A large steel structure frame array flatness detection method
By combining a laser tracker and a photogrammetry system, a global measurement benchmark was established and remote shooting was performed, which solved the problems of accuracy and efficiency in the flatness detection of large steel structure frames and achieved high-precision and high-efficiency flatness measurement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CITIC HEAVY INDUSTRIES CO LTD
- Filing Date
- 2026-05-15
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient for efficiently and accurately detecting the flatness of large steel structure frames. Conventional methods are inefficient and have large cumulative errors. Handheld photogrammetry systems require a large number of photos on large workpieces, are labor-intensive, and lack precision.
A global measurement reference coordinate system is established using a laser tracker, and remote shooting is performed using a photogrammetry system. Data is converted to the reference through coordinate transformation. High-density point cloud acquisition is performed using the photogrammetry system under the laser tracker reference. Overall flatness analysis is performed by combining the data from the laser tracker and the photogrammetry system.
It significantly improves the accuracy and efficiency of flatness measurement of large steel structure frames, reduces the number of photos, reduces labor intensity, reduces cumulative errors, and ensures high accuracy of overall flatness.
Smart Images
Figure CN122408671A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of flatness inspection of structural components, and specifically to a method for flatness inspection of large steel structure frame arrays. Background Technology
[0002] Large steel structures are characterized by their large size, heavy weight, and high precision requirements. These steel frame structures often employ a modular manufacturing process followed by on-site assembly. The sub-frames are connected via precision-machined flanges and positioning bolts. To ensure the overall assembly meets functional requirements, extremely high precision is required for the final planar accuracy of the frame array.
[0003] However, for ultra-large frames with an area of 15m×15m or even larger, conventional flatness detection methods (such as point-by-point measurement with a level or laser rangefinder) are difficult to achieve overall accuracy detection, and the cumulative measurement error is large and the efficiency is low.
[0004] Photogrammetry is a high-precision measurement technology developed in recent years, suitable for medium to large-sized workpieces. It obtains the geometric features of the workpiece by capturing numerous coded points on its surface and then using software for image processing and point cloud data analysis. However, when measuring ultra-large workpieces, handheld photogrammetry, due to limitations in camera field of view and image size, requires taking hundreds or even thousands of photos. This not only results in a huge workload but also leads to significant cumulative errors due to the large number of photos, severely affecting the measurement accuracy of the overall flatness of the large surface area being measured. Summary of the Invention
[0005] To address the above problems, this invention proposes a method for detecting the flatness of large steel structure frames, the specific technical solution of which is as follows: A method for detecting the flatness of a large steel frame structure includes the following steps: Step 1: After assembling the steel frame array, divide the plane to be tested into multiple measurement areas, arrange multiple measurement reference targets on the plane to be tested, and use a laser tracker to measure the spatial coordinate data of all measurement reference targets to establish a global measurement reference coordinate system.
[0006] Step 2: Arrange measurement coding points and measurement reference rulers in each measurement area, use a photogrammetric system to take pictures of each measurement area, and analyze and obtain the spatial coordinate data of the measurement coding points in each measurement area relative to the measurement reference target in that area under the coordinate system of the photogrammetric system itself.
[0007] Step 3: Using the measurement reference targets in each area as common points, transform the spatial coordinate data in the coordinate system of the photogrammetric system to the global measurement reference coordinate system through coordinate transformation, and stitch them together to obtain the complete point cloud data of the plane to be detected. Analyze the data to obtain the overall planar accuracy data of the plane to be detected.
[0008] The photogrammetry system includes a crane, a pod, a camera, and a wireless control module. The pod is mounted on the underside of the crane via lifting lugs. An opening is provided at the bottom of the pod, and the camera is installed inside the pod with its lens and supplementary light extending outward through the opening. The wireless control module communicates with the camera.
[0009] Furthermore, the hoisting box is made of wood or plastic.
[0010] Furthermore, the spacing between adjacent photocoded points is 800mm-1000mm.
[0011] Furthermore, the measurement area is rectangular, with measurement reference targets at the four corners and the center of the measurement area.
[0012] The beneficial effects of this invention are as follows: 1. By hoisting the camera high for remote control shooting, the problems of large number of photos, high labor intensity, and serious cumulative errors caused by handheld shooting due to close distance and small image size are solved. In addition, by increasing the shooting distance, the number of photos can be significantly reduced, improving measurement efficiency and accuracy.
[0013] 2. By combining a laser tracker with a photogrammetric system and using a shared measurement reference target, a "same reference" conversion between the two measurement systems was achieved. The laser tracker is responsible for establishing a large-scale, high-precision global control reference, while the photogrammetric system performs high-density point cloud acquisition for each sub-region under this reference. Finally, through coordinate fitting, the problem of large cumulative error in a single photogrammetric system was solved, ensuring the accuracy of the flatness measurement of large steel structure frame arrays. Attached Figure Description
[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0015] Figure 1 This is a schematic diagram of the photogrammetry system described in this invention; Figure 2 This is a schematic diagram of the measurement in step one of the present invention; Figure 3 This is a schematic diagram of the measurement in step two of the present invention.
[0016] In the diagram: 1. Large steel structure frame; 2. Overhead crane; 3. Wire rope; 4. Hoisting box; 5. Lifting lug; 6. Camera; 7. Fixing clamp; 8. Wireless control module; 9. Measurement coding point; 10. Measurement reference ruler; 11. Measurement reference target; 12. Laser tracker. Detailed Implementation
[0017] The present invention provides the following specific implementation schemes: like Figure 1-3 As shown, the present invention provides a method for detecting the flatness of a large steel structure frame array, comprising the following steps: Step 1: After assembling the steel frame array, divide the plane to be tested into multiple measurement areas, arrange multiple measurement reference targets on the plane to be tested, and use a laser tracker to measure the spatial coordinate data of all measurement reference targets to establish a global measurement reference coordinate system.
[0018] Step 2: Arrange measurement coding points and measurement reference rulers in each measurement area, use a photogrammetric system to take pictures of each measurement area, and analyze and obtain the spatial coordinate data of the measurement coding points in each measurement area relative to the measurement reference target in that area under the coordinate system of the photogrammetric system itself.
[0019] Step 3: Using the measurement reference targets in each area as common points, transform the spatial coordinate data in the coordinate system of the photogrammetric system to the global measurement reference coordinate system through coordinate transformation, and stitch them together to obtain the complete point cloud data of the plane to be detected. Analyze the data to obtain the overall planar accuracy data of the plane to be detected.
[0020] The photogrammetry system includes a crane, a pod, a camera, and a wireless control module. The pod is mounted on the underside of the crane via lifting lugs. An opening is provided at the bottom of the pod, and the camera is installed inside the pod with its lens and supplementary light extending outward through the opening. The wireless control module communicates with the camera.
[0021] Furthermore, the hoisting box is made of wood or plastic.
[0022] Furthermore, the spacing between adjacent photocoded points is 800mm-1000mm.
[0023] Furthermore, the measurement area is rectangular, with measurement reference targets at the four corners and the center of the measurement area.
[0024] This invention suspends the camera at a high altitude for remote-controlled shooting, solving the problems of large number of photos, high labor intensity, and serious cumulative errors caused by handheld shooting due to short distance and small image size. Furthermore, by increasing the shooting distance, the number of photos can be significantly reduced, improving measurement efficiency and accuracy. By combining a laser tracker with a photogrammetric system and using a shared measurement reference target, "same reference" conversion of data from both systems is achieved. The laser tracker is responsible for establishing a large-scale, high-precision global control reference, while the photogrammetric system performs high-density point cloud acquisition for each sub-region under this reference. Finally, through coordinate fitting, the problem of large cumulative errors in a single photogrammetric system is solved, ensuring the accuracy of flatness measurement of large steel structure frame arrays.
[0025] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.
Claims
1. A method for detecting the flatness of a large steel structure frame array, characterized in that, Includes the following steps: Step 1: After assembling the steel frame array, divide the plane to be tested into multiple measurement areas, arrange multiple measurement reference targets on the plane to be tested, use a laser tracker to measure the spatial coordinate data of all measurement reference targets, and establish a global measurement reference coordinate system. Step 2: Arrange measurement coding points and measurement reference rulers in each measurement area, use a photogrammetric system to take pictures of each measurement area, and analyze and obtain the spatial coordinate data of the measurement coding points in each measurement area relative to the measurement reference target in that area under the coordinate system of the photogrammetric system itself; Step 3: Using the measurement reference targets in each area as common points, transform the spatial coordinate data in the coordinate system of the photogrammetric system to the global measurement reference coordinate system through coordinate transformation, stitch together to obtain the complete point cloud data of the plane to be detected, and analyze to obtain the overall planar accuracy data of the plane to be detected. The photogrammetry system includes a crane, a pod, a camera, and a wireless control module. The pod is mounted on the underside of the crane via lifting lugs. An opening is provided at the bottom of the pod, and the camera is installed inside the pod with its lens and supplementary light extending outward through the opening. The wireless control module communicates with the camera.
2. The method for detecting the flatness of a large steel structure frame array according to claim 1, characterized in that: The hoisting box is made of wood or plastic.
3. The method for detecting the flatness of a large steel structure frame array according to claim 1, characterized in that: The spacing between adjacent photo-coded points is 800mm-1000mm.
4. The method for detecting the flatness of a large steel structure frame array according to claim 1, characterized in that: The measurement area is rectangular, with measurement reference targets at the four corners and the center of the measurement area.