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STRUCTURAL HEALTH MONITORING OF PIPELINES FOR ENVIRONMENT POLLUTION MITIGATION

机译:减轻环境污染的管道的结构健康监测

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Oil and gas infrastructures may be exposed to landslides, earthquakes, corrosion and fatigue, and to damage from thefts or vandalism, leading to leakage and failure with serious economic and ecologic consequences. For this reason, an increasing interest in applied research on monitoring and protecting pipelines (for fuel, oil and natural gas transportation) arises. Aimed at the mitigation of catastrophic effects of human and natural damage, the present paper proposes a smart realtime Structural Health Monitoring (SHM) system capable to control structural integrity continuously, focusing on the issue of spillage for thefts of fuels which are not detectable, in realtime, by the existing monitoring systems. The system consists of a smart-pipeline containing a health monitoring integrated measurement chain, i.e. an enhanced Fiber Bragg Gratings-based fiber optics neural network on the pipes, for displacement and acceleration monitoring (gathering many other different measurements such as: ground motion, permanent ground displacement, pipeline temperature, pipeline deformation, leakage, etc.). Specifically, the ability to measure these characteristics at hundreds of points along a single fiber and the great accuracy of each point of measure, are particularly interesting for the monitoring of structures such as pipelines in order to detect hazardous and unauthorized intrusion and damage.
机译:石油和天然气基础设施可能会遭受滑坡,地震,腐蚀和疲劳,并可能因盗窃或故意破坏而遭受破坏,从而导致泄漏和故障,并带来严重的经济和生态后果。因此,人们对在监视和保护管道(用于燃料,石油和天然气运输)的应用研究中越来越感兴趣。为了减轻人为和自然破坏的灾难性影响,本文提出了一种智能的实时结构健康监测(SHM)系统,该系统能够连续控制结构完整性,重点在于无法检测到的燃油盗窃的溢出问题。实时,由现有的监控系统。该系统由一条智能管道组成,该管道包含一个健康监测集成测量链,即,管道上基于纤维布拉格光栅的增强型光纤神经网络,用于位移和加速度监测(收集许多其他不同的测量值,例如:地面运动,永久性地面位移,管道温度,管道变形,泄漏等)。具体地说,对于沿着一条光纤在数百个点上测量这些特性的能力以及每个测量点的高精度,对于监视管道等结构以检测危险和未经授权的入侵和损坏尤其令人感兴趣。

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