基于WSN的井下巷道定位算法研究

发布时间：2018-04-15 15:29

本文选题：WSN(Wireless + Sensor　；参考：《山东科技大学》2017年硕士论文

【摘要】：煤矿作为国民经济的命脉之一,是社会发展重要的推动力,但煤矿事故的频发成为困扰民众安全和行业发展的难题。由于煤矿井下环境的特殊性,井下作业人员随时面临危险,当灾难发生的时候,准确的井下人员信息是救援成功的先决条件。课题来源于山东省自然科学基金项目“井下自组织传感器网络的身份认证及组网技术”。本课题以煤矿井下巷道内庞大的通讯网络为环境支撑,探讨了巷道内几种常见的定位算法的适用性及优缺点,并在此基础上提出了一种井下巷道匹配定位算法,主要研究内容如下:1.论文比较了几种常见的无线传感器网络定位算法,对其原理和实现方法等进行了较为详细的分析,并探讨了指纹定位算法的特点。论文对井下巷道内的定位算法的分析,为后续的井下定位算法的提出奠定了基础。2.基于应用需求分析,论文研究了井下定位的电磁环境特征,分析了多径效应对井下电磁波传输的影响。论文通过对WSN的结构的分析,探讨了影响定位算法精度的因素。3.论文提出了一种适用于井下巷道复杂环境的定位算法,该算法包括两个阶段,即建库阶段和实时定位阶段。在建库阶段,该算法为了解决建库不准确、复杂度高等问题,采用基于分类迭代的方法,利用采集的大量训练库原始数据矢量,选取多个典型中心点的矢量构成矢量集,进而建立精确的数据矢量库;在实时定位阶段,将移动节点实时采集到的环境电磁数据矢量与矢量库中各典型矢量进行匹配运算,找出与实时矢量最为相近的库矢量,查询该库矢量对应的点坐标,获得定位结果。然后针对不同定位点的定位信息相似的问题,根据电磁波的传播特性和井下实际的生产常识,提出了速度限制位置的方法,对定位结果进行进一步的处理。4.最后,论文基于井下匹配定位算法的基础上,模拟井下巷道定位环境,采集样本信息,建立数据矢量库,对移动节点进行定位。通过对传统经典的RSSI定位算法、井下指纹定位算法与本文提出的井下匹配定位算法的仿真对比得出结论:井下匹配定位算法能够提高巷道内对目标节点的定位精度,满足了井下实际生产中的安全要求。
[Abstract]:As one of the lifeblood of the national economy, coal mine is an important driving force for social development, but the frequent occurrence of coal mine accidents has become a difficult problem for the safety of the people and the development of the industry.Due to the particularity of the underground environment, the underground operators are faced with danger at any time. When the disaster occurs, accurate underground personnel information is a prerequisite for successful rescue.The subject comes from Shandong natural science foundation project "identity authentication and networking technology of underground self-organizing sensor network".Based on the huge communication network in underground roadway, this paper discusses the applicability, advantages and disadvantages of several common localization algorithms in roadway, and puts forward a matching localization algorithm for underground roadway.The main research contents are as follows: 1.This paper compares several common wireless sensor network localization algorithms, analyzes its principle and implementation methods in detail, and discusses the characteristics of fingerprint location algorithm.This paper analyzes the localization algorithm in underground roadway, which lays a foundation for further underground localization algorithm.Based on the application requirement analysis, the paper studies the electromagnetic environment characteristics of downhole positioning, and analyzes the influence of multipath effect on underground electromagnetic wave transmission.By analyzing the structure of WSN, this paper discusses the factors that affect the accuracy of the localization algorithm.In this paper, a localization algorithm for complex underground tunnel environment is proposed. The algorithm consists of two stages, namely, the stage of building database and the stage of real-time location.In order to solve the problems of inaccuracy and high complexity in building the database, the algorithm adopts the method based on classification iteration, uses a large number of original data vectors collected from the training database, and selects the vectors of several typical center points to form the vector set.Then the accurate data vector library is established, and in the real-time positioning stage, the environment electromagnetic data vector collected by the mobile node is matched with each typical vector in the vector library, and the library vector that is most close to the real-time vector is found out.The point coordinates corresponding to the library vector are queried and the location results are obtained.Then, aiming at the problem of similar location information of different positioning points, according to the propagation characteristics of electromagnetic wave and practical production common sense of underground, the method of velocity limiting position is put forward, and the location result is further processed. 4.Finally, based on the algorithm of underground matching location, this paper simulates the location environment of underground roadway, collects the sample information, establishes the data vector database, and locates the mobile nodes.By comparing the traditional RSSI localization algorithm, the fingerprint location algorithm and the matching algorithm proposed in this paper, it is concluded that the underground matching algorithm can improve the positioning accuracy of the target nodes in the roadway.Meet the safety requirements of downhole production.
【学位授予单位】：山东科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5;TP212.9

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