基于PSO改进算法的煤矿井下精确UWB技术研究  

Research on accurate UWB technology in coal mine based on improved PSO algorithm

作　　者：岳蕾 YUE Lei(Inner Mongolia Mengdong Energy Co.,Ltd.,Mindong No.1 Mine,Hulunbuir 021100,Inner Mongolia China)

机构地区：[1]内蒙古蒙东能源有限公司敏东一矿,内蒙古呼伦贝尔021100

出　　处：《粘接》2024年第10期129-132,共4页Adhesion

摘　　要：为提高煤矿井下定位精度,提出一种ADS-TWR测距和APSO改进Taylor级数的井下联合定位方法。采用非对称双边双程(ADS-TWR)作为基础的矿井下人员测距算法,使用改进的卡尔曼滤波算法对其进行改进;以Taylor级数法作为基础的矿井下人员定位算法,并以自适应权重粒子群算法(APSO)对其进行改进。结果表明,与使用传统卡尔曼滤波算法优化的ADS-TWR测距算法相比,基于改进卡尔曼滤波算法的ADS-TWR测距算法误差更小;与传统的Taylor级数定位算法及其他类型的定位算法相比,设计的AP⁃SO-Taylor定位算法稳定性更好,定位精度更高,误差始终稳定在60 cm以下。To improve the positioning accuracy of underground personnel in coal mines,a combined positioning method using ADS-TWR ranging and APSO improved Taylor series was proposed.The asymmetric bilateral two-way(ADS-TWR)was used as the basis for the underground personnel ranging algorithm,and the improved Kalman filter algorithm was used to improve it.The underground personnel positioning algorithm based on Taylor series method was improved with the Particle Swarm Optimization Algorithm Based on Adaptive Weight(APSO).The results showed that compared to the ADS-TWR ranging algorithm optimized using traditional Kalman filtering algorithm,the ADS-TWR ranging algorithm based on improved Kalman filtering algorithm had smaller error.Compared with tradi⁃tional Taylor series positioning algorithms and other types of positioning algorithms,the designed APSO-Taylor posi⁃tioning algorithm had better stability,higher positioning accuracy,and consistently stable errors below 60 cm.

关 键 词：煤矿井下 定位 UWB技术 TAYLOR级数法 PSO 

分 类 号：TP39[自动化与计算机技术—计算机应用技术] TD82-9[自动化与计算机技术—计算机科学与技术]