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Application Of Total Station Scanner Technology In Geometric Quality Inspection Of Steel Structure

Posted on:2019-09-30Degree:MasterType:Thesis
Country:ChinaCandidate:M LiFull Text:PDF
GTID:2392330545499027Subject:Structure engineering
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As the steel structure buildings of our country are developing to super high-rise,large spans,and novel designs at present,these large and complex streel structures are made in segmental prefabricated components,and then complete the construction in the field.In order to ensure the construction quality and smooth installation,the geometric quality inspection of steel components(lifting units)required by stages should be carried out.The traditional single point measurement method has some defects in application,which is difficult to meet the requirements of modern engineering construction.With the rapid development of 3D point cloud technology,new technical can be used in geometric quality inspection of steel structure.In this paper,the high precision total station scanning technology is applied to the solid information collection of steel structure.In order to achieve the purpose of geometric quality inspection,the total station scanning technology precision analysis,steel structure point cloud acquisition and denoising,point cloud data regular surface fitting,three-dimensional coordinate transformation and virtual trial assembly error analysis are studied in the following aspects:(1)As a new technology,it is necessary to carry out theoretical analysis and experimental verification on the observation accuracy of total station scanning technology.In this paper,the accuracy of measurement point based on resection and the accuracy of plane reconstruction of point cloud data are analyzed.The results show that the accuracy of planar reconstruction can reach to 1.2mm by total station scanning technology,which can meet the requirements of geometric quality inspection of steel structure.At the same time,the influence of scanning distance and scanning incidence angle on the accuracy of steel structure plane reconstruction is analyzed.(2)Aiming at the problem of rule surface fitting of point cloud data,the algorithms of least square estimation,total least square estimation,mixed total least square and least square estimation and iterative fitting of weight selection are studied.An improved iterative fitting algorithm is proposed and applied to the fitting of plane,spherical and cylindrical surfaces.Considering the simulation results of various factors,a series of experiment are designed.The results show that the improved weighted iterative fitting algorithm is superior to the other algorithms mentioned above.(3)In order to solve the problem of three-dimensional coordinate transformation involved in geometric quality inspection of steel structure,three-dimensional coordinate transformation based on unit four element number is mainly studied.The method is applicable to three-dimensional coordinate transformation of steel structure at any angle.In this paper,a direct solution algorithm of coordinate transformation parameters based on unit four element number is derived,and the coordinate conversion program is compiled based on it.The simulation results show that the program can solve the coordinate transformation parameters at any rotation angle.(4)Taking Zhuhai Hengqin steel structure project as an example,two lifting units on site are selected as the research objects to geometric quality inspect.Through scanning scheme design,point cloud data acquisition,point cloud de-noising processing,plane and cylindrical surface fitting,measured key point acquisition,three-dimensional coordinate conversion,key point position measurement coordinate and design coordinate deviation analysis,the manufacturing deviation of the hoisting unit are mastered.According to the statistical analysis of position error of the key points,the two lifting units are qualified.
Keywords/Search Tags:Steel structure, Geometric quality inspection, Total station scanner technology, Point position accuracy, Rule surface fitting of point cloud data, Threedimensional coordinate transformation
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