Digital steel structure grid deflection monitoring method based on 3D laser scanning

Abstract

The present invention discloses a method for monitoring the deflection and deformation of a digital steel structure grid based on three-dimensional laser scanning, comprising the following steps: S1, formulating a scanning plan, determining a scanning route, and acquiring the shape of an actual grid; S2, splitting the grid into a plurality of beams and numbering them individually in sequence; S3, acquiring scanning data, streamlining a point cloud model, splitting the grid point cloud into point clouds of a plurality of beams, and naming each single beam separately; S4, constructing a comparison model, removing noise points, performing lightweight processing, and format conversion on a pre-compared beam point cloud model; S5, performing comparative analysis on single beam point cloud models of different periods, and acquiring deformation areas and numerical monitoring results; S6, compiling a grid deflection and deformation monitoring data table based on the monitoring results.

Description

Technical Field

[0001] The invention relates to the technical field of contactless digital steel structure roof grid deflection deformation monitoring, and in particular to a digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning. Background Art

[0002] With people's continuous pursuit of aesthetics and space usage, large-span grid structures with no or few columns and flexible spatial layout are increasingly being used in public buildings. However, due to the small number of vertical supports and large spans, grid deflection and deformation monitoring has become one of the most important technical means to grasp the safety status of grid structures. The traditional total station observation method cannot accurately and comprehensively reflect its overall deformation due to the limited setting of observation points. With the development of intelligent measurement technology, 3D laser scanning technology can realize point cloud model comparison and analysis through the high-precision point cloud model scanned, but due to the large area of ​​the grid and the large amount of data, it is difficult to quickly, efficiently, accurately and comprehensively obtain the deflection and deformation data of the steel structure. Summary of the invention

[0003] The purpose of the present invention is to provide a digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides a digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning, comprising the following steps:

[0005] S1. Develop a scanning plan, determine the scanning route, and obtain the actual grid shape;

[0006] S2, split the grid into several beams and number them separately in sequence;

[0007] S3, obtaining scanning data, simplifying the point cloud model, dividing the grid point cloud into point clouds of several beams, and naming the individual beams respectively;

[0008] S4, building a comparison model, removing noise, lightweighting and converting the format of the pre-compared beam point cloud model;

[0009] S5. Compare and analyze the point cloud models of single beams at different periods to obtain deformation areas and numerical monitoring results;

[0010] S6. Based on the monitoring results, prepare a grid deflection and deformation monitoring data table.

[0011] In a preferred embodiment, in step S1, a scanning plan is formulated, a scanning route is determined, and the actual grid shape is obtained, including:

[0012] S11. Conduct on-site survey based on the drawings and materials, and determine the scanning route according to the structural form. The scanning route is selected to scan in a circular manner first, supplement the internal area, and add scanning stations to the key areas to ensure that a complete model of the grid in the area can be obtained;

[0013] S12. Determine the scanning station positions on the scanning route according to the scanning route and the scanning radius of the scanner to ensure that the point cloud models at both ends of the grid, the middle area, and the key focus area are complete.

[0014] In a preferred embodiment, permanent targets are posted at both ends of each beam in the two end regions of the grid for later capture of points with the same name.

[0015] In a preferred embodiment, in step S3, the grid is split into a plurality of beams and numbered individually in sequence, including: splitting the grid into a plurality of beams in both the longitudinal and transverse directions, and numbering the main beams and the secondary beams in sequence.

[0016] In a preferred embodiment, in step S3, scanning data is acquired, the point cloud model is simplified, the grid point cloud is divided into point clouds of several beams, and the individual beams are named respectively, including:

[0017] S31, acquiring point cloud data station by station according to the scanning plan, including initial scanning point cloud data and later scanning point cloud data;

[0018] S32, using software to process the acquired initial scanning point cloud data and the later scanning point cloud data respectively, segmenting the redundant data, and retaining the grid point cloud;

[0019] S33. Segment the grid point cloud again, disassemble it with single beam as unit, name the single beam according to the number, and export the point cloud data of each beam into DXF format, rename and save.

[0020] In a preferred embodiment, in step S4, a comparison model is constructed, and noise removal, lightweight processing and format conversion are performed on the pre-compared beam point cloud model, including:

[0021] S41, import the pre-compared two scanning point cloud models into Geomagic software, select the isolated points in vitro, and delete them;

[0022] S42. Use the curvature sampling function to retain points in high curvature areas, reduce points in flat areas, ensure the point cloud density of curved components, reduce the point cloud density of straight areas, and completely and accurately retain the outer contour edges.

[0023] In a preferred embodiment, constructing the comparison model includes: encapsulating the initial scanning beam point cloud model, constructing a TIN grid model, and setting it as Reference; and setting the later scanning beam point cloud model as Text.

[0024] In a preferred embodiment, in step S5, a comparative analysis is performed on the point cloud models of a single beam at different times to obtain deformation areas and numerical monitoring results, including:

[0025] S51, using the automatic alignment command to align the initial scanning beam point cloud model with the later scanning beam point cloud model. If the automatic alignment fails, the permanent targets posted at both ends of each beam are used for manual alignment;

[0026] S52, perform 3D comparison and single point detection to obtain deformation areas and related values.

[0027] In a preferred embodiment, 3D comparison and single point detection are performed, including:

[0028] Perform 3D comparison on the superimposed initial scanning beam point cloud model and the later scanning beam point cloud model to generate a model deviation chromatogram;

[0029] According to the characteristics of the grid beam, a single-point detection position is selected to generate a single-point deviation value;

[0030] Generates deflection deviation lists and diagrams.

[0031] In a preferred embodiment, the permanent target adopts a black and white target, and a cross target line is set in the center of the black and white target. When manually grasping and aligning, the cross target lines of the initial scanning beam point cloud model and the later scanning beam point cloud model are overlapped.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The present invention uses two measured point cloud comparison methods to replace the traditional point cloud model and design BIM model comparison method, which can directly obtain the actual grid shape and the actual deformation, rather than the theoretical and actual deviation values ​​between the design BIM model and the point cloud model. The deformation range and deformation value of the steel structure grid can be quickly determined by point cloud comparison;

[0034] 2. The present invention abandons the traditional large-area grid point cloud comparison, divides the point cloud of the large-area grid into point clouds of several beams, and focuses on the comparison of single beam point cloud models at different periods, which not only helps to improve the accuracy, intuitiveness and effectiveness of monitoring data, but also greatly reduces the single data processing volume and improves the processing speed;

[0035] 3. Lightweight the components, that is, perform curvature sampling on the point cloud model, that is, retain the arc curve segments or reduce the point cloud density in a small part, and reduce the point cloud density in the straight area, so as to reduce data memory and improve processing speed.

[0036] 4. When performing two-phase point cloud fitting, if the feature points are not easy to capture, resulting in poor alignment effect, point cloud misalignment deviation, thus affecting data quality. The present invention posts permanent targets at both ends of the beam for fitting the two ends of the beam. This method is easy to operate and has high precision, and can quickly obtain the deformation area and value of a single beam. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of the digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning of the present invention;

[0038] Figure 2 It is a schematic diagram of the permanent target of the present invention. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present invention are described clearly and completely below. The embodiments of the present invention and all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] like Figure 1-2 As shown, the digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning according to the preferred embodiment of the present invention comprises the following steps:

[0041] Step S1, formulate a scanning plan, determine the scanning route, and obtain the actual grid shape.

[0042] Specifically, formulate a scanning plan, determine the scanning route, and obtain the actual grid shape, including:

[0043] Step S11, conduct on-site survey based on the drawings and materials, and determine the scanning route according to the structural form. The scanning route is selected to scan in a circular manner first to supplement the internal area. For key areas of concern, such as areas with large deflection values ​​of the grid calculated by design, additional scanning stations should be set up to ensure that a complete model of the grid in the key area can be obtained.

[0044] Step S12: Determine the scanning station position on the scanning route according to the scanning route and the scanning radius of the scanner to ensure that the point cloud models at both ends of the grid, the middle area, and the key focus area are complete and of qualified quality.

[0045] Step S13: When the grid is too high and the scanning distance is not sufficient, it should be set up on an elevator to collect high-quality grid data as close as possible.

[0046] Step S14: Post permanent targets on each beam at both ends of the grid, such as Figure 2 The black and white target 201 shown is convenient for later grabbing of the same-named points.

[0047] Step S2: split the grid into a plurality of beams and number them individually in sequence.

[0048] Specifically, step S2 includes: splitting the grid into a plurality of beams in both the longitudinal and transverse directions, and numbering the main beams and the secondary beams in sequence. In the later stage, all the main beams are compared and analyzed, and only the two ends and the middle part of the secondary beams can be compared and analyzed as needed, or all of them can be compared and analyzed.

[0049] Step S3, obtaining scanning data, simplifying the point cloud model, dividing the grid point cloud into point clouds of several beams, and naming the individual beams respectively.

[0050] Specifically, step S3 includes:

[0051] Step S31, acquiring point cloud data station by station according to the scanning plan, including initial scanning point cloud data and later scanning point cloud data, to ensure data integrity;

[0052] Step S32, using software to process the acquired initial scanning point cloud data and the later scanning point cloud data respectively, segmenting the redundant data, and retaining the grid point cloud;

[0053] Step S33, segment the grid point cloud again, disassemble it with single beam as unit, name the single beam according to the number, and export the point cloud data of each beam into DXF format, rename and save.

[0054] Step S4: construct a comparison model, remove noise, perform lightweight processing and format conversion on the pre-compared beam point cloud model.

[0055] Specifically, step S4 includes:

[0056] Step S41, import the pre-compared two scan point cloud models into Geomagic software, select and delete isolated points in vitro to reduce the influence of redundant points;

[0057] Step S42, use the curvature sampling function to retain points in high curvature areas and reduce points in flat areas, which not only ensures the point cloud density of the curved component part, but also reduces the point cloud density of the straight area, and completely and accurately retains the outer contour edge, and reduces the number of points and data memory.

[0058] The comparison model is constructed, including: encapsulating the initial scanning beam point cloud model, constructing a TIN grid model, and setting it as Reference; and setting the later scanning beam point cloud model as Text.

[0059] Step S5: Compare and analyze the point cloud models of the single beam at different periods to obtain the deformation area and numerical monitoring results.

[0060] Specifically, step S5 includes:

[0061] Step S51, using the automatic alignment command to align the initial scanning beam point cloud model and the later scanning beam point cloud model. If the automatic alignment fails, use the permanent targets posted at both ends of each beam to manually grab and align.

[0062] Furthermore, the permanent target adopts a black and white target, and a cross target line is set in the center of the black and white target. When manually grasping and aligning, the cross target lines of the initial scanning beam point cloud model and the later scanning beam point cloud model are overlapped.

[0063] Step S52: perform 3D comparison and single point detection to obtain the deformation area and related values.

[0064] Among them, 3D comparison and single point detection are performed, including:

[0065] Perform 3D comparison on the superimposed initial scanning beam point cloud model and the later scanning beam point cloud model to generate a model deviation chromatogram;

[0066] According to the characteristics of the grid beam, a single-point detection position is selected to generate a single-point deviation value;

[0067] Generates deflection deviation lists and diagrams.

[0068] Step S6: Based on the monitoring results, compile a grid deflection deformation monitoring data table.

[0069] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital steel structure grid deflection deformation monitoring method based on three-dimensional laser scanning, characterized in that: The steps include: S1. Develop a scanning plan, determine the scanning route, and obtain the actual grid shape; S2, split the grid into several beams and number them separately in sequence; S3, obtain scanning data, simplify the point cloud model, divide the grid point cloud into point clouds of several beams, and name the individual beams respectively; S4, building a comparison model, removing noise, lightweighting and converting the format of the pre-compared beam point cloud model; S5. Compare and analyze the point cloud models of single beams at different periods to obtain deformation areas and numerical monitoring results; S6. Based on the monitoring results, compile a grid deflection monitoring data table; Among them, permanent targets are posted at the ends of each beam at both ends of the grid for later capture of the same-named points; In step S2, the grid is split into a plurality of beams and numbered separately in sequence, including: splitting the grid into a plurality of beams in both the longitudinal and transverse directions, and numbering the main beams and the secondary beams in sequence; In step S5, a comparative analysis is performed on the point cloud models of the single beam at different times to obtain the deformation area and numerical monitoring results, including: S51, using the automatic alignment command to align the initial scanning beam point cloud model with the later scanning beam point cloud model. If the automatic alignment fails, the permanent targets posted at both ends of each beam are used for manual alignment; S52, performing 3D comparison and single point detection to obtain deformation areas and related values; Perform 3D comparison and single point inspection, including: Perform 3D comparison on the superimposed initial scanning beam point cloud model and the later scanning beam point cloud model to generate a model deviation chromatogram; According to the characteristics of the grid beam, a single-point detection position is selected to generate a single-point deviation value; Generates deflection deviation lists and diagrams.

2. The method for monitoring the deflection of a digital steel structure grid based on three-dimensional laser scanning according to claim 1 is characterized in that: In step S1, a scanning plan is formulated, a scanning route is determined, and the actual grid shape is obtained, including: S11. Conduct on-site survey based on the drawings and materials, and determine the scanning route according to the structural form. The scanning route is selected to first perform circular scanning to supplement the internal area, and add scanning stations to the key areas to ensure that a complete model of the grid in the key areas can be obtained; S12. Determine the scanning station positions on the scanning route according to the scanning route and the scanning radius of the scanner to ensure that the point cloud models at both ends of the grid, the middle area, and the key focus area are complete.

3. The method for monitoring the deflection of a digital steel structure grid based on three-dimensional laser scanning according to claim 1 is characterized in that: In step S3, the scanning data is obtained, the point cloud model is simplified, the grid point cloud is divided into point clouds of several beams, and the individual beams are named respectively, including: S31, acquiring point cloud data station by station according to the scanning plan, including initial scanning point cloud data and later scanning point cloud data; S32, using software to process the acquired initial scanning point cloud data and the later scanning point cloud data respectively, segmenting the redundant data, and retaining the grid point cloud; S33. Segment the grid point cloud again, disassemble it with single beam as unit, name the single beam according to the number, and export the point cloud data of each beam into DXF format, rename and save.

4. The method for monitoring the deflection of a digital steel structure grid based on three-dimensional laser scanning according to claim 3 is characterized in that: In step S4, a comparison model is constructed, and noise removal, lightweight processing and format conversion are performed on the pre-compared beam point cloud model, including: S41, import the pre-compared two scanning point cloud models into Geomagic software, select the isolated points in vitro, and delete them; S42. Use the curvature sampling function to retain points in high curvature areas, reduce points in flat areas, ensure the point cloud density of curved components, reduce the point cloud density of straight areas, and completely and accurately retain the outer contour edges.

5. The method for monitoring the deflection of a digital steel structure grid based on three-dimensional laser scanning according to claim 4 is characterized in that: Constructing a comparison model includes: encapsulating the initial scanning beam point cloud model, constructing a TIN grid model, and setting it as Reference; and setting the later scanning beam point cloud model as Text.

6. The method for monitoring the deflection of a digital steel structure grid based on three-dimensional laser scanning according to claim 1 is characterized in that: The permanent target adopts a black and white target, and a cross target line is set in the center of the black and white target. When manually grasping and aligning, the cross target lines of the initial scanning beam point cloud model and the later scanning beam point cloud model are overlapped.

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