Improving the Performance of a Pipeline Crack Detection Embedded System

阿尔伯塔生产的石油产品需要安全有效地运输到其他市场， 如精炼。管道正成为越来越受欢迎的解决方案，因为它们对环境的影响较小， 比铁路等其他交通方式对人类生命的直接风险更大。然而，管道运营商必须检测 主动解决泄漏等问题，并在造成环境破坏之前解决这些问题。通常，管道 操作员使用称为智能猪的嵌入式计算机系统来检测微小的缺陷，这可能会 可能导致泄漏。Encompass Inspections Canada是一家开发出最先进的猪 系统，并成功地部署了它的主要客户，如壳牌和恩布里奇。通常情况下，猪旅行 收集关于段的轮廓的信息的管线的段。这些数据存储在内部 猪的记忆在遍历段之后，收集设备并将其数据传输到字段 笔记本电脑.膝上型计算机上的可视化软件用于提供 管道缺陷。从长远来看，需要解决几个技术挑战，以改善 系统的功效。特别是，可视化软件目前不提供实时渲染 长管道段的数据。分析师不得不等待很长时间，从而影响了敏捷性 的过程。该提案旨在启动研究，重点是优化整个系统的性能， 制度来解决这些问题。例如，一种解决方案是压缩通过网络传输的数据量。 清管器，因为通常大多数数据属于管道的部分，这些部分不太可能发生严重的 裂纹这可以减少将数据传输到笔记本电脑所需的时间以及处理的数据量 通过可视化软件。另一种补充解决方案是使用并行处理技术，例如， 使用笔记本电脑的图形处理器单元（GPU）进行处理，以加快数据可视化。成果 这一领域的长期研究可能会提高管道安全性，从而也有利于环境 作为加拿大的经济。

Petroleum products produced in Alberta need to be safely and efficiently transported to other markets for purposes such as refining. Pipelines are becoming an increasingly preferred solution since they pose lesser direct risk to human lives than other modes such as rail. It is crucial however that pipeline operators detect problems such as leaks proactively and fix them before they cause environmental damage. Typically, pipeline operators use embedded computer systems called smart pigs to detect minute imperfections, which could potentially lead to leaks. Encompass Inspections Canada is a company that has developed a state-of-the-art pig system and successfully deployed it for major clients such as Shell and Enbridge. Typically, the pig travels a section of the pipeline collecting information about the contours of the segment. This data is stored internally in the pig's memory. After traversing the segment, the device is collected and its data is transferred to a field laptop. Visualizing software on the laptop is used to provide graphical views of the location and dimensions of pipeline imperfections. Several technical challenges need to be addressed in the long-term to improve the efficacy of the system. In particular, the visualization software currently does not provide real-time renderings of the data for long pipeline segments. Analysts have to wait for a long time thereby compromising the agility of the process. This proposal aims to initiate research that focuses on optimizing the performance of the entire system to redress such problems. For example, one solution is to compress the amount of data transmitted by the pig since typically most of the data pertains to portions of the pipeline that are unlikely to develop serious cracks. This can reduce the time needed to transfer the data to the laptop and also the amount of data handled by the visualization software. Another complementary solution is to use parallel processing techniques, e.g., processing using the laptop's Graphic Processor Units (GPUs), to speed up data visualization. Outcomes of long term research in this area is likely to improve pipeline safety thereby benefitting the environment as well as the economy of Canada.