CN-121746609-B - Intelligent positioning method and system for self-locking type cable-stayed buckling system assembly node

CN121746609BCN 121746609 BCN121746609 BCN 121746609BCN-121746609-B

Abstract

The invention discloses an intelligent positioning method and system for an assembly node of a self-locking cable-stayed buckling system, wherein the method comprises the steps of obtaining three-dimensional point cloud data of a node area to be assembled, and identifying node characteristics of the node to be assembled according to the three-dimensional point cloud data, wherein the node characteristics comprise a geometric center and a surface normal vector set; the method comprises the steps of constructing a node local coordinate system according to node characteristics, calculating a target homogeneous pose of a node to be assembled, controlling an actuating mechanism to translate and adjust the pose of a buckling member so that the current pose of the buckling member is converged with the target homogeneous pose, measuring the actual pose of the buckling member, and performing error compensation according to errors of the actual pose and the target homogeneous pose until the errors are smaller than an error threshold value, so that intelligent positioning of the assembled node is completed.

Inventors

ZHENG PENGPENG
WANG TONGTONG
ZHANG YIBIN
Xie Yuancan
HUANG HONGFEI
SHU YU
GUO RUIHAN
YAN ZHENJUN
XU KEYAO
XU TE

Assignees

贵州桥梁建设集团有限责任公司

Dates

Publication Date: 20260508
Application Date: 20260227

Claims (5)

1. An intelligent positioning method for an assembly node of a self-locking cable-stayed buckling system is characterized by comprising the following steps: Three-dimensional point cloud data of a node area to be assembled are obtained, and node characteristics of the node to be assembled are identified according to the three-dimensional point cloud data, wherein the node characteristics comprise a geometric center and a surface normal vector set; the node characteristics of the nodes to be assembled are identified according to the three-dimensional point cloud data, wherein the three-dimensional point cloud data are subjected to denoising and downsampling to obtain downsampled three-dimensional point cloud data; Taking the average value of the coordinates of all points in the down-sampled three-dimensional point cloud data as the coordinate of the geometric center of the node to be assembled; Analyzing the down-sampled three-dimensional point cloud data by adopting a principal component to obtain a surface normal vector set; taking the average direction of all the surface normal vectors in the surface normal vector set as a main normal vector; Constructing a node local coordinate system according to the node characteristics, calculating the target homogeneous pose of the node to be assembled, and controlling an actuating mechanism to translate and adjust the pose of the buckling hanging piece so that the current pose of the buckling hanging piece is converged with the target homogeneous pose; constructing a node local coordinate system according to the node characteristics comprises the following steps: Wherein, the Is the first The x-axis of the node local coordinate system of the individual nodes to be assembled, Is the first The y-axis of the node local coordinate system of each node to be assembled, Is the first The z-axis of the node local coordinate system of each node to be assembled, Is the first The main normal vector of the nodes to be assembled, Is the first The reference tangential direction of the individual nodes to be assembled, Is vector cross multiplication; calculating the target homogeneous pose of the node to be assembled comprises the following steps: , , , Wherein, the Is the first The node local coordinate system of each node to be assembled is rotated relative to the target rotation matrix of the global coordinate system, Is the first The targets of the nodes to be assembled are in homogeneous pose, Is the first The target translation vectors of the individual nodes to be assembled, To from the first Known offsets of the geometric center of the individual nodes to be assembled from the design assembly reference point, Transpose the symbol; and measuring the actual pose of the buckle hanging piece, and performing error compensation according to the errors of the actual pose and the target homogeneous pose until the actual pose is smaller than an error threshold value, thereby completing intelligent positioning of the assembly node.
2. The intelligent positioning method of the self-locking cable-stayed buckling system assembly node according to claim 1, wherein the error compensation is performed according to the errors of the actual pose and the target homogeneous pose until the errors are smaller than an error threshold value, comprises the steps of calculating the errors of the actual pose and the target homogeneous pose, and specifically comprises the following steps: The actual pose of the buckle hanging piece is as follows: , Wherein, the Is the first The actual pose of each node to be assembled, Is the first The actual rotation matrix of the node local coordinate system of each node to be assembled with respect to the global coordinate system, Is the first The actual translation vectors of the nodes to be assembled; calculating translation errors of the actual pose and the target homogeneous pose: , Wherein, the Is the first Translational errors of the actual pose and the target homogeneous pose of the nodes to be assembled; calculating the rotation errors of the actual pose and the target homogeneous pose: , Wherein, the Is the first The rotation errors of the actual pose of the nodes to be assembled and the pose of the target alignment, The operation is carried out for converting the anti-symmetry matrix into an axial angle vector; , Wherein, the Is the first The pose errors of the actual pose and the target homogeneous pose of the nodes to be assembled.
3. The intelligent positioning method for the assembly node of the self-locking cable-stayed buckling system according to claim 2, wherein according to the first step Pose errors of actual pose and target homogeneous pose of each node to be assembled The error compensation until the error threshold is smaller comprises outputting the displacement correction quantity of the actuator in PD form through a control law or a compensation law, thereby leading the pose to be error Less than the error threshold.
4. The intelligent positioning method for the assembly node of the self-locking cable-stayed buckling system according to claim 3, wherein the position error is as follows When the error threshold value is smaller than the error threshold value, triggering the self-locking mechanism to complete buckling and hanging and detecting the locking state in real time, and if the locking fails, adjusting the displacement correction quantity of the executing mechanism through a control law or a compensation law.
5. An intelligent positioning system of self-locking cable-stayed buckling system assembly node, which is characterized by comprising: the node characteristic extraction module is used for acquiring three-dimensional point cloud data of a node area to be assembled and identifying node characteristics of the node to be assembled according to the three-dimensional point cloud data, wherein the node characteristics comprise a geometric center and a surface normal vector set; the node characteristics of the nodes to be assembled are identified according to the three-dimensional point cloud data, wherein the three-dimensional point cloud data are subjected to denoising and downsampling to obtain downsampled three-dimensional point cloud data; Taking the average value of the coordinates of all points in the down-sampled three-dimensional point cloud data as the coordinate of the geometric center of the node to be assembled; Analyzing the down-sampled three-dimensional point cloud data by adopting a principal component to obtain a surface normal vector set; taking the average direction of all the surface normal vectors in the surface normal vector set as a main normal vector; the position and pose acquisition module is used for constructing a node local coordinate system according to the node characteristics, calculating the target homogeneous position and pose of the node to be assembled, and controlling the execution mechanism to translate and adjust the pose of the buckling hanging piece so that the current pose of the buckling hanging piece is converged with the target homogeneous position and pose; constructing a node local coordinate system according to the node characteristics comprises the following steps: , Wherein, the Is the first The x-axis of the node local coordinate system of the individual nodes to be assembled, Is the first The y-axis of the node local coordinate system of each node to be assembled, Is the first The z-axis of the node local coordinate system of each node to be assembled, Is the first The main normal vector of the nodes to be assembled, Is the first The reference tangential direction of the individual nodes to be assembled, Is vector cross multiplication; calculating the target homogeneous pose of the node to be assembled comprises the following steps: , , , Wherein, the Is the first The node local coordinate system of each node to be assembled is rotated relative to the target rotation matrix of the global coordinate system, Is the first The targets of the nodes to be assembled are in homogeneous pose, Is the first The target translation vectors of the individual nodes to be assembled, To from the first Known offsets of the geometric center of the individual nodes to be assembled from the design assembly reference point, Transpose the symbol; the assembly module is used for measuring the actual pose of the buckle hanging piece, and performing error compensation according to the errors of the actual pose and the target homogeneous pose until the errors are smaller than an error threshold value, so that intelligent positioning of the assembly node is completed.

Description

Intelligent positioning method and system for self-locking type cable-stayed buckling system assembly node Technical Field The invention belongs to the technical field of bridge assembly construction, and particularly relates to an intelligent positioning method and system for an assembly node of a self-locking type cable-stayed buckling and hanging system. Background In the construction process of a large-span arch bridge, a cable-stayed buckling construction process (also called as cable-stayed buckling auxiliary construction or buckling system construction) has become a common technical route in the current engineering practice. The process generally relies on buckling towers, buckling ropes and an anchoring system arranged on arch feet or temporary towers, and provides an adjustable temporary stress path through the buckling ropes, so that a key vertical and horizontal construction supporting force is provided before a self-balancing system cannot be formed on an arch rib section, and stability and linear precision of the arch rib section in the installation process are ensured. However, the traditional arch bridge buckling construction relies on total stations or level gauges to perform discrete measurement of key nodes, the data updating frequency is low, and dynamic deformation of arch rib sections under the effects of factors such as wind load, temperature gradient, buckling cable tension disturbance and the like cannot be reflected in real time. Particularly, under the condition of complex stress coupling of a cable-stayed buckling system, a single measuring means is difficult to capture the real-time change of the space posture, and the arch rib linear deviation accumulation is easy to cause. Secondly, in the existing engineering, setting and adjustment of the buckling cable tensioning value are generally performed by a field engineer based on experience or static calculation results, but a closed-loop control mechanism capable of feeding back arch rib deformation, buckling cable force change and butt joint error in real time is lacked. Once external disturbance is large (wind, construction load and the like), manual judgment is difficult to respond in time, and node gesture adjustment efficiency is low and even butt joint is difficult easily caused. Therefore, a technical solution is needed to intelligently guide the actuator to accomplish high-precision positioning and to compensate translational and rotational errors in real time. Disclosure of Invention In order to solve the technical problems, the invention provides an intelligent positioning method of an assembly node of a self-locking type cable-stayed buckling and hanging system, which comprises the following steps: Three-dimensional point cloud data of a node area to be assembled are obtained, and node characteristics of the node to be assembled are identified according to the three-dimensional point cloud data, wherein the node characteristics comprise a geometric center and a surface normal vector set; Constructing a node local coordinate system according to the node characteristics, calculating the target homogeneous pose of the node to be assembled, and controlling an actuating mechanism to translate and adjust the pose of the buckling hanging piece so that the current pose of the buckling hanging piece is converged with the target homogeneous pose; and measuring the actual pose of the buckle hanging piece, and performing error compensation according to the errors of the actual pose and the target homogeneous pose until the actual pose is smaller than an error threshold value, thereby completing intelligent positioning of the assembly node. Further, identifying node characteristics of the node to be assembled according to the three-dimensional point cloud data comprises denoising and downsampling the three-dimensional point cloud data to obtain downsampled three-dimensional point cloud data; Taking the average value of the coordinates of all points in the down-sampled three-dimensional point cloud data as the coordinate of the geometric center of the node to be assembled; Analyzing the down-sampled three-dimensional point cloud data by adopting a principal component to obtain a surface normal vector set; the average direction of all the surface normal vectors in the surface normal vector set is taken as the main normal vector. Further, constructing a node local coordinate system according to the node characteristics includes: Wherein, the Is the firstThe x-axis of the node local coordinate system of the individual nodes to be assembled,Is the firstThe y-axis of the node local coordinate system of each node to be assembled,Is the firstThe z-axis of the node local coordinate system of each node to be assembled,Is the firstThe main normal vector of the nodes to be assembled,Is the firstThe reference tangential direction of the individual nodes to be assembled,Is vector cross-multiplied. Further, calculating the target homogeneous pose o