CN-122023679-A - Segment corner reconstruction method and system based on scan data

CN122023679ACN 122023679 ACN122023679 ACN 122023679ACN-122023679-A

Abstract

The invention relates to the field of bridge engineering, in particular to a segment corner reconstruction method and system based on scanning data, wherein the method comprises the steps of respectively performing edge fitting and reconstruction and surface fitting and reconstruction based on a three-dimensional point cloud of a bridge segment and a patch model corresponding to the point cloud; according to the corner points obtained by the fitting reconstruction of the side lines and the corner points obtained by the fitting reconstruction of the surface, the corner points of the bridge segments are determined, and the reconstruction fitting method improves the success rate of corner feature extraction, reduces the work difficulty of earlier scanning operation, improves the operation success rate, avoids multiple scanning, and provides different reconstruction fitting methods for the classification type aiming at common corner error sources on site so as to adapt to corner error extraction under different interference conditions.

Inventors

YU ZHIBING
LV YINMING
LIU LEI
YANG JIE
FENG XIAOYANG
YANG ZHI
XIANG YINGJIE
ZHANG TIANYI
YANG HONG
He Enhuai
HUANG BING
LU WEI
ZOU YU
FENG JING
HU YUCHEN

Assignees

四川省钢构智造有限公司
四川路桥建设集团股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. A method of segment corner reconstruction based on scan data, comprising: based on the three-dimensional point cloud of the bridge segment and the patch model corresponding to the point cloud, performing edge fitting and reconstruction and surface fitting and reconstruction respectively; determining bridge segment corner points according to corner points obtained by the edge fitting reconstruction and corner points obtained by the face fitting reconstruction; And the corner points of the bridge segments are determined by the distances between the corner points obtained by the boundary line fitting reconstruction and the corner points obtained by the surface fitting reconstruction.
2. The method of segment corner reconstruction based on scan data of claim 1, wherein the edge fitting process comprises: downsampling the point cloud after coarse positioning transformation by using the contour of the patch model to obtain a multiple linear edge group; performing point-line matching according to the distance from the midpoint of the point cloud after coarse positioning transformation to the straight line in the multiple straight line edge group; fitting the matched point lines, projecting the points onto a plane perpendicular to the corresponding straight line, and clustering the projected points to obtain a straight line point cluster.
3. The segment corner reconstruction method based on scan data according to claim 2, wherein the edge reconstruction process comprises: reconstructing the linear point clusters by using NURBS curves to obtain a reconstruction curve set; extending the two ends of the reconstruction curve set, and determining the nearest points of two adjacent extension curves; and averaging the obtained nearest points to obtain corner points under the fitting and reconstruction of the edge line.
4. The method of segment corner reconstruction based on scan data of claim 1, wherein the face fitting process comprises: Screening the point cloud after coarse positioning transformation in a spherical space with the corner of the outline as the center to obtain disordered point cloud at the corner; Determining the characteristics of points p in the unordered point cloud at the corners, performing breadth-first clustering, and outputting a clustering container; wherein each cluster container corresponds to a planar point cloud.
5. The method of segment corner reconstruction based on scan data according to claim 4, wherein determining characteristics of points p in the unordered point cloud at the corners comprises: Determining the distance between a point p in the unordered point cloud at the corner and a plurality of nearest neighbor points, and taking the point with the distance smaller than a radius threshold value as a threshold value point set; Calculating a covariance matrix of the threshold point set, and calculating eigenvalues and corresponding eigenvectors of the covariance matrix; And determining a flat index and a normal direction of the point p as the characteristics of the point p according to the characteristic values and the corresponding characteristic vectors of the covariance matrix.
6. The method of segment corner reconstruction based on scan data according to claim 5, wherein the breadth-first clustering of points p comprises: sorting all points p according to the flat index; Loading the ordered point sets into an empty clustering container and numbering; and clustering the points p corresponding to each number according to the normal direction of the points p and all neighbor points thereof, and outputting a clustering container after the clustering is completed.
7. The segment corner reconstruction method based on scan data according to claim 6, wherein for any planar point clouds Pa and Pb, the face reconstruction process comprises: S101, acquiring optimal planes ha and hb corresponding to Ping Miandian clouds Pa and Pb according to a RANSAC algorithm based on a plane distance threshold; S102, determining an intersection line lab of the optimal planes ha and hb; s103, projecting the plane point clouds Pa and Pb by using a columnar filtering range, calculating the distance from a projection point to an intersection line lab, and reserving the point projected in the columnar filtering range; s104, determining the optimal planes corresponding to the reserved points, and calculating intersecting lines between the optimal planes; S105, changing a columnar filtering range, and repeatedly executing S103 and S104 to obtain a plurality of groups of projection intersection results; And S106, screening out optimal intersecting lines from a plurality of groups of projection intersecting line results, and obtaining corner points under surface fitting and reconstruction according to the optimal intersecting lines.
8. The segment corner reconstruction method based on scan data according to claim 7, wherein the corner determination method under the face fitting and reconstruction is as follows: Filtering and weighted averaging the optimal intersecting lines through normal distribution, and then k clustering; determining corner points under surface fitting and reconstruction according to the distance between the clustering center and the surrounding original point cloud clustering center; wherein, the optimal intersecting line is determined by clustering a plurality of groups of projection intersecting line results, or, And determining according to the proportion of the inner points contained in the two planes corresponding to the projection intersection lines.
9. The segment corner reconstruction method based on the scan data according to claim 1, wherein the method for determining the bridge segment corner points is as follows: performing repeated surface reconstruction to obtain a possible corner point group in the surface reconstruction process; Clustering the corner point groups to obtain clustering mean points; comparing the distance between the average value point of the clusters and the corner points under the fitting and reconstruction of the edge lines: If the error is smaller than the error, fitting the cluster mean points and the boundary lines and using the corner points under reconstruction as bridge segment corner points; if the error is greater than or equal to the error, determining by manual selection based on all points in the corner point group, the cluster mean point, the corner points under the fitting and reconstruction of the edge and all points in the preset peripheral range of the corner points under the fitting and reconstruction of the edge.
10. A segment corner reconstruction system based on scan data for performing the method of any of claims 1-9, comprising: the data importing module is used for reading the three-dimensional point cloud of the bridge segment and the patch model corresponding to the point cloud; the edge fitting and reconstructing module is used for performing edge fitting and reconstruction according to the three-dimensional point cloud of the bridge segment and the patch model corresponding to the point cloud and outputting corner points under the edge fitting and reconstruction; the surface fitting and reconstructing module is used for carrying out surface fitting and reconstruction according to the three-dimensional point cloud of the bridge segment and the surface patch model corresponding to the point cloud, and outputting corner points under the surface fitting and reconstruction; and the bridge segment corner point determining module is used for determining the bridge segment corner point according to the corner point under the boundary line fitting and reconstruction and the corner point under the surface fitting and reconstruction.

Description

Segment corner reconstruction method and system based on scan data Technical Field The invention relates to the field of bridge engineering, in particular to a segment corner reconstruction method and system based on scanning data. Background In the actual assembly and hoisting process of the large complex bridge, the high-precision matching and alignment requirements on the sizes of the multiple sections are extremely high. The traditional method generally relies on-site manual measurement, which is time-consuming and labor-consuming, has large measurement error, and is easy to further increase in error due to the fact that indirect measurement is required due to interference of additional components, so that construction progress and quality are affected. In the prior art, a method based on laser or oblique photography scanning is mostly adopted, absolute measurement deviation can be relatively reduced, component interference is avoided, but processing of scanning point cloud data is a key problem, and partial scanning point cloud is frequently lost due to interference or shielding and other reasons. The angular point measurement of the corner of the component is key measurement point data under the existing construction method and standard, but because the corner of the segment component is often provided with the characteristics of grooves, welding seams, matching parts and the like which affect the corner, the existing angular point selection method has the problems of difficult measurement, poor precision and large error, and further, the method relies on manual confirmation in the reconstruction process of the corner of the segment. Disclosure of Invention The invention aims to solve the problems of low success rate of scanning operation and insufficient corner measurement in the prior art and provides a segment corner reconstruction method and system based on scanning data. In a first aspect, the present invention provides a segment corner reconstruction method based on scan data, comprising: based on the three-dimensional point cloud of the bridge segment and the patch model corresponding to the point cloud, performing edge fitting and reconstruction and surface fitting and reconstruction respectively; determining bridge segment corner points according to corner points obtained by the edge fitting reconstruction and corner points obtained by the face fitting reconstruction; And the corner points of the bridge segments are determined by the distances between the corner points obtained by the boundary line fitting reconstruction and the corner points obtained by the surface fitting reconstruction. Aiming at common corner error (sideline/surface) sources on site, different reconstruction fitting methods are provided for classification type so as to adapt to corner error extraction under different interference conditions, and the reconstruction fitting method improves the success rate of corner feature extraction, reduces the working difficulty of early scanning operation, improves the operation success rate and avoids repeated scanning. Preferably, the contour of the patch model is used for downsampling the point cloud after coarse positioning transformation to obtain multiple linear edge groups; performing point-line matching according to the distance from the midpoint of the point cloud after coarse positioning transformation to the straight line in the multiple straight line edge group; fitting the matched point lines, projecting the points onto a plane perpendicular to the corresponding straight line, and clustering the projected points to obtain a straight line point cluster. Preferably, the edge reconstruction process comprises: reconstructing the linear point clusters by using NURBS curves to obtain a reconstruction curve set; extending the two ends of the reconstruction curve set, and determining the nearest points of two adjacent extension curves; and averaging the obtained nearest points to obtain corner points under the fitting and reconstruction of the edge line. A complete edge fitting and reconstruction scheme is provided to accommodate corner error extraction in the case of edge interference. Preferably, the surface fitting process comprises: Screening the point cloud after coarse positioning transformation in a spherical space with the corner of the outline as the center to obtain disordered point cloud at the corner; Determining the characteristics of points p in the unordered point cloud at the corners, performing breadth-first clustering, and outputting a clustering container; wherein each cluster container corresponds to a planar point cloud. Preferably, the process of determining the characteristics of the point p in the unordered point cloud at the corner comprises: Determining the distance between a point p in the unordered point cloud at the corner and a plurality of nearest neighbor points, and taking the point with the distance smaller than a radius threshold value as a thres