ZHAO Yue, LAN Ying, QU Xian. Design of personnel positioning system in coal mine underground based on MEMS sensor[J]. Journal of Mine Automation, 2018, 44(8): 87-91. DOI: 10.13272/j.issn.1671-251x.17326
Citation: ZHAO Yue, LAN Ying, QU Xian. Design of personnel positioning system in coal mine underground based on MEMS sensor[J]. Journal of Mine Automation, 2018, 44(8): 87-91. DOI: 10.13272/j.issn.1671-251x.17326

Design of personnel positioning system in coal mine underground based on MEMS sensor

More Information
  • For problems of low positioning accuracy and high cost existed in current underground personnel positioning system, a personnel positioning system in coal mine underground based on MEMS sensor was designed. The system uses MPU9150 inertial sensor to obtain measurement data and takes CC2530 as the main control chip to collect and process data. It combines with pedestrian dead reckoning (PDR) algorithm and through existing underground WiFi base station to realize accurate positioning for underground personnel: it uses an expression that combined the variance of the walking frequency and acceleration to determine step length, and uses the quaternion method to estimated pedestrian orientation angle, uses extended Kalman filter to correct the original data, so as to obtain specific location of underground personnels. The experimental results show that the positioning error of the system is less than 2.2 m in 100 m, which can achieve high accuracy of personnel positioning in coal mine underground.
  • Related Articles

    [1]GAO Lijun, JIN Fadong, LIANG Dongyu, YANG Wenbin, TANG Yepeng, WANG Tong. Study on the stress distribution of surrounding rock and the inclination effect of gangue filling features in steeply dipping mining sites[J]. Journal of Mine Automation, 2024, 50(3): 142-150. DOI: 10.13272/j.issn.1671-251x.2023100064
    [2]CHANG Lizong, SU Xuegui, DU Xianjie, YANG Pengbo, GUO Maomao. Research on mining damage characteristics of roadway support structure in high stress area[J]. Journal of Mine Automation, 2021, 47(3): 20-26. DOI: 10.13272/j.issn.1671-251x.2020100043
    [3]XUE Yanping. Optimal measures for gas control on fully mechanized working face of close-distance coal seam group[J]. Journal of Mine Automation, 2021, 47(2): 98-103. DOI: 10.13272/j.issn.1671-251x.2020060055
    [4]ZHANG Shaohua, ZHANG Yuchen, LIU Yiming. Research on mining stress distribution law of overburden under typical key strata structure[J]. Journal of Mine Automation, 2019, 45(12): 50-53. DOI: 10.13272/j.issn.1671-251x.2019060026
    [5]LI Zhu, XIE Feng. Research on slope stability of open-pit mine under coupled seepage-stress[J]. Journal of Mine Automation, 2018, 44(12): 83-88. DOI: 10.13272/j.issn.1671-251x.17368
    [6]YANG He, QIU Liming, WANG Hao, ZHANG Ziyang, ZHAO Cong. Numerical simulation research on mining stress field of overlying coal-rock seam under far distance lower protective seam mining[J]. Journal of Mine Automation, 2017, 43(6): 37-41. DOI: 10.13272/j.issn.1671-251x.2017.06.009
    [7]JIANG Zilong, CHEN Wenlong, LIU Youjian. Research on variation law of secondary stress on working face of Guotun Coal Mine[J]. Journal of Mine Automation, 2017, 43(4): 18-21. DOI: 10.13272/j.issn.1671-251x.2017.04.005
    [8]YU Zhanhe. Research of surrounding rock instability and support of deep mining roadway affected by dynamic pressure[J]. Journal of Mine Automation, 2017, 43(2): 66-70. DOI: 10.13272/j.issn.1671-251x.2017.02.014
    [9]HAO Tian-xuan, ZHANG Hai-bo. Realization of visualization multivariable prediction method for gas content based on grey system theory[J]. Journal of Mine Automation, 2013, 39(6): 6-9.
    [10]ZHAO Yan-ming. Predicting Model of Gas Content Based on Improved BP Neural Network[J]. Journal of Mine Automation, 2009, 35(4): 10-13.
  • Cited by

    Periodical cited type(3)

    1. 薛江达,孙永康,王军,张庚. 水力压裂弱化顶板护孔技术. 工矿自动化. 2024(03): 160-166 . 本站查看
    2. 宋昱播. 复杂软弱煤层条件下高转速大扭矩钻探装备设计及试验研究. 煤矿安全. 2024(06): 200-205 .
    3. 段会军. 碎软煤层高速螺旋钻探装备研制与实践. 煤矿机械. 2024(10): 165-168 .

    Other cited types(0)

Catalog

    Article Metrics

    Article views (122) PDF downloads (15) Cited by(3)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return