周登极, 邢同胜, 张麟, 马世喜, 郭永华. 大数据背景下天然气管网数据挖掘与应用[J]. 油气储运, 2021, 40(3): 271-276. DOI: 10.6047/j.issn.1000-8241.2021.03.005
引用本文: 周登极, 邢同胜, 张麟, 马世喜, 郭永华. 大数据背景下天然气管网数据挖掘与应用[J]. 油气储运, 2021, 40(3): 271-276. DOI: 10.6047/j.issn.1000-8241.2021.03.005
ZHOU Dengji, XING Tongsheng, ZHANG Lin, MA Shixi, GUO Yonghua. Data mining and its application in natural gas pipeline network under the context of big data[J]. Oil & Gas Storage and Transportation, 2021, 40(3): 271-276. DOI: 10.6047/j.issn.1000-8241.2021.03.005
Citation: ZHOU Dengji, XING Tongsheng, ZHANG Lin, MA Shixi, GUO Yonghua. Data mining and its application in natural gas pipeline network under the context of big data[J]. Oil & Gas Storage and Transportation, 2021, 40(3): 271-276. DOI: 10.6047/j.issn.1000-8241.2021.03.005

大数据背景下天然气管网数据挖掘与应用

Data mining and its application in natural gas pipeline network under the context of big data

  • 摘要: 大数据时代的来临带来了工业的大变革。为了提高工业生产效率、安全性和自动化水平,需要通过对工业大数据的充分挖掘利用,从海量数据中发现隐藏的规律,从而提高工业领域的信息管理水平,为智能监测、运行及维护提供技术支持。以大数据为背景,通过实例分析了数据挖掘技术在天然气管网负荷预测、安全预警、调度优化及性能监视中的应用方案及应用效果,进而从多源数据融合、综合信息平台建设、全生命周期管理等方面探讨了数据挖掘及相关技术的发展方向,展望了天然气管网数据挖掘广阔的应用前景。

     

    Abstract: The era of big data has brought about great changes in industry. In order to improve the efficiency, security and automation level of industrial production, it is necessary to find out the hidden rules in the massive data by fully mining and utilizing the big data of industry, so as to improve the level of information management in industry, further providing reliable technical support for intelligent monitoring, operation and maintenance. Herein, the application solution and effect of data mining in load forecasting, safety warning, scheduling optimization and performance monitoring of natural gas pipeline network under the context of big data were analyzed with specific cases. Based on that, the development direction of data mining and other relevant technologies was discussed from the perspectives of multi-data fusion, establishment of integrated information platform and full-life-cycle management. Moreover, the application of data mining in natural gas pipeline network was prospected.

     

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