Tunnel section feature point accurate extraction method based on laser point cloud measurement

Abstract

The invention discloses a tunnel section feature point accurate extraction method based on laser point cloud measurement. A fracture surface extracted from existing point cloud data obtained through three-dimensional laser scanning is large in data size and comprises feature points and a large number of redundant data points, and the post-processing speed is affected. The method comprises the following steps: firstly, setting a section interval, specifying mileage, cutting thickness, offset and angle interval, calculating three-dimensional coordinates of all section extraction positions, and establishing an array containing mileage and coordinate information; calculating a normal vector and a normal plane coefficient at a specified mileage; performing tunnel section point cloud segmentation; transforming the tunnel section point cloud projection to a normal plane; points on the normal plane are converted to an XOY plane; and obtaining section feature points and feature lines until all sections are extracted. According to the method, accurate extraction of feature points and feature lines of various types of tunnels is met, redundant data is avoided, overall deformation features of the tunnels can be reflected, and the post-processing speed is high.

Description

technical field [0001] The invention belongs to the technical field of laser point cloud measurement, in particular to a method for accurately extracting characteristic points of tunnel sections based on laser point cloud measurement. Background technique [0002] Monitoring and measurement during tunnel construction and operation can effectively ensure the stability and safety of the tunnel structure. The traditional measurement methods represented by total station, level and cross section have been unable to adapt to large-scale tunnel measurement tasks. 3D laser scanning measurement technology has the characteristics of fast measurement speed, large amount of data, high precision, high safety and non-contact, which makes the measurement work safer and more efficient. Monitoring and measurement are generally analyzed by extracting cross-sections. The cross-sections extracted from the point cloud data obtained by 3D laser scanning have a large amount of data, including fea...

AI Technical Summary

Problems solved by technology

The disadvantages of this method are: 1) The central axis extraction method proposed by this method is to arbitrarily select the point cloud data of a section of the tunnel, project it to the XOY plane and YOZ plane respectively, and use a quadratic polynomial to calculate the median value of the selected interval. Curve fitting to obtain the equation of the central axis on the XOY and YOZ surfaces. This method of calculating the central axis can only match the actual central axis in a circular tunnel, which has certain limitations; 2) The number of extracted section points is large, Point cloud thinning and feature point extraction are not performed, resulting in slow post-processing calculation speed

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