基于灰色预测模型的井下精确人员定位方法

唐丽均, 吴畏, 刘世森

唐丽均，吴畏，刘世森.基于灰色预测模型的井下精确人员定位方法［J］.工矿自动化，2021,47（8）：128-132.. DOI: 10.13272/j.issn.1671-251x.2021060027
引用本文: 唐丽均，吴畏，刘世森.基于灰色预测模型的井下精确人员定位方法［J］.工矿自动化，2021,47（8）：128-132.. DOI: 10.13272/j.issn.1671-251x.2021060027
shu
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
shu

基于灰色预测模型的井下精确人员定位方法

  • 1.

    重庆工程职业技术学院 大数据与物联网学院， 重庆402260

  • 2.

    重庆城市管理职业学院 智能工程学院， 重庆401331

  • 3.

    中煤科工集团重庆研究院有限公司， 重庆400039

基金项目: 

国家重点研发计划资助项目(2018YFC0808303)

详细信息

  • 中图分类号: TD76

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

  • 1.

    Big Data and Internet of Things School, Chongqing Vocational Institute of Engineering,Chongqing 402260 China

  • 2.

    School of Intelligent Engineering, Chongqing City Management College, Chongqing 401331, China

  • 3.

    CCTEG Chongqing Research Institute, Chongqing 400039, China

摘要

    摘要
  • 摘要: 井下精确人员定位系统的定位精度受非视距误差和时钟误差的影响，目前系统多采用基于卡尔曼滤波的定位方法来减小误差，但当测量数据出现粗大误差时定位精度不高。针对该问题，提出了一种基于灰色预测模型的井下精确人员定位方法。携带标志卡的人员进入定位读卡器覆盖范围时，定位读卡器通过无线定位技术计算出标志卡与读卡器之间的测量距离，并将测量距离存储至数据缓存区；根据数据缓存区内的测量距离，采用GM(1，1)模型计算出下一时刻标志卡与读卡器之间的预测距离；当该预测距离的预测精度等级为优，且与测量距离之差超过误差判断阈值时，用该预测距离替代测量距离，实现对测距误差的优化补偿。测试结果表明，该方法不受测距误差影响，当测量距离存在粗大误差时，该方法的定位精度明显优于基于卡尔曼滤波的定位方法。
    Abstract: 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.
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出版历程
  • 刊出日期:  2021-08-19

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