• 中文核心期刊
  • 中国科技核心期刊
  • RCCSE中国核心学术期刊

基于井下巷道网络与定位设备数据联合拓扑的井下精确定位系统实时定位纠偏算法

周翔, 韩燕南, 周嘉欣

周翔, 韩燕南, 周嘉欣. 基于井下巷道网络与定位设备数据联合拓扑的井下精确定位系统实时定位纠偏算法[J]. 煤矿安全, 2022, 53(5): 122-128.
引用本文: 周翔, 韩燕南, 周嘉欣. 基于井下巷道网络与定位设备数据联合拓扑的井下精确定位系统实时定位纠偏算法[J]. 煤矿安全, 2022, 53(5): 122-128.
ZHOU Xiang, HAN Yannan, ZHOU Jiaxin. Real-time positioning correction algorithm for precise personnel positioning system in underground mine based on topologies of combined mine network and positioning equipment data[J]. Safety in Coal Mines, 2022, 53(5): 122-128.
Citation: ZHOU Xiang, HAN Yannan, ZHOU Jiaxin. Real-time positioning correction algorithm for precise personnel positioning system in underground mine based on topologies of combined mine network and positioning equipment data[J]. Safety in Coal Mines, 2022, 53(5): 122-128.

基于井下巷道网络与定位设备数据联合拓扑的井下精确定位系统实时定位纠偏算法

Real-time positioning correction algorithm for precise personnel positioning system in underground mine based on topologies of combined mine network and positioning equipment data

  • 摘要: 针对煤矿井下人员的定位精度易受硬件系统测算误差以及复杂巷道条件的影响,从而导致定位结果与人员在井下的真实位置存在偏差问题,提出了一种可应用于井下精确定位系统的基于井下巷道-定位设备拓扑结构的实时定位纠偏算法;首先构建出巷道网络及其与定位设备之间的拓扑关系,其次计算出定位设备测距信号在巷道方向的偏离量,最后利用拓扑计算的结果和测距偏离量完成人员定位的实时位置纠偏。试验结果表明:算法在较为复杂的巷道条件下,平均纠偏计算耗时约为0.002 5 s,巷道定位的准确率超过90%,坐标纠偏误差较小,在具备较高的纠偏准确率和实时性的同时,也保持了良好的鲁棒性。
    Abstract: For the problem that the accuracy of personnel positioning in coal mines is susceptible to the calculation errors of the hardware system and complex roadway conditions, which leads to the problem of inconsistency between the calculation results and the actual position coordinates of the personnel, a real-time positioning correction algorithm based on topological structure of lanes and positioning equipment for precise personnel positioning system in underground mine was proposed. Firstly, the topological relationship between lanes and positioning equipment was constructed; then, the deviation of personnel ranging signal was calculated; finally, the real-time position correction of personnel positioning was realized based on the topology network and deviation of ranging signal. Test results show that in the complex condition of lanes, the average time-consuming of correction calculation was about 0.002 5 s, and the accuracy of lanes positioning was higher than 90%, the error between coordinate correction and actual measurement is small. Experimental results show that proposed method can get high correction accuracy, real-time effects and robustness.
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  • 发布日期:  2022-05-19

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