矿井侦测无人机研究现状与发展趋势
转载 2020-07-25 10:58 工矿自动化 来源:工矿自动化原文发表在《工矿自动化》2020年第7期,欢迎品读。
矿井侦测无人机具有体积较小、造价低廉、无人员伤亡风险及灵活性强等优势,已在目标跟踪、应急通信和环境监测等多种领域得到广泛应用,它可进入井下巷道进行实时侦测,利用传感器对井下的瓦斯浓度、氧气浓度、环境温度及伤员位置等信息进行采集与处理,并将这些信息通过数据及视音频实时传输到救援指挥中心,为救援指挥人员提供决策依据。
本文通过分析矿井侦测无人机动力系统、定位系统、环境监测系统及通信系统等的国内外研究现状,指出了矿井侦测无人机存在续航能力不足、定位精度差、信息感知能力弱、信息数据传输性能差等问题,针对上述问题,展望了矿井侦测无人机的发展趋势:① 新能源或新型供电技术的应用。对整个电源管理系统进行更加高效合理的优化,实时侦测用电设备的耗电情况,提高用电的高效性,延长侦测无人机的续航时间,并满足防爆性能。② 基于协同导航搜索的无人机集群系统开发。采用混合式无人机集群控制结构,克服了分布式结构通信可靠性差、搜索效率低的缺点,解决了集中式结构鲁棒性及自主性弱的问题;通过数理优化算法进行信息推导,并对多无人机协同信息进行融合,提高定位精度,缩短救援时间。③ 基于多传感器融合技术的无人机监测平台设计。通过基于BP神经网络算法的多传感器信息协调及互相融合,提高无人机对井下环境的感知能力。④ 多无人机链状无线Mesh组网模式的应用。多无人机在井下环境搜索时,每架无人机采集的信息都是局部区域的信息,通过链状无线Mesh组网模式,所有无人机进行信息融合和资源互补,实时更新环境信息状况,提高侦测的可靠性和救援效率。
引用格式
张铎(1986-),男,陕西华阴人,讲师,硕士研究生导师,博士,主要研究方向为煤火灾害防治与灾害应急救援,E-mail:zhangd@xust.edu.cn。
作者联系方式
张铎,吴佩利,郑学召,等.矿井侦测无人机研究现状与发展趋势[J].工矿自动化,2020,46(7):76-81.
ZHANG Duo,WU Peili,ZHENG Xuezhao,et al.Research status and development trend of mine detection unmanned aerial vehicle[J].Industry and Mine Automation,2020,46(7):76-81.
责任编辑联系方式
张强,E-mail:zhangqiang@cari.com.cn
矿井侦测无人机研究现状与发展趋势
Research status and development trend of mine detection unmanned aerial vehicle
【作者】张铎1,2,吴佩利1,郑学召1,2,郭军1,2【Author】 ZHANG Duo1,2,WU Peili1,ZHENG Xuezhao1,2,GUO Jun1,2【作者机构】1.西安科技大学 安全科学与工程学院, 陕西 西安710054;2.国家矿山救援西安研究中心, 陕西 西安710054【Unit】1.College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China; 2.Xi'an Research Center of National Mine Rescue, Xi'an 710054, China
【摘要】通过分析矿井侦测无人机动力系统、定位系统、环境监测系统及通信系统等的国内外研究现状,指出了矿井侦测无人机存在续航能力不足、定位精度差、信息感知能力弱、信息数据传输性能差等问题。展望了矿井侦测无人机的发展趋势:① 新能源或新型供电技术的应用。对整个电源管理系统进行更加高效合理的优化,实时侦测用电设备的耗电情况,提高用电的高效性,延长侦测无人机的续航时间,并满足防爆性能。② 基于协同导航搜索的无人机集群系统开发。采用混合式无人机集群控制结构,克服了分布式结构通信可靠性差、搜索效率低的缺点,解决了集中式结构鲁棒性及自主性弱的问题;通过数理优化算法进行信息推导,并对多无人机协同信息进行融合,提高定位精度,缩短救援时间。③ 基于多传感器融合技术的无人机监测平台设计。通过基于BP神经网络算法的多传感器信息协调及互相融合,提高无人机对井下环境的感知能力。④ 多无人机链状无线Mesh组网模式的应用。多无人机在井下环境搜索时,每架无人机采集的信息都是局部区域的信息,通过链状无线Mesh组网模式,所有无人机进行信息融合和资源互补,实时更新环境信息状况,提高侦测的可靠性和救援效率。【Abstract】By analyzing research status of power system, positioning system, environmental monitoring system and communication system of mine detection unmanned aerial vehicle (UAV) at home and abroad, the problems of mine detection UAV were pointed out, such as insufficient cruising power, poor positioning accuracy, weak information perception ability and poor information data transmission performance. For the above problems, the development trends of mine detection UAV were prospected: ① Application of new energy or new power supply technology, the whole power management system is optimized in a more efficient and reasonable way to detect power consumption of electric equipment in real time, improve power efficiency and enhance endurance time of detection UAV, and meet explosion-proof performance. ② Development of UAV cluster system based on collaborative navigation search, the hybrid UAV cluster control structure overcomes the shortcomings of poor communication reliability and low search efficiency in distributed structure and solves the problems of weak robustness and autonomy in centralized structure; the system can improve the positioning accuracy and shorten the rescue time through mathematical optimization algorithm for information derivation and multi-UAV collaborative information fusion. ③ Design of UAV monitoring platform based on multi-sensor fusion technology, the multi-sensor information coordination and mutual fusion based on BP neural network algorithm can improve the UAV's perception ability to underground environment. ④ Application of multi-UAV chain wireless Mesh networking mode, when multi-UAVs search in underground environment, the information collected by each UAV is local area information, all UAVs conduct information fusion and resource complementarity to update the environmental information status in real time through the chain wireless Mesh networking mode, so as to improve reliability of detection and rescue efficiency.
【关键词】 矿井应急救援;侦测无人机;无人机集群;动力系统;定位导航;环境监测;无线通信;多传感器融合【Keywords】mine emergency rescue; detection unmanned aerial vehicle; unmanned aerial vehicle cluster; power system; positioning and navigation; environmental monitoring; wireless communication; multi-sensor fusion
【基金项目】国家重点研发计划重点专项项目(2018YFC0808201);国家自然科学基金项目(51904234);陕西省自然科学基础研究计划项目(2018JM5009,2018JQ5080)
信息提供:张强 图文编辑:张聚
审 核:王晖