摘要
三维地质力学模型的变形数据主要由岩体内部变形和收敛变形两部分构成。寻找满足高精度位移测量的收敛变形观测方法已成为三维地质力学模型试验数据采集的重要研究方向。修正了传统的数码相机摄影测量基于图像坐标变换的计算思路,改善了试验中5×5小模板作业方式,采用大模板标准点布设方案和标志点相邻坐标数据点的选择方法,有效地减小了镜头畸变对标准点、标志点的影响。基于BP神经网络的直接线性变换原理进行了图像间的坐标识别和试验阶段测量观测点的坐标比较,实现了三维地质力学模型的收敛变形观测。将数码相机数字近景摄影方法应用于某大型分岔隧道的三维地质力学模型试验研究,取得了满意的研究成果。
The deformation date of 3D geo-mechanics model are composed of the internal deformation of rock mass and convergence deformation of boundaries. Searching the method of measuring the convergence deformation with high precision has been major direction of research in the area of data acquisition for 3D geo-mechanics model. In this paper, the calculation method based on the coordinates transformation of images in the traditional digital camera photogrammetry was revised the small template operation method of 5 x 5 was improved. Instead, the big templates with the layout of standard points was used and a method of selection for coordinate data of neighboring marked nods was designed, thus, the influence of lens distortion was reduced effectively. The direct linear transformation mechanism based on the BP neural network was used for coordinates recognition of images and comparison of coordinates of marked nods during experiment period. The measurement of convergence deformation for 3D geo-mechanics model was thus achieved. A 3D geo-mechanics model applying the close shot photographic technique of digital camera was set up for a large scale forked tunnels, the results of measurements were satisfactory.
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2008年第4期897-900,共4页
Rock and Soil Mechanics
基金
国家自然科学基金资助项目(No.40772173)
山东省自然科学基金资助项目(No.Y2007F52)
关键词
收敛变形
神经网络
直接线性变换
分岔隧道
三维地质力学模型试验
convergence deformation
neural network
direct linear substitution
bifurcation tunnels
3D geo-mechanics model test
