基于WSN的公路隧道车辆监测定位系统研究

发布时间：2018-03-24 19:17

本文选题：公路隧道　切入点：WSN　出处：《长安大学》2014年硕士论文

【摘要】：针对目前公路隧道消防监控系统无法有效进行事故预警，事故发生后无法准确获知事故地点及现场状况，本文研究并设计了一种基于WSN的隧道车辆监测定位系统，旨在实时监测隧道内车辆的运行状态该系统可对危险品运输车辆进行重点监控，预警因载有危险品的车辆出现意外而引起的恶性事故，也可实时监测隧道内交通状况，当事故发生时，，可通过该系统精确定位事故发生地点并了解现场交通状况，也可跟进了解救援状况，为救援工作的顺利进行提供可靠的情报基础，实现对公路隧道的综合监控本文研究搭建了基于Zigbee技术的WSN，首先分析了电磁波在隧道空间中的传递机制和特性，根据电波在隧道内的场强分布对其传播区域进行了划分，并依据Fresnel区域理论验证了隧道近场区电磁波传输特性符合自由空间模型的结论，在此基础上利用T-R场强函数推导出RSSI-D模型，并根据隧道环境采集大量数据拟合出基于RSSI的测距函数；之后，针对常用定位算法的缺陷，并结合隧道环境，提出一种基于RSSI-APIT的整合算法以提高系统定位性能；最后，根据隧道现有机电系统的状况，从整体上研究了系统框架，并结合设计算法，提出了一种等腰梯形子定位网络的节点布设方式，同时对系统硬件平台的搭建及各类节点的主要软件模块设计进行了研究经过对本系统建立数学模型，模拟节点分布，对系统定位精度进行了多次仿真，定位误差在3%~6%之间波动，且主要集中在车辆行进方向，能够基本满足定位要求该系统可融入隧道现有的通信监控系统，作为隧道机电系统的一个子系统，实现对隧道内车辆的定位追踪，实时监控潜在的危险因素，对现有的监控消防预警系统进行完善，实现事故预警监测定位及事故救援的远程跟进，方便隧道事故处理策略的及时调整，在隧道管理方面具有一定的应用价值
[Abstract]:In view of the current highway tunnel fire monitoring system can not effectively carry out the accident early warning, after the accident can not accurately know the accident location and the scene situation, this paper studies and designs a tunnel vehicle monitoring and positioning system based on WSN. The system can monitor the traffic condition of dangerous goods transport vehicles in real time. The system can warn of serious accidents caused by accidents of vehicles carrying dangerous goods, and can also monitor traffic conditions in tunnels in real time. When the accident occurs, the system can accurately locate the location of the accident and understand the traffic situation on the spot. It can also follow up and understand the rescue situation, which can provide a reliable information basis for the smooth operation of the rescue work and realize the comprehensive monitoring of the highway tunnel. Firstly, the transmission mechanism and characteristics of electromagnetic waves in tunnel space are analyzed, and the propagation regions are divided according to the distribution of electric waves in the tunnel. Based on the theory of Fresnel region, the conclusion that the electromagnetic wave propagation in the near field of tunnel conforms to the free space model is verified. Based on this, the RSSI-D model is derived by using T-R field intensity function. And according to the tunnel environment to collect a large number of data fitting out the location function based on RSSI. Then, aiming at the defects of common localization algorithms and combining the tunnel environment, an integrated algorithm based on RSSI-APIT is proposed to improve the positioning performance of the system. According to the existing mechanical and electrical system of the tunnel, the system framework is studied in the whole, and a node layout method of the isosceles trapezoidal positioning network is proposed in combination with the design algorithm. At the same time, the construction of the hardware platform and the design of the main software modules of all kinds of nodes are studied. After establishing the mathematical model of the system and simulating the distribution of nodes, the positioning accuracy of the system is simulated many times. The positioning error fluctuates between 3% and 6%, and it is mainly concentrated in the direction of the vehicle, which can basically meet the positioning requirements. The system can be integrated into the existing communication monitoring system of tunnel, as a subsystem of tunnel mechanical and electrical system, to realize the positioning and tracking of vehicles in the tunnel, to monitor the potential risk factors in real time, and to perfect the existing monitoring and fire alarm system. It can realize the accident early warning monitoring and positioning and the remote follow-up of accident rescue, facilitate the timely adjustment of tunnel accident handling strategy, and have certain application value in tunnel management.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495

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