林现喜, 李银喜, 周信, 张克政. 大数据环境下管道内检测数据管理[J]. 油气储运, 2015, 34(4): 349-353. DOI: 10.6047/j.issn.1000-8241.2015.04.002
引用本文: 林现喜, 李银喜, 周信, 张克政. 大数据环境下管道内检测数据管理[J]. 油气储运, 2015, 34(4): 349-353. DOI: 10.6047/j.issn.1000-8241.2015.04.002
LIN Xianxi, LI Yinxi, ZHOU Xin, ZHANG Kezheng. Management of inline inspection data of pipelines under the environment of big data[J]. Oil & Gas Storage and Transportation, 2015, 34(4): 349-353. DOI: 10.6047/j.issn.1000-8241.2015.04.002
Citation: LIN Xianxi, LI Yinxi, ZHOU Xin, ZHANG Kezheng. Management of inline inspection data of pipelines under the environment of big data[J]. Oil & Gas Storage and Transportation, 2015, 34(4): 349-353. DOI: 10.6047/j.issn.1000-8241.2015.04.002

大数据环境下管道内检测数据管理

Management of inline inspection data of pipelines under the environment of big data

  • 摘要: 管道大数据的形成是大势所趋, 管道内检测数据是管道大数据中极其重要的组成部分.构建了大数据环境下管道内检测数据模型, 梳理了管道内检测数据管理流程, 提出在管道大数据背景下, 对内检测数据进行深度挖掘与应用, 主要包括: 管道多轮内检测数据比对, 管道内外检测数据比对, 管道位置精确定位及其在管道日常管理、维护维修、地理信息系统等的应用, 管道可靠性及安全状态评估等.由此, 可以有效提高管道管理水平, 保证管道安全可靠运行.

     

    Abstract: Forming of pipeline big data is an irresistible trend, while the inline inspection data of pipelines are major part of such big data. In this paper, the inline inspection data model of pipeline under the environment of big data is established, and the management process of such inline inspection data is streamlined. Moreover, the in-depth research and application of inline inspection data are discussed under the environment of big data, mainly including: comparison of data obtained from multiple inline inspection, comparison of data obtained from inline and external inspections, accurate locating of pipeline and its application in daily pipeline management, maintenance and repair, and geoinformation system, as well as evaluation on pipeline reliability and safety. In this way, the pipeline management level can be effectively enhanced to ensure the safe and reliable operation of pipelines.

     

/

返回文章
返回