煤矿自动驾驶磁寻迹定位技术

杨丽

doi:10.13272/j.issn.1671-251x.2021110049

煤矿自动驾驶磁寻迹定位技术

doi: 10.13272/j.issn.1671-251x.2021110049

杨丽

中煤科工集团北京华宇工程有限公司, 北京　100120

基金项目: 中国煤炭科工集团创新创业重点项目（2018-TD-ZD008）。

详细信息

作者简介:
杨丽（1982— ），女，北京人，高级工程师，硕士，主要从事智能化矿山设计相关工作，E-mail: 625017892@qq.com

中图分类号: TD655
计量
- 文章访问数: 424
- HTML全文浏览量: 136
- PDF下载量: 39
- 被引次数: 0
出版历程
- 收稿日期: 2021-11-19
- 修回日期: 2022-04-30
- 网络出版日期: 2022-03-05

Research on magnetic tracking and positioning technology for automatic driving in coal mine

YANG Li

CCTEG Beijing Huayu Engineering Company, Beijing 100120, China

摘要

摘要: 煤矿辅助运输车辆大多采用无线定位方式，动态定位精度为3 m以上，不能满足煤矿自动驾驶车辆定位精度的要求；车辆实时定位数据响应时间在400 ms以上，不能满足自动驾驶车辆对定位信息实时获取的要求。针对上述问题，提出了一种煤矿自动驾驶磁寻迹定位技术。在辅助运输自动驾驶车辆的合适位置安装磁感应天线装置，在车辆行驶路线上布置数个带有编号的无源感应磁钉，当感应天线经过无源感应磁钉时，无源感应磁钉受感应天线磁场的作用产生脉冲信号，该脉冲信号发生的位置在磁感应天线磁场范围内的具体位置可实时获取，磁感应天线将定位信息通过CAN总线通信接口转发给车辆控制系统，控制系统根据磁感应天线中心点与磁感应磁钉的相对位置，通过批通知树（BIT*）算法计算出车辆所在巷道位置和行驶路线中心的偏差位置，从而达到定位寻迹的目的。为验证该磁寻迹定位技术的有效性，在陕煤集团神木张家峁煤矿进行了工业性试验：在常规路段采用单排等间距布置磁钉；在井口、弯道和车辆行驶路线的终点前后处，根据不同的应用需求采用5排4磁钉和2排5磁钉相结合的方案布置无源感应磁钉，实现了自动驾驶车辆毫米级高精度、毫秒级低延时、有效的寻迹定位，使自动驾驶车辆按照最优路径准确行驶至终点。
- 煤矿辅助运输车辆 /
- 自动驾驶 /
- 磁寻迹定位 /
- 磁钉 /
- 磁感应天线
Abstract: Most auxiliary transportation vehicles in coal mine adopt wireless positioning method, and the dynamic positioning precision is more than 3 m. This method can not meet the requirements of automatic driving vehicles positioning precision in coal mine. The response time of real-time vehicle positioning data is more than 400 ms, which cannot meet the requirements of automatic driving vehicles for real-time acquisition of positioning information. In order to solve the above problems, a magnetic tracking and positioning technology for automatic driving in coal mine is proposed. The magnetic induction antenna device is arranged at a suitable position of the automatic driving vehicle for auxiliary transportation. Several numbered passive induction magnetic nails are arranged on the vehicle driving route. When the induction antenna passes through the passive induction magnetic nails, the passive induction magnetic nails generate pulse signals under the action of the magnetic field of the induction antenna. The specific position of the pulse signal generation position within the magnetic field range of the magnetic induction antenna can be obtained in real time. The positioning information is forwarded by the magnetic induction antenna to vehicle control system through the CAN bus communication interface. According to the relative position of the center point of the magnetic induction antenna and the passive induction magnetic nail, the control system calculates the deviation position between the position of the vehicle's roadway and the center of the driving route through the batch informed tree (BIT*) algorithm. Therefore, the purpose of positioning and tracking is achieved. In order to verify the effectiveness of the magnetic tracking and positioning technology, an industrial test is carried out in Shenmu Zhangjiamao Coal Mine of Shaanxi Coal Group. Magnetic nails are arranged in a single row with equal spacing in conventional sections. According to different application requirements, the combination of 5 rows of 4 magnetic nails and 2 rows of 5 magnetic nails is used to arrange passive induction magnetic nails in mine well,roadway turn and before and after destination of vehicles route. This method realizes the millimeter-level high precision, millisecond-level low latency, and effective tracking and positioning of the automatic driving vehicle. And it enables the automatic driving vehicle to accurately drive to the destination according to the optimal path.
- coal mine auxiliary transportation vehicles /
- automatic driving /
- magnetic tracking and positioning /
- magnetic nail /
- magnetic induction antenna

HTML全文

图 1 磁寻迹定位技术原理

Figure 1. Magnetic tracking and positioning technologyprinciple

下载: 全尺寸图片幻灯片

图 2 磁寻迹定位流程

Figure 2. Magnetic tracking and positioning process

下载: 全尺寸图片幻灯片

图 3 磁寻迹路径搜索过程

Figure 3. Magnetic tracking path search process

下载: 全尺寸图片幻灯片

图 4 磁钉具体布置

Figure 4. Specific arrangement of magnetic nails

下载: 全尺寸图片幻灯片

参考文献(13)

[1]	王国法,杜毅博. 智慧煤矿与智能化开采技术的发展方向[J]. 煤炭科学技术,2019,47(1):1-10. WANG Guofa,DU Yibo. Development direction of intelligent coal mine and intelligent mining technology[J]. Coal Science and Technology,2019,47(1):1-10.
[2]	王国法,赵国瑞,任怀伟. 智慧煤矿与智能化开采关键核心技术分析[J]. 煤炭学报,2019,44(1):34-41. WANG Guofa,ZHAO Guorui,REN Huaiwei. Analysis on key technologies of intelligent coal mine and intelligent mining[J]. Journal of China Coal Society,2019,44(1):34-41.
[3]	张彦禄,高英,樊运平,等. 煤矿井下辅助运输的现状与展望[J]. 矿山机械,2011,39(10):6-9. ZHANG Yanlu,GAO Ying,FAN Yunping,et al. Current situation and prospects of underground auxiliary transportation in collieries[J]. Mining & Processing Equipment,2011,39(10):6-9.
[4]	MEYER-EBERLING J, ROTH M. Method for estimating the range of amotor vehicle: US12915137[P]. 2011-05-12.
[5]	鲍文亮. 基于特征地图的煤矿辅助运输车辆定位方法[J]. 煤炭科学技术,2020,48(5):115-119. BAO Wenliang. Localization method for auxiliary transport vehicles of coal mine based on feature map[J]. Coal Science and Technology,2020,48(5):115-119.
[6]	KESSELS J, ROSCA B, BERGVELD H J. On-line battery identification for electric driving range prediction[C]//2011 IEEE Vehicle Power and Propulsion Conference（VPPC）, Chigago, 2011: 1-6.
[7]	王烁. 煤矿用无轨胶轮车发展现状与展望[J]. 煤炭与化工,2016,39(5):22-24. WANG Shuo. Development and outlook of mine trackless tyred vehicle[J]. Coal and Chemical Industry,2016,39(5):22-24.
[8]	PANDIT S B, KSHATRIYA T K, VAIDYA V G. Motor assistance for a hybrid vehicle based on predicted driving range: US2011008739-0A1[P].2011-02-14.
[9]	袁晓明. 煤矿电动无轨运输车辆的关键技术研究[J]. 煤炭科学技术,2011,39(5):80-82. YUAN Xiaoming. Research on key technology of mine electric trackless transportation vehicle[J]. Coal Science and Technology,2011,39(5):80-82.
[10]	王国法,庞义辉,任怀伟. 煤矿智能化开采模式与技术路径[J]. 采矿与岩层控制工程学报,2020,2(1):1-15. WANG Guofa,PANG Yihui,REN Huaiwei. Intelligent coal mining pattern and technological path[J]. Journal of Mining and Strata Control Engineering,2020,2(1):1-15.
[11]	张立宽. 改革开放40年我国煤炭工业实现三大科技革命[J]. 中国能源,2018,40(12):9-13. doi: 10.3969/j.issn.1003-2355.2018.12.002 ZHANG Likuan. China's coal industry realizes three scientific revolutions during the past 40 years[J]. Energy of China,2018,40(12):9-13. doi: 10.3969/j.issn.1003-2355.2018.12.002
[12]	赵浩, 毛开江, 曲业明, 等. 我国露天煤矿无人驾驶及新能源卡车发展现状与关键技术[J]. 中国煤炭, 2021, 47（4）: 45-50. ZHAO Hao, MAO Kaijiang, QU Yeming, et al. Development status and key technology of driverless and new energy trucks in open-pit coal mine in China [J] China Coal, 2021, 47（4）: 45-50.
[13]	张智,张磊,苏丽,等. 基于人工离线特征库的室内机器人双目定位[J]. 哈尔滨工程大学学报,2017,38(12):1906-1914. ZHANG Zhi,ZHANG Lei,SU Li,et al. Binocular localization of indoor robot based on artificial offline feature-database[J]. Journal of Harbin Engineering University,2017,38(12):1906-1914.