌生和扩展机制包括蠕变和蠕变疲劳,缝焊特别容易受到影响。利用包括工作温度,压力,开始和停止之间的平均工作时间等的历史数据,以及有关材料特性的广泛数据库,可以创建一个准确的模型,该模型可用于评估关键部件和零件断裂的风险。随后的检查策略可减轻风险并将其降低到可接受的水平。基于物理的材料退化模型预测与基于服务经验的预测方法相结合,使用基于特定机器的经验不断校正模型预测,可用于创建可以产生高度可靠的预测的方法。这种方法需要解决逆问题的能力。本文以再热缝焊接蒸汽管为例,介绍了这种混合方法的功能。演示了如何使用先前连续检查中的服务数据库来减少焊件材料属性中遇到的变化,从而做出更准确的检查间隔预测。

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