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首页> 外文会议>ASME international pipeline conference 2008 >OBTAINING CORROSION GROWTH RATES FROM REPEAT IN-LINE INSPECTION RUNS AND DEALING WITH THE MEASUREMENT UNCERTAINTIES
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OBTAINING CORROSION GROWTH RATES FROM REPEAT IN-LINE INSPECTION RUNS AND DEALING WITH THE MEASUREMENT UNCERTAINTIES

机译：通过重复的在线检查运行并获得测量不确定性来获得腐蚀增长速率

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The ability to accurately determine the rate of corrosion growth along a pipeline is an essential input into a number of key integrity management decisions. For example, corrosion rates are needed to predict pipeline reliability (probability of failure and/or probability of exceedance) as a function of time, to identify the need for and timing of field investigations and/or repairs and to determine optimum re-inspection intervals to name just a few applications. As more and more pipelines are now being inspected using intelligent in-line inspection (ILI) tools for a second or even third or fourth time, pipeline operators require reliable guidelines for comparing repeat ILI data sets to obtain valid corrosion growth rates.rnBecause of the measurement uncertainties associated with corrosion size estimated from a single ILI run, the corrosion growth rate calculated from consecutive ILI runs has a degree of uncertainty that needs to be considered in determining valid and accurate corrosion growth rates. The ratio between the measured corrosion growth and the measurement error is an important parameter in determining a meaningful distribution of the corrosion growth rate either when performing defect to defect comparisons or when comparing the defect populations in pipeline segments. When this ratio is small the associated uncertainty can be too large to make meaningful probabilistic inferences. As the ratio increases, the effect of measurement uncertainty becomes more manageable, allowing growth rate distributions to be calculated with reasonable confidence.rnThis paper describes an approach to define the probability distribution of corrosion growth rates as a function of a simple parameter that characterizes the ratio between the ILI-observed corrosion growth and the ILI measurement error. Thisrnapproach has been developed as part of an ongoing PRCI-sponsored research project to produce procedures for determining and validating corrosion growth rates from repeat ILI runs. The paper also provides examples using sample data from repeat ILI runs showing the application of these procedures, the treatment of measurement uncertainty, the resulting corrosion growth rate information that can be obtained and the associated level of confidence in the results.
机译：准确确定沿管道腐蚀增长速率的能力是许多关键完整性管理决策的一项重要输入。例如，需要腐蚀速率来预测管道可靠性（失效的概率和/或超标的概率）随时间的变化，以识别现场调查和/或维修的需求和时间，并确定最佳的重新检查间隔仅举几个例子。随着越来越多的管道正在使用智能在线检查（ILI）工具进行第二次，甚至第三次或第四次检查，管道运营商需要可靠的指南来比较重复的ILI数据集以获得有效的腐蚀增长率。与通过单个ILI运行估算出的腐蚀尺寸相关的测量不确定性，从连续ILI运行计算得出的腐蚀增长速率具有一定程度的不确定性，在确定有效和准确的腐蚀增长速率时应予以考虑。在执行缺陷与缺陷比较或比较管道段中的缺陷数量时，所测腐蚀增长与测量误差之间的比率是确定腐蚀增长速率有意义分布的重要参数。当该比率小时，相关的不确定性可能太大而无法做出有意义的概率推论。随着比率的增加，测量不确定性的影响变得更易于管理，从而可以合理地计算出增长率分布。rn本文介绍了一种定义腐蚀增长率的概率分布的方法，该概率分布是表征比率的简单参数的函数在ILI观察到的腐蚀增长和ILI测量误差之间。此方法已作为正在进行的PRCI资助的研究项目的一部分进行开发，以制定程序来确定和验证ILI重复运行的腐蚀增长率。本文还提供了一些示例，这些示例使用了来自重复ILI运行的示例数据，这些示例数据显示了这些程序的应用，测量不确定度的处理，可获得的最终腐蚀速率信息以及相关结果的置信度。

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