The application of direct linear transformation based on the neural network in geo-mechanics model test
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The application of direct linear transformation based on the neural network in geo-mechanics model test
Vol. 29, Issue 4, (2008)
作者机构:
1. 山东大学 土建与水利工程学院,济南,250061
2. 山东大学 岩土与结构工程研究中心,济南,250061
作者简介:
基金信息:
DOI:
CLC:TB115
Online First:10 July 2013,
Published:2008
稿件说明:
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CHEN Ji-guang, ZHANG Qiang-yong, LI Shu-cai, et al. The application of direct linear transformation based on the neural network in geo-mechanics model test[J]. 2008, 29(4).
DOI:
CHEN Ji-guang, ZHANG Qiang-yong, LI Shu-cai, et al. The application of direct linear transformation based on the neural network in geo-mechanics model test[J]. 2008, 29(4).DOI:
The application of direct linear transformation based on the neural network in geo-mechanics model test
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 ? 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