TANG Lijun, WU Wei, LIU Shisen. .Precise personnel positioning method in underground mine based on grey prediction model[J]. Journal of Mine Automation, 2021, 47(8): 128-132. DOI: 10.13272/j.issn.1671-251x.2021060027
Citation: TANG Lijun, WU Wei, LIU Shisen. .Precise personnel positioning method in underground mine based on grey prediction model[J]. Journal of Mine Automation, 2021, 47(8): 128-132. DOI: 10.13272/j.issn.1671-251x.2021060027

.Precise personnel positioning method in underground mine based on grey prediction model

More Information
  • The positioning accuracy of the precise personnel positioning system in underground mine is affected by the non-line-of-sight error and clock error. At present, the system mostly uses Kalman filter-based positioning method to reduce the error, but the positioning accuracy is not high when there is gross error in the measured data. In order to solve this problem, a precise personnel positioning method in underground mine based on grey prediction model is proposed. When a person carrying a marker card enters the coverage area of the positioning reader, the positioning reader calculates the measured distance between the marker card and the reader through wireless positioning technology and stores the measured distance into the data cache area. According to the measured distance in the data cache area, the GM (1, 1) model is used to calculate the predicted distance between the marker card and the reader at the next moment. When the prediction accuracy level of this predicted distance is excellent and the difference with the measured distance exceeds the error judgment threshold, the predicted distance is used to replace the measured distance to achieve the optimal compensation of the distance measurement error. The test results show that the method is not affected by the distance measurement error. When there is a gross error in the measured distance, the positioning accuracy of this method is significantly better than that of the Kalman filter-based positioning method.
  • Related Articles

    [1]JIA Yutao, LI Guanhua, PAN Hongguang, CHEN Haijian, WEI Xuqiang, BAI Junming. A fusion positioning method for underground personnel based on UWB and PDR[J]. Journal of Mine Automation, 2024, 50(6): 96-102, 135. DOI: 10.13272/j.issn.1671-251x.2024010071
    [2]LI Zhihai, LIU Zhixiang, XIE Miao, LI Yuqi, WANG Shuai. Error modeling and analysis of alternating measurement mode roadheader positioning system[J]. Journal of Mine Automation, 2022, 48(1): 7-15. DOI: 10.13272/j.issn.1671-251x.2021060015
    [3]SUN Yanxin, MAO Shanjun, SU Ying, YANG Meng. Research on improved PDR algorithm for underground personnel positioning[J]. Journal of Mine Automation, 2021, 47(1): 43-48. DOI: 10.13272/j.issn.1671-251x.2020080086
    [4]CHEN Wei. Research on precise positioning system of coal mine underground[J]. Journal of Mine Automation, 2019, 45(12): 86-90. DOI: 10.13272/j.issn.1671-251x.17409
    [5]MO Shupei, TANG Jin, DU Yongwan, CHEN Ming. Underground adaptive positioning algorithm based on SAPSO-BP neural network[J]. Journal of Mine Automation, 2019, 45(7): 80-85. DOI: 10.13272/j.issn.1671-251x.2019010066
    [6]CUI Lizhen, XU Fanfei, WANG Qiaoli, GAO Lili. Underground adaptive positioning algorithm based on PSO-BP neural network[J]. Journal of Mine Automation, 2018, 44(2): 74-79. DOI: 10.13272/j.issn.1671-251x.2017090028
    [7]HOU Beibei, SONG Yulong, CAO Shuo. An underground positioning algorithm of offset error correction based on RSSI[J]. Journal of Mine Automation, 2017, 43(11): 63-69. DOI: 10.13272/j.issn.1671-251x.2017.11.013
    [8]WANG Wei. Research on application of Hadoop in personnel positioning software system[J]. Journal of Mine Automation, 2017, 43(1): 66-68. DOI: 10.13272/j.issn.1671-251x.2017.01.016
    [9]LI Zhengdong, ZHANG Kefan, BAO Jianju. Precise positioning method of underground moving target based on distance measurement technology[J]. Journal of Mine Automation, 2015, 41(5): 9-12. DOI: 10.13272/j.issn.1671-251x.2015.05.003
    [10]LIU Jia, ZHU Hui, HUA Gang. Design of data model of underground personnel positioning and management system[J]. Journal of Mine Automation, 2013, 39(7): 90-92.
  • Cited by

    Periodical cited type(6)

    1. 刘清,刘军锋. 基于UWB的综采工作面推进度测量系统. 工矿自动化. 2024(04): 33-40 . 本站查看
    2. 刘超. 矿井通风安全监控系统优化研究. 煤矿机械. 2024(09): 190-192 .
    3. 郑学召,严瑞锦,蔡国斌,王宝元,何芹健. 矿井动目标精确定位技术及优化方法研究. 工矿自动化. 2023(02): 14-22 . 本站查看
    4. 王苏洁. 煤峪口煤矿基于WSN井下人员定位系统设计研究. 山东煤炭科技. 2023(03): 202-204+207 .
    5. 李自森,毛馨凯,王洪亮. 选煤厂智能照明控制. 工矿自动化. 2022(S1): 124-125+132 . 本站查看
    6. 白怡明,曾祥玉,李杰,辛凤阳,郭晓松,朱金龙. 基于卡尔曼滤波算法的UWB+IMU组合精确定位系统在选煤厂中的应用. 选煤技术. 2022(05): 85-90 .

    Other cited types(3)

Catalog

    Article Metrics

    Article views (115) PDF downloads (18) Cited by(9)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return