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Risk-based maintenance planning of subsea pipelines through fatigue crack growth monitoring

机译:通过疲劳裂纹生长监测基于风险的海底管道维护计划

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摘要

Research and development in the field of risk-based maintenance of offshore structures has recently attracted large attention due to the significant level of accident risk and the cost associated with maintenance in such remote facilities. The uncertainties associated with the deterioration of these facilities require a sound decision making methodology for maintenance planning. This paper presents a dynamic risk-based methodology for maintenance scheduling of subsea pipelines subjected to fatigue cracks. The developed method can assist the asset managers to select the optimum approach for mitigating the consequences of failure while minimizing the maintenance costs. A Bayesian network is developed to model the probabilistic deterioration process and then it is extended to an influence diagram for estimating the expected utility of each decision alternative. Observation of damage state is included in the model to enhance decision making capacity. To demonstrate the applicability of the methodology, three cases with different fatigue crack incidents on a pipeline are considered. Based on the monitoring results, the model is able to determine whether the maintenance should be performed or not. The economic risk associated with maintenance is also minimized by suggesting the optimum maintenance technique among multiple possible methods such as welding or major repair.
机译:由于事故风险显着程度和与此类远程设施维护的成本,近海结构基于风险维护领域的研究和开发最近引起了很大的关注。与这些设施恶化相关的不确定性需要用于维护计划的声音决策方法。本文介绍了一种基于风险的基于风险的方法,用于维持疲劳裂缝的海底管道的维护调度。开发的方法可以帮助资产管理者选择可减轻失败后果的最佳方法,同时最小化维护成本。开发了贝叶斯网络以模拟概率劣化过程,然后扩展到估计每个决策替代方案的预期效用的影响图。模型中包含对损坏状态的观察,以提高决策能力。为了证明方法的适用性,考虑了管道上具有不同疲劳裂缝事件的三种情况。根据监测结果,该模型能够确定是否应执行维护。通过建议焊接或重大修复等多种可能方法中的最佳维护技术,还可以最小化与维护相关的经济风险。

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