Tunnel three-dimensional geometric reconstruction method considering data-driven segment segmentation and model-driven segment assembly

Abstract

The invention provides a tunnel three-dimensional geometric reconstruction method considering data driving segment segmentation and model driving segment assembly. The method comprises the following steps: (1) a mapping method from tunnel three-dimensional point cloud expansion to a two-dimensional image; (2) a tunnel image segmentation method; and (3) tunnel segment reconstruction based on modelmatching. The invention provides a method for reconstructing a three-dimensional tunnel geometric model by coupling data and a model driving thought, which is used for reconstructing a multi-scale shield tunnel geometric model. Based on a data driving thought, firstly, point cloud is converted into a binary image, and then tunnel point cloud is segmented on a loop-by-loop scale and a segment scalerespectively by utilizing morphology and a template matching algorithm. The sealing grooves and the bolt holes between the segments are more obvious in the binary image, and the image itself also contains the mapping topological relation between the original point cloud and the pixels. Based on the observation that each ring of a tunnel only comprises one capping block; a segment segmentation problem is converted into a template matching problem based on least square constraint of a binary image; and then, based on the thought of model driving, the reconstruction problem of the shield tunnelsegment on the scale is converted into the matching problem of the segment point cloud and the model base, the types, sizes and positions of various segments are obtained, and assembling of the tunnelsegments is completed.

Description

technical field [0001] The invention relates to a tunnel three-dimensional geometric reconstruction method considering data-driven segment segmentation and model-driven segment assembly, and belongs to the technical field of laser radar remote sensing data intelligent processing and analysis. Background technique [0002] The subway tunnel is a public transportation system with a complex underground space structure. Due to the influence of comprehensive factors such as ground building loads, soil disturbance, and construction around the tunnel, the shape, size, or spatial position of the tunnel will change. At present, how to efficiently and Accurate monitoring of subway tunnel deformation is a hot and difficult issue in underground engineering research. Traditional tunnel deformation monitoring uses instruments such as total stations, levels, and convergent gauges to periodically collect monitoring point data for analysis of tunnel deformation. The traditional monitoring m...

AI Technical Summary

Problems solved by technology

These emerging technologies reduce manual operations, have a high degree of automation, a short monitoring cycle, strong continuity of monitoring data, and high accuracy, but they also have certain limitations: for example, ground aperture radar needs to arrange monitoring points on the inner wall of the tunnel. Can damage the physical structure of the inner walls of the tunnel

However, the section-based tunnel deformation monitoring method also has great limitations: a) This method is only suitable for the measurement of geometric structures such as tunnel section convergence measurement and chord length measurement, and cannot monitor tunnel lining surface shedding, segment cracks, etc. b) When analyzing the tunnel deformation by fitting the tunnel section, the change of the overall geometric shape of the tunnel section can be monitored, but the changes caused by uneven force cannot be monitored. Local nonlinear changes in the tunnel section; c) As a discrete monitoring method, the section monitoring method ignores the continuity of tunnel deformation

However, this method is very sensitive to the noise of the tunnel lining, and often requires human-computer interaction, which seriously reduces the degree of automation of the method

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