传感技术学报
傳感技術學報
전감기술학보
Journal of Transduction Technology
2014年
10期
1431-1436
,共6页
无线传感器网络%故障定位%DV-Hop算法%混沌%遗传算法%粒子群优化算法
無線傳感器網絡%故障定位%DV-Hop算法%混沌%遺傳算法%粒子群優化算法
무선전감기망락%고장정위%DV-Hop산법%혼돈%유전산법%입자군우화산법
wireless sensor network%fault location%DV ̄Hop%chaos%genetic algorithm%particle swarm optimization algorithm
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。
煤礦井下輸電線路的實時鑑測中,漏電故障定位是供電繫統保護的重要研究課題。針對井下無線傳感器網絡定位算法存在不準確的問題,提齣瞭一種改進DV ̄Hop節點定位算法。首先通過計算錨節點組成的三角形麵積,排除麵積極小的錨節點組,避免錨節點近似共線的情況,完成瞭錨節點的優選方案;此外在粒子群算法的基礎上結閤遺傳算法和混沌理論,提齣瞭一種遺傳混沌粒子群優化算法;最後利用改進的粒子群算法對DV ̄Hop算法定位得到的節點位置進行校正。經過倣真實驗錶明在相同的網絡環境下,與傳統DV ̄Hop算法相比,改進算法能夠更有效地提高定位精度,從而更加準確地鑑測到煤礦井下漏電事故位置。
매광정하수전선로적실시감측중,루전고장정위시공전계통보호적중요연구과제。침대정하무선전감기망락정위산법존재불준학적문제,제출료일충개진DV ̄Hop절점정위산법。수선통과계산묘절점조성적삼각형면적,배제면적겁소적묘절점조,피면묘절점근사공선적정황,완성료묘절점적우선방안;차외재입자군산법적기출상결합유전산법화혼돈이론,제출료일충유전혼돈입자군우화산법;최후이용개진적입자군산법대DV ̄Hop산법정위득도적절점위치진행교정。경과방진실험표명재상동적망락배경하,여전통DV ̄Hop산법상비,개진산법능구경유효지제고정위정도,종이경가준학지감측도매광정하루전사고위치。
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.