|本期目录/Table of Contents|

[1]余修武,张可,周利兴,等.基于误差修正距离约束的深井巷道目标定位算法[J].中国安全生产科学技术,2017,13(5):68-72.[doi:10.11731/j.issn.1673-193x.2017.05.011]
 YU Xiuwu,ZHANG Ke,ZHOU Lixing,et al.Study on target location algorithm of deep mine roadway with distance constraint based on error correction[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2017,13(5):68-72.[doi:10.11731/j.issn.1673-193x.2017.05.011]
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基于误差修正距离约束的深井巷道目标定位算法
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
13
期数:
2017年5期
页码:
68-72
栏目:
现代职业安全卫生管理与技术
出版日期:
2017-05-31

文章信息/Info

Title:
Study on target location algorithm of deep mine roadway with distance constraint based on error correction
文章编号:
1673-193X(2017)-05-0068-05
作者:
余修武12张可1周利兴12张枫12胡沐芳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.中钢集团马鞍山矿山研究院有限公司 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 ZHANG Ke1 ZHOU Lixing12 ZHANG Feng12 HU Mufang1 LIU Qin1
1. Environmental Protection and Safety Engineering Institute, University of South China, Hengyang Hunan 421001, China; 2. State Key Laboratory of Safety and Health for Metal Mines, Sinosteel Maanshan Institute of Mining Research Co., Ltd., Maanshan Anhui 243000, China
关键词:
无线传感器网络深井定位接收信号强度指示距离约束误差修正
Keywords:
WSN location of deep mine RSSI distance constraint error correction
分类号:
TP301.6;X936
DOI:
10.11731/j.issn.1673-193x.2017.05.011
文献标志码:
A
摘要:
针对基于距离约束的井下定位算法本身存在的近似误差,尤其在锚点附近定位误差较大的问题,通过改进算法,引入1个误差系数ω,并以此为依据,来选取误差较小的边作为定位信息来源,同时引入修正系数ε来进行修正分割点,使其更加接近于垂足,以此来减少定位的误差。仿真结果表明:改进算法的平均定位误差远小于原定位算法,约为1/4;改进算法的最大误差小于1.5 m、最小误差为0.2 m;改进算法不仅定位精度优于原定位算法,且计算复杂度较低,更加适用于深井环境定位。
Abstract:
Aiming at the problem of approximation error in underground target location algorithm based on distance constraint, especially the large location error around the anchor point, an error coefficient ω was introduced to improve the algorithm. On this basis, the edges with smaller error were selected as the information source of location. Meanwhile, a correction coefficient ε was introduced to correct the division point, which made it closer to the foot of perpendicular, so as to reduce the location error. The simulation results showed that the average location error of the improved algorithm was much less than the original location algorithm, about 1/4 times. The maximum error of the improved algorithm was less than 1.5 m, and the minimum error was 0.2 m. The improved algorithm has a better location accuracy than the original location algorithm, with a lower computation complexity, so it's more suitable for the location in deep mine environment.

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备注/Memo

备注/Memo:
金属矿山安全与健康国家重点实验室开放基金项目(2016-JSKSSYS-04);江西省自然科学基金(20122BAB201050);南华大学环境与安全工程学院研究生创新课题(2017YCXXM08)
更新日期/Last Update: 2017-06-09