期刊文献+

基于浮标漂移遥测的沉石移位估计方法研究

Research on Estimation Method of Anchorage Stone Displace Based on Buoy Drift Telemetry
下载PDF
导出
摘要 为了确定浮标沉石在极端条件下是否发生移位,需要结合浮标遥测定位信息和环境条件进行建模和分析.文中基于航标遥测数据,利用箱线图对数据进行处理.利用k-means算法求取聚类中心,作为计算浮标漂移量的基准点;分析相邻浮标在相同时间下的漂移运动特征,确定导致浮标漂移的主要原因并进行量化.通过BP神经网络预测航标漂移,并与极端条件发生后一段时间的浮标位置数据进行对比分析,判断沉石是否发生移位.结果表明该方法能够较好地判断浮标沉石的移位情况. To determine whether the buoy sinkhole will shift under extreme conditions,it is necessary to combine the buoy telemetry positioning information and environmental conditions for modeling and analysis.In this paper,based on the telemetering data of navigation mark,the box diagram was used to process the data.The clustering center was obtained by k-means algorithm as the reference point for calculating the float drift.By analyzing the drift characteristics of adjacent buoys at the same time,the main causes of buoy drift were determined and quantified.BP neural network was used to predict the drift of navigation mark,and it is compared with the buoy position data for a period of time after extreme conditions,so as to judge whether the sunken stone has shifted or not.The results show that this method can better judge the displacement of buoy sinking stone.
作者 李政 周春辉 陈刚 刘宗杨 赵俊男 LI Zheng;ZHOU Chunhui;CHEN Gang;LIU Zongyang;ZHAO Junnan(School of Navigation,Wuhan University of Technology,Wuhan 430063,China;Hubei Key Laboratory of Inland Shipping Technology,Wuhan 430063,China)
出处 《武汉理工大学学报(交通科学与工程版)》 2022年第2期340-344,共5页 Journal of Wuhan University of Technology(Transportation Science & Engineering)
基金 国家重点研发计划(2018YFC1407405)。
关键词 浮标 沉石移位 K-MEANS算法 BP神经网络 航海保障 buoy anchorage stone displace K-means algorithm BP neural network navigation support
  • 相关文献

参考文献8

二级参考文献18

共引文献40

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部