Volume 48 Issue 4
Apr.  2022
Turn off MathJax
Article Contents
Article Navigation >  Journal of Mine Automation  > 2022  >  48(4): 31-37, 113
LIU Haiqiang, CHEN Xiaojing, ZHANG Xinghua, et al. Key technologies of data warehouse for coal mine safety monitoring[J]. Journal of Mine Automation，2022，48(4)：31-37, 113.  doi: 10.13272/j.issn.1671-251x.2022010053
Citation: LIU Haiqiang, CHEN Xiaojing, ZHANG Xinghua, et al. Key technologies of data warehouse for coal mine safety monitoring[J]. Journal of Mine Automation，2022，48(4)：31-37, 113.  doi: 10.13272/j.issn.1671-251x.2022010053
shu

Key technologies of data warehouse for coal mine safety monitoring

doi: 10.13272/j.issn.1671-251x.2022010053
  • 1.

    CCTEG Changzhou Research Institute, Changzhou 213015, China

  • 2.

    School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China

  • 3.

    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China

  • Received Date: 2022-01-25
  • Rev Recd Date: 2022-04-11
    • Available Online: 2022-03-29
    Abstract
  • Due to the adoption of operational data storage method, the coal mine safety monitoring system can't use massive data effectively and the data analysis capability is poor. In order to solve the above problems, this paper proposes the key technologies of data warehouse for coal mine safety monitoring. According to the business requirements of coal mine safety monitoring, the functional structure of coal mine safety monitoring data warehouse is proposed. Moreover, the five business subjects are designed, including overrun analysis, calibration analysis, abnormal data analysis, measuring point network interruption analysis and personnel management analysis. The logical model of coal mine safety monitoring data warehouse is established by using the fact constellation model. The fact table and dimension table are designed by subject. The physical model of data warehouse is established by using SQL Server. According to the characteristics of coal mine safety monitoring data warehouse, data extraction, conversion and loading strategies are proposed. The different data extraction rules are used to extract data by subject. The data from different sources are processed through format conversion, cleaning and sorting. In the process of data loading, pre-loading, loading and post-processing operations are carried out.

     

    • FullText(HTML)
  • loading
    • References(16)
  • [1]
    王国法,王虹,任怀伟,等. 智慧煤矿2025情景目标和发展路径[J]. 煤炭学报,2018,43(2):295-305.

    WANG Guofa,WANG Hong,REN Huaiwei,et al. 2025 scenarios and development path of intelligent coal mine[J]. Journal of China Coal Society,2018,43(2):295-305.
    [2]
    新华社.国家矿山安监局: 2020年全国煤矿无重特大瓦斯事故[EB/OL]. （ 2021-01-08）[2022-01-03]. http://www.xinhuanet.com/2021- 01/08/c_1126961922.htm.

    Xinhua News Agency. China State Administration of Work Safety: there is no heavy and large gas accident in China in 2020[EB/OL]. （ 2021-01-08）[2022-01-03]. http://www.xinhuanet.com/2021-01/08/1126961922.htm.
    [3]
    DZEMYDIEN D,MASKELIUNAS S,RADZEVIIUS V. Approach of ensuring interoperability of multi-dimensional data warehouses for monitoring of water resources[J]. Journal of Environmental Engineering and Landscape Management,2021,29(1):9-20. doi: 10.3846/jeelm.2021.14112
    [4]
    何敏. 智慧矿山定义探讨[J]. 工矿自动化,2017,43(9):12-16.

    HE Min. Discussion on definition of wisdom mine[J]. Industry and Mine Automation,2017,43(9):12-16.
    [5]
    张鹏. 智能矿山大数据体系建设探索[J]. 工矿自动化,2021,47(增刊1):21-23,44.

    ZHANG Peng. Exploration on construction of big data system for intelligent mine[J]. Industry and Mine Automation,2021,47(S1):21-23,44.
    [6]
    孟光伟. 基于大数据技术的区域煤矿监管数据服务平台设计[J]. 工矿自动化,2021,47(10):97-102,109.

    MENG Guangwei. Design of a regional coal mine supervision data service platform based on big data technology[J]. Industry and Mine Automation,2021,47(10):97-102,109.
    [7]
    张毅. 基于数据仓库原理的煤矿精细化管理研究[D]. 徐州: 中国矿业大学, 2014.

    ZHANG Yi. Study on coal mine management based on the principle of data warehouse[D]. Xuzhou: China University of Mining and Technology, 2014.
    [8]
    贾国兵. 基于数据仓库的煤矿井下真三维建模与综合应用系统研发[D]. 沈阳: 东北大学, 2015.

    JIA Guobing. Development of real 3D modeling and integrated application system in coal mine downhole data based on the data warehouse[D]. Shenyang: Northeastern University, 2015.
    [9]
    刘馨蕊. 矿山生产数据集成系统构建与应用研究[D]. 沈阳: 东北大学, 2013.

    LIU Xinrui. Research on construction and application of mine production data integration system[D]. Shenyang: Northeastern University, 2013.
    [10]
    贾冬冬. 数据挖掘在冲击地压智能预警系统中的应用与研究[D]. 青岛: 山东科技大学, 2018.

    JIA Dongdong. The application and research of data mining in the impact ground pressure intelligent early warning system[D]. Qingdao: Shandong University of Science and Technology, 2018.
    [11]
    侯杰,胡乃联,李国清,等. 基于OLAP的矿业集团生产运营决策系统构建研究[J]. 中国矿业,2016,25(11):11-15,27. doi: 10.3969/j.issn.1004-4051.2016.11.004

    HOU Jie,HU Nailian,LI Guoqing,et al. Construction of production operation & decision-making system for mining group based on OLAP[J]. China Mining Magazine,2016,25(11):11-15,27. doi: 10.3969/j.issn.1004-4051.2016.11.004
    [12]
    BANERJEE S,BHASKAR S,SARKAR A,et al. A formal OLAP algebra for NoSQL based data warehouses[J]. Annals of Emerging Technologies in Computing,2021,5(5):154-161. doi: 10.33166/AETiC.2021.05.019
    [13]
    吴纪龙. 中医药大数据资源数据仓库构建及处方分析应用研究[D]. 北京: 北京交通大学, 2021.

    WU Jilong. TCM big data resources data warehouse construction and prescription analysis application research[D]. Beijing: Beijing Jiaotong University, 2021.
    [14]
    雷博文. 基于大数据的实时数据仓库的设计与实现[D].北京: 中国地质大学（北京）, 2021.

    LEI Bowen. Design and implementation of real-time data warehouse based on big data[D]. Beijing: China University of Geosciences（Beijing）, 2021.
    [15]
    许诗怡. 森林资源数据仓库管理系统研建与数据分析应用技术研究[D]. 北京: 北京林业大学, 2020.

    XU Shiyi. Research on forest resource data warehouse management system and data analysis and application technology[D]. Beijing: Beijing Forestry University, 2020.
    [16]
    李伟超. 停车管理数据仓库构建与可视化分析[D]. 西安: 西安电子科技大学, 2020.

    LI Weichao. Data warehouse construction and visual analysis of parking management[D]. Xi'an: Xidian University, 2020.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(7)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (245) PDF downloads(38) Cited by()
    Proportional views
    Related

    苏ICP备 05016349号-2

    Supported by: Beijing Renhe Information Technology Co. Ltd.  Visits：    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return