摘要
针对现有的钨矿井下矿车定位系统的布线困难、信息化和可视化水平低等问题,为了更加合理、高效地调度矿车,设计了一种基于Zig Bee的无线网络系统,实现对井下矿车定位及安全监测。首先探讨了井下环境无线信号传输的RSSI测距模型,并采用高斯滤波对RSSI测距参数进行修正后,结合极大似然估计定位方法实现矿车定位,针对此定位算法存在的较大误差,提出了加权质心定位算法来提高矿车定位的准确性。然后通过上位机将井下采集的矿车速度和定位信息实时显示在井上监控主机和大屏幕中。通过实验仿真,结果证明,改进的加权质心定位算法有效地降低了定位误差,上位机对速度数据信息可实现调用、存储、实时显示、查询并预警等功能,系统具有实时性强、精度高、鲁棒性好等特点,可以有效提升钨矿井下开采生产的安全性。
In view of wiring difficulties,low level of information and visualization problems about underground tramcar positioning system in tungsten mine,and in order to more reasonably and efficiently schedule tramcar,a real-time positioning and monitoring system of the tramcar based on ZigBee wireless network was proposed to realize underground positioning and safety monitoring on tramcars. RSSI ranging model for transferring wireless signal of ground environment was explored. Then, with the aid of Gauss filter,the RSSI ranging parameters were modified. Then,combined with the multilateral localization algo-rithm,the positioning was achieved. For large errors in the algorithm,the weighted centroid localization algorithm was proposed to improve the positioning accuracy. The underground tramcar speed and position information were real-time uploaded and well displayed on host computer. Through simulation experiments,the results demonstrated that the modified weighted centroid algo-rithm can effectively lower the positioning error,and the host computer can realize the transfer,storage,real-time display,que-ry,and early warning and other functions. The system has the characteristics of real-time,high accuracy and good robustness, which can effectively improve the safety of production in tungsten mine.
出处
《金属矿山》
CAS
北大核心
2015年第2期127-132,共6页
Metal Mine
基金
国家自然科学基金项目(编号:61163063
50764005)
江西省教育厅科技项目(GJJ12329
GJJ12353
GJJ14441)
关键词
ZIGBEE无线网络
钨矿
井下矿车定位
极大似然估计
加权质心
RSSI
ZigBee wireless network
Tungsten mine
Underground tramcar positioning
Received signal strength indica-tion
Maximum likelihood
Weighted centroid
