CN117744225B - Quick generation method of bridge drawing - Google Patents
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- CN117744225B CN117744225B CN202311804032.2A CN202311804032A CN117744225B CN 117744225 B CN117744225 B CN 117744225B CN 202311804032 A CN202311804032 A CN 202311804032A CN 117744225 B CN117744225 B CN 117744225B
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Abstract
The invention discloses a method for rapidly generating a bridge drawing, which comprises the following steps: (1) Acquiring bridge point clouds by using a laser radar and an RTK according to a preset route; (2) Noise reduction processing is carried out on the collected bridge point cloud data, and abnormal points are removed; (3) thinning the bridge point cloud data after noise reduction; (4) Performing point cloud splicing on the characteristic points of the overlapping area, unifying bridge point cloud data acquired at different positions to a CGCS2000 coordinate system, and generating a las-format bridge point cloud model; (5) Importing a las format bridge point cloud model into AutoDesk Civil D, and obtaining Ping Miandian cloud and elevation point cloud through model view rotation and point cloud clipping; (6) Deleting Ping Miandian irrelevant objects in the cloud and the elevation point cloud, connecting bridge characteristic points by using a Line command, and generating a bridge CAD plan and an elevation. The method can realize rapid drawing of CAD drawings of the bridge plane and the facade, and remarkably improve the efficiency of the scheme design of the bridge health monitoring system.
Description
Technical Field
The invention relates to a bridge mapping method, in particular to a method for quickly generating a bridge drawing, which is particularly suitable for quickly generating a main line bridge drawing in national province.
Background
The bridge health monitoring system is mainly used for evaluating the health degree of the bridge by monitoring the structural response of the bridge under the actions of load, environment and the like for a long time and providing a timely safety early warning function for the structure. The scheme design is a key work for determining whether the bridge health monitoring system is successful or not, and the scheme design needs to be carried out on the basis of CAD drawings. The long bridge is an important unit project, the budget is full, and a construction drawing design file is completely stored; for the main line bridge of the national province with wide range, part of bridge file management work built in early years is not paid attention to, and the bridge design data is incomplete and the drawing is missing, so that a scheme designer needs to go to the bridge site to perform field measurement and then hand-drawing CAD drawing. At present, bridge line-shaped measurement is mainly carried out through a total station and a level gauge, the total station can measure distance, elevation, coordinates, angles and the like at the same time, however, the total station needs to be in communication with an observation target, otherwise, a station is required to be turned, and measurement workload is increased; the level is only capable of elevation measurements, and is typically only used as an auxiliary measuring tool. In addition, some local areas are also measured by tools such as a tape and a range finder, so that the method is long in time consumption, high in cost and low in efficiency. In recent years, with the development of advanced sensing, GNSS and unmanned aerial vehicle flight control technologies, measurement methods based on unmanned aerial vehicles, laser radars and RTKs are gradually applied to bridge prefabricated part size detection and deformation measurement.
In addition, when the design staff has more workload and the given design time is too short, the design staff and the mapping staff do not have enough time and energy to perform on-site measurement, and even can apply some bridge drawings with similar structures to perform the design, so that the expected purpose of the health monitoring scheme design can not be achieved.
Disclosure of Invention
The invention aims to: aiming at the defects in the prior art, the invention provides the rapid generation method of the bridge drawing, wherein the unmanned aerial vehicle is used for carrying the laser radar, the information of the point clouds of different angles of the bridge is flexibly and efficiently collected, the point clouds are preprocessed and spliced to generate the bridge point cloud model, the model is imported into the point cloud processing software, the rapid drawing of the CAD drawing of the bridge plane and the elevation is realized, the base drawing is provided for the scheme design of the bridge health monitoring system, the measurement cost is reduced, the design efficiency is improved, and the rapid generation method is particularly suitable for the rapid and batch plotting of the trunk bridge group in national province.
The technical scheme is as follows: a method for rapidly generating a bridge drawing comprises the following steps:
(1) Planning a plurality of routes for the tested bridge, and acquiring bridge point cloud data of different positions and angles according to preset routes by adopting a laser radar and an RTK;
(2) Noise reduction processing is carried out on the bridge point cloud data, and abnormal points are removed;
(3) Thinning the bridge point cloud data after noise reduction;
(4) The noise-reduced bridge point cloud data comprise a source point cloud and a target point cloud, an overlapping area of the source point cloud and the target point cloud is defined, point cloud splicing is carried out on characteristic points of the overlapping area, and bridge point cloud data acquired at different positions and angles are unified under a CGCS2000 coordinate system to generate a las format bridge point cloud model;
(5) Importing a las format bridge point cloud model into AutoDesk Civil D, and obtaining Ping Miandian cloud and elevation point cloud through model view rotation and point cloud clipping;
(6) Deleting Ping Miandian irrelevant objects in the cloud and the elevation point cloud, leaving bridge characteristic points, connecting the bridge characteristic points by using a Line command, and generating a bridge CAD plan and an elevation.
In one embodiment, the lidar and the RTK of step (1) are onboard the drone.
In one embodiment, the step (2) performs noise reduction processing on the collected bridge point cloud data based on a gaussian filtering algorithm.
Further optionally, the feature points of the overlapping area are subjected to point cloud stitching based on an ICP algorithm. The ICP algorithm is preferably a point-to-face ICP registration algorithm;
Let p i＝(pix,piy,piz) be a source point cloud, q i＝(qix,qiy,qiz) be the corresponding target point, n i＝(nix,niy,niz) be the unit normal vector of q i;
The optimal transformation matrix M o is searched for through least square iteration:
wherein the transformation matrix M is composed of a rotation matrix R (u, v, w) and a translation matrix T (T x,ty,tz):
M＝T(tx,ty,tz)·R(u,v,w)。
In one embodiment, step (5) includes the following:
(1) Rotating the bridge point cloud model, and designating a series of characteristic points in the bridge point cloud model;
(2) The following cuts are defined:
Ax+By+Cz+D＝0
A. B, C, D is clipping plane parameter;
(3) Traversing the characteristic points, and calculating the distance d between each point and the clipping surface according to the following formula:
Wherein, (x 0,y0,z0) is the coordinates of the feature points traversed;
(4) Judging whether the distance d from each feature point to the clipping surface is within a threshold range, if so, storing the feature point until the traversal of all the feature points is completed;
(5) And respectively projecting the stored characteristic points into a preset plane and a preset vertical plane to obtain a bridge plane view and a bridge vertical plane view.
In one embodiment, the extraneous object in the planar point cloud of step (6) comprises a pavement marking line, a vehicle, a water accumulation, a light pole. Correspondingly, the bridge characteristic points in the plane point cloud comprise contour points of a bridge plane, a railing and a central partition belt.
In one embodiment, the unrelated objects in the elevation point cloud in the step (6) include water surface, vegetation and land. Correspondingly, the bridge characteristic points in the elevation point cloud comprise contour points of a bridge elevation, pier columns and a capping beam.
Compared with the prior art, the method has the following beneficial effects:
The unmanned aerial vehicle is used for carrying the laser radar and the RTK, so that the activity and the high efficiency of the unmanned aerial vehicle are fully utilized, the establishment of a bridge point cloud model and the quick measurement of the line shape are realized, and the traditional measurement mode of manually using a total station and a level gauge is replaced;
The rapid drawing of the CAD drawing of the bridge plane and the elevation is realized by collecting point clouds in batches of multiple bridges and multiple spans, processing the point cloud information into las format data which can be read by AutoDesk Civil D software, extracting target data in AutoDesk Civil D software, cutting, deleting and connecting the bridge point cloud model, thereby omitting the conventional manual measurement of the bridge line shape operation, reducing the cost, improving the drawing efficiency, greatly improving the working efficiency of line design staff, reducing the load and providing support for the high-quality completion of the project under the conditions of the tight time and heavy task of the health monitoring project of the bridge group.
Drawings
FIG. 1 is a flow chart of a method for generating a bridge drawing according to a preferred embodiment of the present invention;
Fig. 2 is a diagram showing the principle of the point-to-face ICP algorithm in accordance with a preferred embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention relates to a bridge drawing generation method for bridge mapping, which comprises the following steps:
(1) Planning a plurality of routes for the tested bridge, and acquiring bridge point cloud data according to the preset routes by using a laser radar and an RTK.
(2) And (3) carrying out noise reduction treatment on the collected bridge point cloud data, and eliminating abnormal points reflected by rain, fog and the like.
(3) And thinning the bridge point cloud data after noise reduction according to proper intervals, so that the point cloud model is light, the hardware cost of computer analysis is reduced, and the processing speed is improved.
(4) And (3) performing point cloud splicing on the characteristic points of the overlapping region, unifying bridge point cloud data acquired at different positions to a CGCS2000 (2000 national geodetic coordinate system) coordinate system, and generating a final las format bridge point cloud model. The overlapping area refers to an overlapping range of a source point cloud and a target point cloud, the size of the overlapping range is related to the flight speed, the position and the laser radar scanning angle of the unmanned aerial vehicle, and the overlapping range is calibrated specifically through the point cloud overlapping rate. The two-piece point cloud registration with low overlapping rate has the problems of high difficulty, low precision, difficult feature extraction and easy mismatch. The basic basis of the calculation of the point cloud overlapping rate is to acquire the point coordinates of two or more point clouds and calculate the intersection rate between the two or more source point clouds and the target point cloud. The specific calculation process is as follows:
① Firstly, comparing the number and the positions of a plurality of groups of point cloud coordinates to obtain a common point between a source point cloud and a target point cloud;
② And calculating the ratio of the common points in the target point cloud to obtain the overlapping rate between the two groups of point clouds (the source point cloud and the target point cloud), wherein a calculation formula is shown in a formula (1).
Wherein ω represents the point cloud overlap ratio; s 1 represents the number of coincident points of the source point cloud and the target point cloud; s represents the total number of points of the target point cloud.
(5) And importing AutoDesk Civil D into a labs-format bridge point cloud model, and obtaining a bridge plane point cloud and a bridge elevation point cloud through rotation model visual angles and cutting operation.
(6) Deleting Ping Miandian objects such as pavement marking lines, vehicles, ponding, lamp posts and the like in the cloud, leaving characteristic points of bridge planes, railings and central separation bands, connecting the characteristic points by using a Line command, and generating a CAD plan.
(7) And deleting objects such as water surfaces, vegetation, lands and the like in the vertical point cloud, leaving characteristic points of the objects such as bridge vertical surfaces, pier columns, capping beams and the like, connecting the characteristic points by using a Line command, and generating a CAD vertical drawing.
Based on the above embodiment, step (1) may plan 5 routes before, after, left, right, and top for the tested bridge, and collect the bridge point cloud according to the preset 5 routes by using the unmanned aerial vehicle carrying the laser radar and the RTK.
Preferably, in the step (2), noise reduction processing is performed on the collected bridge point cloud data based on a gaussian filtering algorithm.
As a preferred solution, the step (4) may calculate the common point between the source point cloud and the target point cloud by ICP algorithm. The ICP algorithm (ITERATIVE CLOSEST POINT), namely the nearest point iterative algorithm, is used for realizing the registration of point clouds by transferring the point clouds under different coordinate systems in a three-dimensional space into the same group of coordinate systems through rotation translation change so as to enable the point clouds of the same part to coincide.
The ICP algorithm includes a point-to-point ICP and a point-to-plane ICP algorithm, and as shown in fig. 2, the present embodiment employs a point-to-plane ICP registration algorithm. The point-to-face ICP registration is to minimize the distance from the source point cloud to the tangential plane of the target point cloud, so as to calculate the transformation parameters of the input data set, and the specific process is as follows:
Let p i＝(pix,piy,piz) be a source point cloud, q i＝(qix,qiy,qiz) be the corresponding target point, n i＝(nix,niy,niz) be the unit normal vector of q i. The best transformation matrix M o is found by least squares iteration, see equation 2. The transformation matrix M consists of a rotation matrix R (u, v, w) and a translation matrix T (T x,ty,tz), as shown in formula (3).
Mo＝argmin∑i((M·pi-qi)·ni)2 (2)
M＝T(tx,ty,tz)·R(u,v,w) (3)
Furthermore, step (5) leads the las bridge point cloud model collected by the unmanned aerial vehicle into AutoDesk Civil D, rotates the model view angle, cuts the bridge point cloud model by constructing a cutting face, is used for generating a bridge plane view and a vertical view, and the algorithm implementation process is as follows:
① Designing a cutting surface;
the clipping plane equation is: ax+By+ cz+d=0
Wherein A, B, C, D is clipping plane parameter;
② Designating a series of characteristic points in the bridge point cloud model;
Calculating the distance from each characteristic point to the cutting surface;
In the formula (4), (x 0,y0,z0) is the coordinates of each feature point; d is the distance from the feature point to the clipping surface.
③ Judging whether the distance d between each characteristic point and the cutting surface is within a threshold range or not; if so, the feature point is saved, if the threshold range is exceeded, the calculation and the judgment are continued whether the distances from other feature points to the clipping surface meet the threshold requirement or not until the traversal of all the feature points is completed;
④ And finally, respectively projecting the stored characteristic points into a preset plane and a preset vertical plane to obtain a plane view and a vertical plane view of the bridge.
The foregoing embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the present invention and to implement the same according to the present invention, not to limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (9)
1. The rapid generation method of the bridge drawing is characterized by comprising the following steps of:
(1) Planning a plurality of routes for the tested bridge, and acquiring bridge point cloud data of different positions and angles according to preset routes by adopting a laser radar and an RTK;
(2) Noise reduction processing is carried out on the bridge point cloud data, and abnormal points are removed;
(3) Thinning the bridge point cloud data after noise reduction;
(4) The noise-reduced bridge point cloud data comprise a source point cloud and a target point cloud, an overlapping area of the source point cloud and the target point cloud is defined, point cloud splicing is carried out on characteristic points of the overlapping area, and bridge point cloud data acquired at different positions and angles are unified under a CGCS2000 coordinate system to generate a las format bridge point cloud model;
(5) Importing a las format bridge point cloud model into AutoDeskCivil D, and obtaining Ping Miandian cloud and elevation point cloud through model view rotation and point cloud clipping; the method comprises the following steps:
rotating the bridge point cloud model, and designating a series of characteristic points in the bridge point cloud model;
The following cuts are defined:
Ax+By+Cz+D＝0
A. B, C, D is clipping plane parameter;
traversing the characteristic points, and calculating the distance d between each point and the clipping surface according to the following formula:
Wherein, (x 0,y0,z0) is the coordinates of the feature points traversed;
judging whether the distance d from each feature point to the clipping surface is within a threshold range, if so, storing the feature point until the traversal of all the feature points is completed;
Respectively projecting the stored characteristic points into a preset plane and a preset vertical plane to obtain a bridge plane diagram and a bridge vertical plane diagram;
(6) Deleting Ping Miandian irrelevant objects in the cloud and the elevation point cloud, leaving bridge characteristic points, connecting the bridge characteristic points by using a Line command, and generating a bridge CAD plan and an elevation.
2. The method for rapidly generating a bridge drawing according to claim 1, wherein in the step (1), the laser radar and the RTK are mounted on an unmanned plane.
3. The method for quickly generating the bridge drawing according to claim 1, wherein in the step (2), noise reduction processing is performed on the collected bridge point cloud data based on a gaussian filtering algorithm.
4. The method for rapidly generating the bridge drawing according to claim 1 or 3, wherein in the step (4), the characteristic points of the overlapping area are spliced by point cloud based on an ICP algorithm.
5. The method for rapidly generating the bridge drawing according to claim 4, wherein the ICP algorithm is a point-to-face ICP registration algorithm;
Let p i＝(pix,piy,piz) be a source point cloud, q i＝(qix,qiy,qiz) be the corresponding target point, n i＝(nix,niy,niz) be the unit normal vector of q i;
The optimal transformation matrix M o is searched for through least square iteration:
Mo＝argmin∑i((M·pi-qi)·ni)2
Wherein the transformation matrix M is composed of a rotation matrix R (u, v, w) and a translation matrix T (T x,ty,tz):
M＝T(tx,ty,tz)·R(u，v，w)。
6. The method for quickly generating a bridge drawing according to claim 1, wherein in the step (6), the unrelated objects in the plane point cloud comprise pavement marker lines, vehicles, ponding and lamp posts.
7. The method for quickly generating a bridge drawing according to claim 6, wherein the bridge feature points in the plane point cloud comprise contour points of a bridge plane, a railing and a central partition.
8. The method for quickly generating a bridge drawing according to claim 1, wherein in the step (6), the unrelated objects in the elevation point cloud comprise water surface, vegetation and land.
9. The method for quickly generating the bridge drawing according to claim 8, wherein the bridge feature points in the elevation point cloud comprise contour points of a bridge elevation, pier columns and capping beams.
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| 采用激光扫描的古田会议会址三维几何造型建模;黄明伟等;华侨大学学报（自然科学版）;20170531;第415-416页 * |
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