一种改进的无线传感器网络DV￣Hop定位算法在煤矿井下漏电事故中的应用∗

摘要

The location of leakage fault is an important topic of power system protection in the real￣time monitoring of transmission lines of coal mine. An improved DV￣Hop localization algorithm is proposed in order to solve the problem of inaccurate localization for wireless sensor networks in the underground coal mine. Firstly,by calculating the triangle area of anchor nodes to eliminate the anchor node group of which the area is tiny. Then,a beacon node optimization is followed to eliminate the beacon nodes which are approximately in a line. Besides,the Genetic Chaos Particle Swarm Optimization algorithm was proposed based on the particle swarm optimization algorithm which com￣bine with genetic algorithms and chaos. Finally,the improved particle swarm optimization was used to correct the lo￣cation of DV￣Hop algorithm. The results from simulation show that the proposed improved algorithm has better loca￣ting performance in positioning accuracy than the traditional DV￣Hop algorithm in the same network environment. Therefore,the location of leakage can be monitored more accurately in the coal mine.%煤矿井下输电线路的实时监测中，漏电故障定位是供电系统保护的重要研究课题。针对井下无线传感器网络定位算法存在不准确的问题，提出了一种改进DV￣Hop节点定位算法。首先通过计算锚节点组成的三角形面积，排除面积极小的锚节点组，避免锚节点近似共线的情况，完成了锚节点的优选方案；此外在粒子群算法的基础上结合遗传算法和混沌理论，提出了一种遗传混沌粒子群优化算法；最后利用改进的粒子群算法对DV￣Hop算法定位得到的节点位置进行校正。经过仿真实验表明在相同的网络环境下，与传统DV￣Hop算法相比，改进算法能够更有效地提高定位精度，从而更加准确地监测到煤矿井下漏电事故位置。