基于光纤传感的物联网节点定位技术研究

Research on IoT Node Position Technology based on Fiber Sensing

基于光纤传感的物联网(IoT)具有测量感知与数据传输的双重特性,为了实现网络内任意节点的快速定位,文章研究了快速节点定位技术,该技术采用边界盒定位的方法优化了人工蜂群(ABC)算法。实验对光纤传感网络中的多个未知节点进行定位分析,并将所提算法、未优化的ABC算法和传统粒子群(PSO)算法的测试结果进行了对比。实验结果表明,随着种群数的增加,3种算法的定位精度都会提高,当种群数>20后趋于稳定,定位精度依次为2.2、3.0和3.3 m。由达到稳定的迭代次数和定位精度上下限可知,所提算法的收敛速度和定位稳定性均优于后两种算法。由此可见,基于所提算法的定位技术更适用于光纤传感IoT的节点定位应用。

The Internet of Things(IoT)of fiber-optic sensing has the characteristics of measurement perception and data transmission.In order to realize the fast positioning of any node in the network,a fast node positioning technology is investigated,which uses the method of boundary box optimizing the Artificial Bee Colony(ABC)algorithm.Experiments are performed on multiple unknown nodes in fiber-optic sensor networks.The performances of the proposed algorithm,the unoptimized ABC algorithm and the traditional Particle Swarm Optimization(PSO)algorithm are compared.The results show that as the population increases,the positioning accuracy of the three algorithms improves.When the population is greater than 20,it will stabilize,and the positioning accuracy is 2.2,3.0 and 3.3 m,respectively.It can be known from the number of iterations and positioning accuracy interval that the convergence speed and positioning stability of this algorithm are better than the latter two algorithms.It can be seen that the positioning technology based on this algorithm is more suitable for node positioning applications of the optical fiber sensing IoT.