贾韶辉, 周利剑, 张新建, 郝文心. 长输管道时空序列数据分析[J]. 油气储运, 2016, 35(7): 713-717. DOI: 10.6047/j.issn.1000-8241.2016.07.006
引用本文: 贾韶辉, 周利剑, 张新建, 郝文心. 长输管道时空序列数据分析[J]. 油气储运, 2016, 35(7): 713-717. DOI: 10.6047/j.issn.1000-8241.2016.07.006
JIA Shaohui, ZHOU Lijian, ZHANG Xinjian, HAO Wenxin. Analysis on spatiotemporal data of long-distance pipelines[J]. Oil & Gas Storage and Transportation, 2016, 35(7): 713-717. DOI: 10.6047/j.issn.1000-8241.2016.07.006
Citation: JIA Shaohui, ZHOU Lijian, ZHANG Xinjian, HAO Wenxin. Analysis on spatiotemporal data of long-distance pipelines[J]. Oil & Gas Storage and Transportation, 2016, 35(7): 713-717. DOI: 10.6047/j.issn.1000-8241.2016.07.006

长输管道时空序列数据分析

Analysis on spatiotemporal data of long-distance pipelines

  • 摘要: 随着我国长输管道里程的不断增加,管道数据呈几何级数增长,挖掘管道数据在空间和时间上的分布规律,从而有针对性地采取预防措施,对管道安全运营具有非常重要的意义。以管道第三方施工和管道水工保护工程为例,基于管道完整性管理系统积累的大量数据,采用频谱分析技术与GIS技术,分析得出了我国长输管道在空间和时间上的分布规律:采用GIS技术分析其空间分布特性,得出第三方施工发生频次最高区域分布在银川、深圳、连云港、南京及无锡,同时对第三方施工数据进行傅里叶变换,得出其在时间上具有明显的周期性或拟周期性;采用GIS技术分析得出水工保护工程密度最高区域分布在忠县和萍乡,同时对各管道水工保护工程数据进行傅里叶变换,得出其在时间上不具有明显的周期性。最后,指出了采用非线性方法是长输管道时空序列数据分析的发展方向。

     

    Abstract: With the growing long-distance pipeline mileage in China, pipeline data grows exponentially. It is of great significance for the safe operation of pipelines to investigate the spatial and temporal distribution patterns of pipeline data, so as to take preventive measures. In this paper, the third-party construction and hydraulic protection project of pipelines were taken as examples for analysis. Based on a large amount of data collected in pipeline integrity management system, the spatial and temporal distribution patterns of domestic long-distance pipelines were, for the first time, analyzed by the frequency spectrum analysis technology and the GIS technology. The spatial distribution characteristics were analyzed by GIS technology. It is indicated that third-party construction is carried out most frequently in Yinchuan, Shenzhen, Lianyungang, Nanjing and Wuxi. By means of Fourier transform, the temporal distribution of the third-party construction data presents obvious periodicity or quasi-periodicity. It is revealed from the GIS analysis results that hydraulic protection projects are the densest in both Zhongxian and Pingxiang. When Fourier transform was performed on the data of pipeline hydraulic protection projects, no obvious periodicity was presented. Finally, it was proposed that non-linear method would be an effective way for spatiotemporal data analysis of long distance pipeline in the future.

     

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