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Taking Corrosion Management Seriously

机译：认真对待腐蚀管理

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Pipeline operators have an ongoing battle with corrosion, and are always making decisions about inspections, coating repairs, cathodic protection, inhibitor injection, and a myriad of other activities to fight this corrosion. Decision-making requires information, and a key source of data is internal inspection. The demand for increasingly accurate data has driven the development of hardware with an ever-higher density of sensors, improved batteries, massive on-board storage, and mechanical design that gives the sensors a smooth ride over welds, dents, wrinkles, at a wide range of speeds while maintaining a tiny gap to the pipe wall. The explosion in computing power, development of artificial intelligence and the ability to measure corrosion features in-field very accurately has resulted in substantial improvements in feature sizing and the larger the database of accurately measured real corrosion training features, the better the sizing will be. However it has become evident that some feature types cannot be sized with just one technology, in addition not all corrosion mechanisms are created equal, some progress much faster than others. It is important to remember that material properties and stress level also have a significant part to play in understanding pipeline condition and technologies to help us quantify these are now available.
机译：管道运营商具有腐蚀的持续战斗，始终做出关于检查，涂层维修，阴极保护，抑制剂注射的决定，以及对抗这种腐蚀的其他活动。决策需要信息，并且内部检查是内部检查的关键源。对越来越准确的数据的需求推动了硬件的开发，具有更高的传感器密度，改善的电池，大规模的板载存储和机械设计，使传感器在宽阔的焊缝，凹痕，皱纹，宽度下滑，凹痕，褶皱，宽度速度范围，同时保持到管壁的微小间隙。计算能力下的爆炸，人工智能的发展和测量腐蚀功能的能力非常精确地导致特征尺寸的大量改进和准确测量实际腐蚀训练特征的数据库越大，尺寸越好。然而，已经很明显，一些特征类型不能只用一种技术来大小，此外并非所有的腐蚀机制都是平等的，一些进展比其他技术要快得多。重要的是要记住，材料属性和压力水平还可以在理解管道状况和技术方面发挥重要部分，以帮助我们量化现在可用。

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    《Pipeline & gas journal》 |2019年第7期|69-69|共1页
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  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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