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基于智慧云的超高层建筑施工测控管理平台的研究 被引量:4

The Construction of Measurement and Management Platform for Super High-rise Building Based on Intelligent Cloud
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摘要 超高层建筑施工测控管理平台依托于云管理、云计算和智能分析,实现了超高层建筑的整体变形的自动化提取和表达、空间结构形态的精细化检测以及变形趋势的智慧预测。论文详细介绍了系统逻辑结构层次划分、系统功能的具体实现方法和核心技术。并结合在建的北京市第一高楼"中国尊"(528m)施工测控项目,完成了平台的应用研究与验证。该平台在超高层建筑施工的变形数据处理分析、主体结构检测和桁架卸载三维分析等方面应用效果良好,具备良好的数据处理、分析和管理能力。 With technology of cloud management,cloud computing and intelligent analysis,the platform of measure-ment and management of super high-rise building realizes the automatic extraction and expression of the overall de-formation of the super high-rise building,the refined detection of spatial structure morphology and the intelligent pre-diction of deformation trends.This paper introduces in detail the logical structure of the system,the hierarchical divi-sion,the concrete realization method and the core technology of the system function.Combined with the construction project of the China Zun(the first high-rise under construction in Beijing,528m),the application of research and ver-ification of the platform has been completed.The platform has good application effect in the deformation data pro-cessing analysis,monitoring of main structure and three-dimensional analysis of truss unloading in the super high-rise building construction,and has good data processing,analysis and management capabilities.
作者 邱冬炜 段明旭 丁克良 王彤 王来阳 QIU Dongwei;DUAN Mingxu;DING Keliang;WANG Tong;WANG Laiyang(Beijing University of Civil Engineering and Architecture,Beijing 102616,China)
机构地区 北京建筑大学
出处 《北京测绘》 2017年第2S期7-11,共5页 Beijing Surveying and Mapping
基金 国家重点研发计划(2017YFB0503700) 中国住房和城乡建设部科学技术项目(2015-K8-050)
关键词 超高层建筑 智慧云 测控管理平台 系统设计 变形监测 结构检测 the super high-rise building intelligent cloud measurement and management platform system design de-formation monitoring structure detection
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  • 1徐建新,张光伟,羌鑫林,蒋莹,高磊.激光测量采集车在城市部件调查中的应用[J].测绘与空间地理信息,2013,36(S1):237-239. 被引量:19
  • 2王晏民,郭明,王国利,赵有山,李玉敏,胡春梅.利用激光雷达技术制作古建筑正射影像图[J].北京建筑工程学院学报,2006,22(4):19-22. 被引量:32
  • 3李晖,吴禄慎.三维激光扫描技术在虚拟现实中的应用[J].南昌大学学报(工科版),2007,29(3):239-242. 被引量:16
  • 4王小川,史峰,郁磊,等.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社,2013.
  • 5Rumelhart D E, Hinton G E, Williams R J. Learning representations by back-propagating errors. Nature, 1986, 323: 533-536.
  • 6Hagan M T, Menhaj M B. Training feedforward networks with the marquardt algorithm. IEEE Trans Neural Netw, 1994, 5:989-993.
  • 7Wilamowski B M, Yu H. Neural network learning without backpropagation. IEEE Trans Neural Netw, 2010, 21: 1793-1803.
  • 8Chen S, Cowan C, Grant P. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Netw, 1991, 2:302-309.
  • 9Li K, Peng J X, Irwin G W. A fast nonlinear model identification method. IEEE Trans Automat Contr, 2005, 50: 1211-1216.
  • 10Hornik K. Approximation capabilities of multilayer feedforward networks. Neural netw, 1991, 4:251 257.

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