|本期目录/Table of Contents|

[1]余修武,胡沐芳,周利兴,等.基于阶次序列与凸规划的铀尾矿库监测定位算法[J].中国安全生产科学技术,2016,12(12):86-91.[doi:10.11731/j.issn.1673-193x.2016.12.015]
 YU Xiuwu,HU Mufang,ZHOU Lixing,et al.A localization algorithm of uranium tailings monitoring based on rank sequence and convex programming[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(12):86-91.[doi:10.11731/j.issn.1673-193x.2016.12.015]
点击复制

基于阶次序列与凸规划的铀尾矿库监测定位算法
分享到:

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
12
期数:
2016年12期
页码:
86-91
栏目:
现代职业安全卫生管理与技术
出版日期:
2016-12-30

文章信息/Info

Title:
A localization algorithm of uranium tailings monitoring based on rank sequence and convex programming
文章编号:
1673-193X(2016)-12-0086-06
作者:
余修武12胡沐芳1周利兴12张可1刘琴1
1.南华大学 环境保护与安全工程学院,湖南 衡阳 421001; 2.金属矿山安全与健康国家重点实验室,安徽 马鞍山 243000)
Author(s):
YU Xiuwu12 HU Mufang1 ZHOU Lixing12 ZHANG Ke1 LIU Qin1
(1. School of Environmental Protection and Safety Engineering, University of South China, Hengyang Hunan 421001, China; 2. State Key Laboratory of Safety and Health for Metal Mines, Maanshan Anhui 243000, China)
关键词:
WSN凸规划阶次序列子区域监测定位铀尾矿库
Keywords:
WSN convex programming rank sequence subregion monitoring and localization uranium tailings
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2016.12.015
文献标志码:
A
摘要:
在铀尾矿库放射性核素泄露污染WSN监测中,针对凸规划定位精度低的问题,提出一种基于阶次序列的凸规划定位算法。通过划分子区域缩小未知节点几何约束范围,建立各子区域的重心坐标到锚节点的阶次序列表,计算未知节点序列与序列表的相关度,并以最大相关度的子区域重心坐标为定位结果。使该改进算法满足低密度条件的定位并能减少其计算量提高定位精度。经过仿真,新算法较凸规划算法在定位精度上提高了14%。
Abstract:
For the WSN monitoring of radionuclide leakage and pollution in uranium tailings, aiming at the problem about low localization precision of convex programming, a convex programming localization algorithm based on rank sequence was put forward. The geometric constraint range of unknown node was reduced by dividing the subregion, and the rank sequence table of barycentric coordinate in each subregion to anchor node was established. The correlation degree of unknown node sequence and sequence table was calculated, and the barycentric coordinate of the subregion with the largest correlation degree was taken as the localization result. The improved algorithm can satisfy the localization under low density condition, reduce the amount of calculation, and increase the localization precision. Through the simulation, it showed that the localization precision of new algorithm increased by 14% compared with the convex programming algorithm.

参考文献/References:

[1]钱志鸿,孙大洋,LENG Victor.无线网络定位综述[J].计算机学报,2016,39(6) :1238-1256. QIAN Zhihong, SUN Dayang LEUN Victor.A survey on localization model in wireless networks[J].Chinese Journal of Computers,2016,39(6) :1238-1256.
[2]余修武, 范飞生, 李睿,等. 基于接收信号强度分区矿山无线定位算法[J].中国安全生产科学技术, 2015, 11(9):70-75. YU Xiuwu, FAN Feisheng, LI Rui, et al.Study on wireless positioning algorithm in mine based on received signal strength paritition[J].Journal of Safety Science and Technology, 2015, 11(9):70-75.
[3]余修武,周利兴,范飞生,等. 基于新内点测试与Grid-Scan的铀尾矿库监测定位算法[J]. 中国安全生产科学技术, 2016, 12(5):6-8. YU Xiuwu, ZHOU Lixing, FAN Feisheng, et al. A location algorithm for uranium tailings monitoring based on approved Point-In-Triangulation and Grid-Scan[J].Journal of Safety Science and Technology, 2016, 12(5):6-8.
[4]Mehrabi A, Kim K. Maximizing Data Collection Throughput on a Path in Energy Harvesting Sensor NetworksUsing a Mobile Sink[J]. IEEE Transactions on MobileComputing, 2016:690-704.
[5]韩睿松,杨维.一种基于SBL和APIT的混合定位算法[J].传感技术学报,2014,27(8):1095-1099. HAN Ruisong, YANG Wei.A hybrid localization algorihm bsed on SBL and APIT[J].Chinese Journal of sensors and Actuatiors,2014,27(8):1095-1099.
[6]裴忠民,邓志东,徐硕,等.一种基于N-最优阶次序列的无线传感器网络节点定位方法[J].自动化学报,2010, 36 (2) :199-207. PEI Zhongmin, DENG Zhidong, XU Shuo, et al.A new localization method for wireless sensor network nodes based on N-best rank sequence[J].Acta Automatica Sinica,2010, 36 (2) :199-207.
[7]张翰,刘锋.无线传感器网络基于凸规划的改进定位算法:Convex-PIT[J].传感技术学报,2007,20(5):1129-1133. ZHANG Han, LIU Feng.Optimized localization algorithm for wireless sensor netnwork based on Convex algorithm:convex PIT[J].Chinese Journal of sensors and Actuatiors,2007,20(5):1129-1133.
[8]Hsiao C C,Tfsai Y J. Node Deployment Strategy for WSN-Based Node-Sequence Localization[A]//Intelligent Sensors, Sensor Net-works and Information Processing(ISSNIP), 2011 Seventh lnternational Conference on.Piscataway[C]. IEEE,2011 :259-264.
[9]陈昌祥,达维,周洁.基于RSSI的无线传感器网络距离修正定位算法[J].通信技术,2011,44 (2) :65-66. CHEN Changxiang, DA Wei, ZHOU Jie.RSSI-based range collation localization algorithm in WSN[J].Communication Techology,2011,44(2):65-66.
[10]Li M D,Xiong w,Liang Q.An improved ABC-based node localization algorithm for wireless sensor networks[A]//Proceedings of International Conference on Wireless Com-municsRions, Networking and Mobile Computing( WICOM)[C],Shanghai,2012,12:1-4.
[11]杨玺,刘军,阎芳.基于序列加权的无线传感器网络定位算法[J].电子测量与仪器,2014,10(10):1155-1159. YANG Xi, LIU Jun, YAN Fang.Wireless sensor networks localization algorithm based on sequence weighting[J].Journal of Electronic Measurement and Instrumentation, 2014, 10(10): 1155-1159.
[12]向满天,罗嗣力,戴美思.无线传感器网络中一种改进的凸规划定位算法[J]. 传感技术学报, 2014,8(8): 1139-1142. XIANG Mantian, LUO Sili, DAI Meisi.An improved Con-vex localization algorithm in wireless sensor network[J].Chinese Journal of Sensors and Actuatiors,2014,8(8):1139-1142.
[13]韩江洪,祝满拳,马学森,等.基于RSSI的极大似然与加权质心混合定位算法[J].电子测量与仪器学报,2013, 27(10): 937-943. HAN Jianghong, ZHU Manquan, MA Xuesen, et al.Hybrid localization algorithm of maximum likelihood and weighted centroid based on RSSI[J].Journal of Electronic Measurement and Instrumentation,2013,27(10):937-943.
[14]胡敏.基于阶次序列加权的无线传感器定位算法[J].计算机工程与应用,2014, 50(10):116-119. HU Min. Node localization algorithm of wireless sensor networks based on optimal weighted rank sequences[J]. Computer Engineering and Applications, 2014, 50(10):116-119.
[15]胡伟,徐福缘.基于信标优化的无线传感网络定位算法研究[J].计算机工程与设计,2012,33(4):1324-1328. HU Wei,XU Fuyuan.Research of localization algorithm based on optimal beacon for wireless sensor networks[J].Computer Engineering and Design,2012,33(4):1324-1328.

相似文献/References:

[1]余修武,周利兴,范飞生,等.基于新内点测试与Grid-SCAN的铀尾矿库监测定位算法[J].中国安全生产科学技术,2016,12(5):5.[doi:10.11731/j.issn.1673-193x.2016.05.001]
 YU Xiuwu,ZHOU Lixing,FAN Feisheng,et al.A localization algorithm for uranium tailings monitoring based on new interior point test and Grid-SCAN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(12):5.[doi:10.11731/j.issn.1673-193x.2016.05.001]

备注/Memo

备注/Memo:
湖南省重点研发项目(2015SK2005);湖南省教育厅科研重点项目(15A161)
更新日期/Last Update: 2017-01-13