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主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
煤炭工业监控大数据平台建设与数据处理应用技术
  • Title

    Platform construction and data processing application technology in coal industry monitoring big data

  • 作者

    张元刚刘坤杨林1王磊

  • Author

    ZHANG Yuangang,LIU Kun,YANG Lin,WANG Lei

  • 单位

    兖矿集团有限公司 信息化中心北斗天地股份有限公司,陕西兖州煤业股份有限公司 兴隆庄煤矿

  • Organization
    1.Information Center,Yankuang Group,Zoucheng ,China;2.Beidou Tiandi Co.,Ltd,Xi’an 710000;3.Xinglongzhuang Coal Mine,Yanzhou Coal Industry Co.,Ltd.,Yanzhou
  • 摘要

    为保障煤矿的安全高效生产,及时准确地预测可能发生的故障及灾害,通过分析兖矿集团煤矿大数据的现状及存在的问题,探讨了在大数据时代下,煤炭工业监控大数据平台的建设和使用方法。依托互联网、云计算和大数据技术,采集、整理和存储海量数据。通过数据挖掘技术和视频分析技术来探索发掘现场生产规律,从而提高煤矿应对潜在灾害和发现安全隐患的能力。以煤矿带式输送机工况监控系统大数据和视频监控系统大数据分析为例,分别使用流形空间的非平衡处理技术和分水岭等视觉技术对数据进行处理。试验结果表明:流形空间的过采样技术可以提高AUC指标20%左右,且基于机器视觉的煤流检测也能达到较好的效果。同时,探讨了大数据与煤炭工业监控系统的结合,并提出了报警数据融合应用的具体解决方法。

  • Abstract
    In order to ensure the safe and efficient production of coal mines, and forecast the faults and the disa sters timely and accurately, this paper analyzes the current situation and existing problems of coal mines big data in Yankuang Group, and explores the construction and application of big data platform for coal industry monitoring. Massive data is collected, processed and stored by using the internet, cloud computing and big data technology. Through data mining technology and video analysis technology to explore the production rules of the site, the ability of coal mines can be improved in dealing with potential disasters and identifying potential safety hazards. Taking the big data analysis of the coal mine belt conveyor monitoring system and video monitoring system as examples, the data is processed by using the manifold space imbalance processing technology and watershed algorithm. The experimental results show that the manifold space imbalance processing technology can increase the AUC index by about 20%, and the coal flow detection based on machine vision can also achieve better performance. Meanwhile, the combination of big data and coal industry monitoring system is discussed, and the specific solution of alarm data fusion application is proposed.
  • 关键词

    大数据工业监控大数据视频大数据分析带式输送机煤矿

  • KeyWords

    big data; industrial monitoring big data; video big data analysis; belt conveyer; coal mine

  • 相关专题
  • 图表
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    • 煤流运输设备在线监测及预警分析系统总体功能结构

    图(2) / 表(0)

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主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

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