Improving the Performance of a Pipeline Crack Detection Embedded System

提高管道裂纹检测嵌入式系统的性能

基本信息

  • 批准号:
    486313-2015
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Engage Grants Program
  • 财政年份:
    2015
  • 资助国家:
    加拿大
  • 起止时间:
    2015-01-01 至 2016-12-31
  • 项目状态:
    已结题

项目摘要

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.
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 操作员使用嵌入式计算机系统,称为智能猪,以检测微小的缺陷,这可能 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。

项目成果

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会议论文数量(0)
专利数量(0)

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Krishnamurthy, Diwakar其他文献

Krishnamurthy, Diwakar的其他文献

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{{ truncateString('Krishnamurthy, Diwakar', 18)}}的其他基金

Performance Management of Enterprise Application Systems in the Cloud Era
云时代企业应用系统的性能管理
  • 批准号:
    RGPIN-2018-04224
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
AR/MR software for improving communication and education outcomes of minimally verbal autistic people
AR/MR 软件可改善语言能力极低的自闭症患者的沟通和教育成果
  • 批准号:
    571326-2021
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Alliance Grants
Performance Management of Enterprise Application Systems in the Cloud Era
云时代企业应用系统的性能管理
  • 批准号:
    RGPIN-2018-04224
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Performance Management of Enterprise Application Systems in the Cloud Era
云时代企业应用系统的性能管理
  • 批准号:
    RGPIN-2018-04224
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Scalable Fog and Cloud Computing for Industrial IoT
适用于工业物联网的可扩展雾和云计算
  • 批准号:
    539276-2019
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Engage Grants Program
Performance Management of Enterprise Application Systems in the Cloud Era
云时代企业应用系统的性能管理
  • 批准号:
    RGPIN-2018-04224
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Performance Management of Enterprise Application Systems in the Cloud Era
云时代企业应用系统的性能管理
  • 批准号:
    RGPIN-2018-04224
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Performance evaluation and management of enterprise application systems
企业应用系统性能评估与管理
  • 批准号:
    311746-2013
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Performance management tools for big data applications
大数据应用的性能管理工具
  • 批准号:
    513200-2017
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Predictive analytics for Smarttarget: Proactive performance anomaly detection techniques for cloud-based Web services
Smarttarget 的预测分析:基于云的 Web 服务的主动性能异常检测技术
  • 批准号:
    514610-2017
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Engage Grants Program

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