摘要
钢结构的异常变形或局部损坏可通过荷载_挠度曲线以及纵轴线的挠度曲线反映出来。利用数字摄影测量方法进行钢结构的变形监测是传统测量方式的变革 ,可实现半自动的实时监测。本文介绍了相应的测量方法并给出了实验结果。
The load_bend curve and vertical axis curve express the unusual deformation or part destroy of steel structure.The digital photogrammetry method used to monitor the deformation of steel structures is an innovation of tradition surveying method. In order to prove the feasibility of using digital photogrammetry method in monitoring the deformation of steal structures,an experiment was conducted as follows.First,26 circle signs were averagely placed on the testing steel frame which was made in one tenth size of the real one.Second,a pressure experiment for the testing steel frame was conducted with 200t hydraulic machine.A series of images were taken from the vertical side at pressing status and bowed point status.Then the images were transmitted to the computer.Third,we process the images.The coordinates of each sign were acquired.Finally,the deformation of the steel structure could be analyzed. During image processing,we got the binary image and traced the edge's point.We detected and extracted the circle in the binary image.Each circle has just one horizontal symmetrical axis and one vertical symmetrical axis.The crossing point of the horizontal symmetrical axis and the vertical symmetrical axis is the circle centre.All possible horizontal and vertical axis can be extracted in the image.All the pixel symmetric to one pair axis could be grouped into one subimage,Thus all the isolated points,lines,and other irregular curves are removed at this stage. We got the image's coordinates of A and B at every load.The coordinates were horizontally moved,rotated,shrunk and enlarged.They became a series of coordinates of the same direction based on the left under side corner point as zero.The method mentioned above can achieve semiautomatic real_time monitor deformation.This paper introduces the surveying method,and presents the result of experiments.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2001年第3期256-260,共5页
Geomatics and Information Science of Wuhan University
基金
山东省科委科技计划资助!项目 (9812 0 6 30 3)