基于GNSS的建筑塔机垂直度全圆智能检测
作者:
作者单位:

北京建筑大学测绘与城市空间信息学院,北京,102616

作者简介:

通讯作者:

基金项目:

国家重点研发计划(2017YFB0503700)资助项目;北京市教委科技计划一般项目(SQKM201710016005)资助项目。


GNSS-Based Verticality Intelligent Detection in Rounds for Construction Tower Crane
Author:
Affiliation:

School of Geomatrics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    鉴于传统经纬仪测量方法检测塔机垂直度存在诸多弊端,提出一种基于全球卫星导航系统(Global navigation satellite system,GNSS)的建筑塔机垂直度全圆智能检测技术。基于GNSS的动态检测模型,设计一种建筑塔机垂直度全圆智能检测方法,并基于Visual Studio 2017平台,利用C#编程语言,设计并开发一种基于GNSS的建筑塔机垂直度全圆智能检测系统(GNSS-based verticality intelligent detection system in rounds, GNSS_VDS)。实验结果表明:GNSS_VDS系统全圆智能检测水平精度优于3 cm、高程精度优于4 cm,本文算法是行之有效的,可为建筑塔机抗倾翻稳定性实时监测提供一种高精度智能化解决方案。

    Abstract:

    In view of the disadvantages of the traditional theodolite surveying method applied to verticality detection for construction tower crane, a global navigation satellite system (GNSS) based verticality intelligent detection technique in rounds for construction tower crane is proposed. And then, a verticality intelligent detection method in rounds for construction tower crane is designed based on GNSS dynamic detection model and the GNSS-based verticality intelligent detection system in rounds (GNSS_VDS) is designed and developed based on Visual Studio 2017 platform using C# program language. The preliminary experimental results show that the accuracy of intelligent detection in rounds of GNSS_VDS system is better than 3 cm in the horizontal direction and 4 cm in the vertical direction, verifying the effectiveness of the proposed algorithm. The high-precision intelligent solution can be provided for real-time monitoring of anti-toppling stability for construction tower crane.

    参考文献
    相似文献
    引证文献
引用本文

周命端,马博泓,鲍宏伟,师佳艺,罗德安.基于GNSS的建筑塔机垂直度全圆智能检测[J].数据采集与处理,2020,35(2):223-230

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
历史
  • 收稿日期:2019-12-30
  • 最后修改日期:2020-02-10
  • 录用日期:
  • 在线发布日期: 2020-03-25