CN214670726U - Bridge anticollision wall disease data acquisition modeling system - Google Patents
Bridge anticollision wall disease data acquisition modeling system Download PDFInfo
- Publication number
- CN214670726U CN214670726U CN202121001754.0U CN202121001754U CN214670726U CN 214670726 U CN214670726 U CN 214670726U CN 202121001754 U CN202121001754 U CN 202121001754U CN 214670726 U CN214670726 U CN 214670726U
- Authority
- CN
- China
- Prior art keywords
- camera
- modeling system
- image
- collision wall
- data acquisition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Image Processing (AREA)
Abstract
The utility model belongs to the technical field of the bridge monitoring, concretely relates to bridge anticollision wall disease data acquisition modeling system. A bridge anti-collision wall disease data acquisition modeling system comprises a three-dimensional image acquisition device, wherein the three-dimensional image acquisition device comprises an inner side camera, a top surface camera and an outer side camera; the three-dimensional model generation system comprises an image modeling system, wherein the inner side camera, the top side camera and the outer side camera are respectively electrically connected with the image modeling system, and the image modeling system is used for generating a three-dimensional model. The utility model provides a can gather the trilateral image of anticollision wall and generate three-dimensional model's bridge anticollision wall disease data acquisition modeling system through the image modeling system.
Description
Technical Field
The utility model belongs to the technical field of the bridge monitoring, concretely relates to bridge anticollision wall disease data acquisition modeling system.
Background
The bridge anti-collision wall is used as an accessory structure of a bridge, and not only is an important safety shield, but also the line shape and the surface finish of the bridge anti-collision wall directly influence the beauty and the quality of the bridge. Because the anti-collision wall is directly exposed in the natural environment and is corroded, neutralized and damaged by acid, alkali, particularly salt snow-melting agents and other harmful substances, cracks, concrete peeling, rib exposure and other diseases often occur within several years, the service life and the appearance environment of the anti-collision wall are affected, the steel bars of the anti-collision wall are seriously corroded, the safety performance of the anti-collision wall can be weakened, and potential safety hazards are formed, so that a bridge operation management unit needs to regularly maintain the anti-collision wall. Before the anti-collision wall is maintained, data acquisition is required to be carried out on the diseases existing in the anti-collision wall, and data support is provided for maintenance.
At present, most of data acquisition work of bridge anti-collision wall diseases in China adopts manual acquisition. The manual collection mode has the following defects: firstly, the acquisition efficiency is low, the cost is high, and the method is uneconomical; secondly, the acquisition process is often influenced by personal subjective quality (such as operation level, responsibility and the like) of operators, and the acquired image data is inaccurate and incomplete; thirdly, manual collection is usually reserved in the form of pictures and images, information is relatively fragmented, and later-stage searching is inconvenient; fourth, when crashproof wall outside disease data acquisition, the aerial work is dangerous great, and the potential safety hazard is high.
SUMMERY OF THE UTILITY MODEL
In order to solve the above-mentioned problem that prior art exists, the utility model aims to provide a can gather the trilateral image of anticollision wall and generate three-dimensional model's bridge anticollision wall disease data acquisition modeling system through the image modeling system.
The utility model discloses the technical scheme who adopts does:
a bridge anti-collision wall disease data acquisition modeling system comprises a three-dimensional image acquisition device, wherein the three-dimensional image acquisition device comprises an inner side camera positioned on the inner side of an anti-collision wall, a top surface camera positioned on the upper side of the anti-collision wall and an outer side camera positioned on the outer side of the anti-collision wall; the three-dimensional model generation system comprises an image modeling system, wherein the inner side camera, the top side camera and the outer side camera are respectively electrically connected with the image modeling system, and the image modeling system is used for generating a three-dimensional model.
The inboard camera is located the anticollision wall inboard, and the top surface camera is located the anticollision wall top, and the outside camera is located the anticollision wall outside to the trilateral homoenergetic of anticollision wall is shot, shoots inconvenient circumstances when having avoided manual operation. Under the condition of three-side shooting, the image modeling system can generate a three-dimensional model according to three-side images, collected data are expressed in a three-dimensional model form with space geometric information and surface texture information, and effective data support can be provided for disease treatment.
As the utility model discloses an optimized scheme, three-dimensional image acquisition device still includes the base, is connected with interior pole setting on the base, and the other end of interior pole setting is connected with the horizontal pole, and the other end of horizontal pole is connected with outer pole setting, and inboard camera is installed in interior pole setting, and the top surface camera is installed on the horizontal pole, and outside camera is installed in outer pole setting. Interior pole setting is located the anticollision wall inboard, and the horizontal pole is located the anticollision wall top, and outer pole setting is located the anticollision wall outside to inboard camera, top surface camera and outside camera are all installing definite position, and the convenience is gathered the image to each side of anticollision wall.
As the utility model discloses a preferred scheme, the gyro wheel is installed to the bottom of base, installs actuating mechanism on the base, and actuating mechanism's output shaft is connected with the pivot of one of them gyro wheel. In the process of image acquisition, the driving mechanism drives the base to move, so that the inner side camera, the top-out camera and the outer side camera can continuously shoot the anti-collision wall in the moving process, and the image information of each part of the anti-collision wall can be acquired.
As the utility model discloses a preferred scheme, actuating mechanism includes the motor, and the output shaft of motor has the reduction gear, and the output shaft of reduction gear is connected with the pivot of gyro wheel, and motor and reduction gear are installed on the base. The motor drives the speed reducer to act, and the speed reducer drives the roller to rotate, so that the base can move along the anti-collision wall.
As the utility model discloses an optimized scheme, interior pole setting includes the loop bar, and the loop bar is connected on the base, and the loop bar endotheca is equipped with the lifter, and the loop bar passes through screw locking with the lifter, and the horizontal pole is connected with the lifter. According to the height of anticollision wall, can adjust the height of interior pole setting, avoid the top of horizontal pole and anticollision wall to interfere. When the lifting rod is adjusted, the lifting rod is pulled to a determined position from the inside of the loop rod, and then the loop rod and the lifting rod are locked by a screw.
As the utility model discloses an optimal scheme, all be provided with the slide rail in interior pole setting, horizontal pole and the outer pole setting, inboard camera cover is located on the slide rail of interior pole setting and through the screw locking, and top surface camera cover is located on the slide rail of horizontal pole and through the screw locking, and outside camera cover is located on the slide rail of outer pole setting and through the screw locking. The inner side camera, the top surface camera and the outer side camera can move on the corresponding slide rails, so that the positions of the cameras can be accurately adjusted, and the cameras can shoot complete pictures of the surface of the anti-collision wall.
The utility model has the advantages that:
the utility model discloses an inboard camera is located the anticollision wall inboard, and the top surface camera is located the anticollision wall top, and the outside camera is located the anticollision wall outside to the trilateral homoenergetic of anticollision wall is shot, shoots inconvenient circumstances when having avoided manual operation. Under the condition of three-side shooting, the image modeling system can generate a three-dimensional model according to three-side images, collected data are expressed in a three-dimensional model form with space geometric information and surface texture information, and effective data support can be provided for disease treatment.
Drawings
Fig. 1 is a schematic structural diagram of the present invention;
fig. 2 is a flow chart of the method of the present invention.
In the figure, 1-collision wall; 2-an inside camera; 3-a top camera; 4-an outside camera; 5-a base; 6-inner vertical rod; 7-a cross bar; 8-outer vertical rod; 9-a drive mechanism; 51-a roller; 61-loop bar; 62-a lifting rod; 91-a motor; 92-speed reducer.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present invention, and should not be construed as limiting the present invention.
As shown in fig. 1, the bridge anti-collision wall disease data acquisition modeling system of the embodiment includes a three-dimensional image acquisition device, where the three-dimensional image acquisition device includes an inside camera 2 located inside an anti-collision wall 1, a top camera 3 located on the upper side of the anti-collision wall 1, and an outside camera 4 located outside the anti-collision wall 1; the three-dimensional model generation system further comprises an image modeling system, wherein the inner side camera 2, the top side camera 3 and the outer side camera 4 are respectively and electrically connected with the image modeling system, and the image modeling system is used for generating a three-dimensional model.
The image modeling is a technical method for acquiring images of a measured object by a calibrated measuring or non-measuring digital camera and reducing the original surface morphology of the object by utilizing basic theoretical knowledge of photogrammetry and related software and hardware. The image modeling is a non-contact measurement technology without contacting with an object to be measured in the data acquisition process, then the acquired image information is imported into professional analysis software, and finally three-dimensional space coordinates and other information of all points in the image are solved. By expressing the image data of the anti-collision wall 1 in the form of a three-dimensional model with space geometric information and surface texture information, effective data support can be provided for disease treatment.
The utility model discloses a system simple structure, reliable and stable, maneuverability is strong. The construction method is simple to operate, the data of three surfaces are acquired at one time, and the acquisition efficiency is obviously improved. The utility model discloses avoided artifical safety risk who gathers the aerial work, the safe effect is showing. The utility model discloses make cost of labor greatly reduced, practice thrift the fund.
Wherein, three-dimensional image acquisition device still includes base 5, is connected with interior pole setting 6 on the base 5, and the other end of interior pole setting 6 is connected with horizontal pole 7, and the other end of horizontal pole 7 is connected with outer pole setting 8, and inboard camera 2 is installed on interior pole setting 6, and top surface camera 3 is installed on horizontal pole 7, and outside camera 4 is installed on outer pole setting 8. Interior pole setting 6 is located 1 inboards of crashproof wall, and horizontal pole 7 is located 1 tops of crashproof wall, and outer pole setting 8 is located the 1 outside of crashproof wall to inboard camera 2, top surface camera 3 and outside camera 4 are all installing the definite position, and the convenience is carried out image acquisition to 1 each side of crashproof wall.
In order to control conveniently the utility model discloses a system is along crashproof wall 1 automatic movement, gyro wheel 51 is installed to the bottom of base 5, installs actuating mechanism 9 on the base 5, and actuating mechanism 9's output shaft is connected with one of them gyro wheel 51's pivot. In the process of image acquisition, the driving mechanism 9 drives the base 5 to move, so that the inner side camera 2, the top-out camera and the outer side camera 4 can continuously photograph the anti-collision wall 1 in the moving process, and the image information of all positions of the anti-collision wall 1 can be acquired.
The driving mechanism 9 includes a motor 91, an output shaft of the motor 91 is connected to a speed reducer 92, an output shaft of the speed reducer 92 is connected to a rotating shaft of the roller 51, and the motor 91 and the speed reducer 92 are mounted on the base 5. The motor 91 drives the decelerator 92 to operate, and the decelerator 92 drives the roller 51 to rotate, so that the base 5 can move along the impact wall 1.
In order to adjust the height of the cross rod 7 conveniently, the inner vertical rod 6 comprises a sleeve rod 61, the sleeve rod 61 is connected to the base 5, a lifting rod 62 is sleeved in the sleeve rod 61, the sleeve rod 61 and the lifting rod 62 are locked through screws, and the cross rod 7 is connected with the lifting rod 62. According to the height of crashproof wall 1, can adjust the height of interior pole setting 6, avoid horizontal pole 7 to interfere with the top of crashproof wall 1. During adjustment, the lifting rod 62 is pulled to a certain position from the inside of the sleeve rod 61, and the sleeve rod 61 and the lifting rod 62 are locked by a screw.
In order to adjust the positions of the cameras conveniently, the inner vertical rod 6, the cross rod 7 and the outer vertical rod 8 are provided with slide rails, the inner side camera 2 is sleeved on the slide rail of the inner vertical rod 6 and locked through screws, the top side camera 3 is sleeved on the slide rail of the cross rod 7 and locked through screws, and the outer side camera 4 is sleeved on the slide rail of the outer vertical rod 8 and locked through screws. The inside camera 2, the top surface camera 3 and the outside camera 4 can all move on corresponding slide rails, so that the positions of the cameras can be accurately adjusted, and the cameras can shoot complete pictures of the surface of the anti-collision wall 1.
As shown in fig. 2, a method for collecting and modeling disease data of a bridge anti-collision wall comprises the following steps:
s1: the inner side camera 2, the top side camera 3 and the outer side camera 4 collect three-side images of the anti-collision wall 1; the inner side camera 2, the top side camera 3 and the outer side camera 4 move along the anti-collision wall 1 and continuously acquire three-side images; the overlapping degree of the images shot by the adjacent cameras is not less than 60%.
The overlapping degree of the images shot by the adjacent cameras is not less than 60%. In the image modeling process, the overlapping degree plays a decisive role. The higher overlapping degree can reduce the image matching difficulty, improve the precision of redundant observation and results, and provide detail texture for the side surface of the structure. The overlapping degree refers to the ratio of the ground overlapping part of two adjacent images to the breadth of a single image.
S2: image preprocessing: the equipment that the data acquisition device gathered prefabricated component image data is little single-phase camera, and little single-phase camera exists machining error and assembly error for non-measuration digital camera, can have certain geometric deformation during the image information of gathering, can influence the precision of the empty three calculations of later stage modeling, consequently before utilizing image modeling technique to establish the component model, need carry out the preliminary treatment to the image data of gathering, carry out the preliminary treatment to the image of gathering and mainly include image distortion correction and image dodging even look processing.
S3: data import and air-to-three calculation: after the image data is imported, the space-three calculation is started, and generally comprises the processes of image feature matching, multi-view image joint adjustment, dense matching and the like, and finally a high-density three-dimensional point cloud model is generated. The aerial triangulation is called aerial triangulation computation for short, and is an important technical step in oblique photogrammetry. The aerial triangulation is a process of solving the external orientation element and the encryption point of an image by combining the relation between image data and a corresponding shot object and the coordinates of a control point based on the theory of photogrammetry.
After image matching and joint adjustment are completed, sparse feature points between images and external orientation elements of the images are obtained, and information required for building a three-dimensional point cloud model cannot be formed by means of the sparse feature points. Therefore, dense matching between images is required, and the dense matching is mainly to obtain more object point space three-dimensional coordinates between two images by using front intersection under the condition that the external orientation elements of the images are known.
S4: constructing a TIN model: after the image dense matching is completed, a large amount of dense point cloud data is generated, and irregular triangular meshes of different levels of details are constructed through the dense point cloud data, wherein the irregular triangular meshes are called TIN models for short. The denser area of the triangular net in the TIN model represents that the detail characteristics of the area are rich, and the sparser area of the triangular net represents that the detail characteristics of the area are not obvious. And the three-dimensional mesh model is packaged to produce a component three-dimensional white model.
S5: texture mapping: the surface of the three-dimensional white model which is established through encapsulation has no texture information, and real surface information of an object cannot be displayed, so that the model needs to be subjected to texture mapping treatment after the white model is established, the essence is that corresponding two-dimensional image information is selected from image data according to the spatial shape and the position of the white model for texture fitting, and the texture mapping technology is usually applied to a model with fine and rich surface texture of the object in reverse three-dimensional modeling.
The present invention is not limited to the above-mentioned optional embodiments, and any other products in various forms can be obtained by anyone under the teaching of the present invention, and any changes in the shape or structure thereof, all the technical solutions falling within the scope of the present invention, are within the protection scope of the present invention.
Claims (6)
1. A bridge anti-collision wall disease data acquisition modeling system is characterized by comprising a three-dimensional image acquisition device, wherein the three-dimensional image acquisition device comprises an inner side camera (2) positioned on the inner side of an anti-collision wall (1), a top surface camera (3) positioned on the upper side of the anti-collision wall (1) and an outer side camera (4) positioned on the outer side of the anti-collision wall (1); the three-dimensional model generation system is characterized by further comprising an image modeling system, wherein the inner side camera (2), the top surface camera (3) and the outer side camera (4) are electrically connected with the image modeling system respectively, and the image modeling system is used for generating a three-dimensional model.
2. The bridge anti-collision wall disease data acquisition modeling system according to claim 1, characterized in that the three-dimensional image acquisition device further comprises a base (5), an inner vertical rod (6) is connected to the base (5), a cross rod (7) is connected to the other end of the inner vertical rod (6), an outer vertical rod (8) is connected to the other end of the cross rod (7), the inner camera (2) is installed on the inner vertical rod (6), the top camera (3) is installed on the cross rod (7), and the outer camera (4) is installed on the outer vertical rod (8).
3. The bridge anti-collision wall disease data acquisition modeling system according to claim 2, characterized in that rollers (51) are installed at the bottom of the base (5), a driving mechanism (9) is installed on the base (5), and an output shaft of the driving mechanism (9) is connected with a rotating shaft of one of the rollers (51).
4. The bridge anti-collision wall disease data acquisition modeling system according to claim 3, characterized in that the driving mechanism (9) comprises a motor (91), an output shaft of the motor (91) is connected with a speed reducer (92), an output shaft of the speed reducer (92) is connected with a rotating shaft of the roller (51), and the motor (91) and the speed reducer (92) are installed on the base (5).
5. The bridge anti-collision wall disease data acquisition modeling system according to claim 2, characterized in that the inner vertical rod (6) comprises a loop bar (61), the loop bar (61) is connected to the base (5), a lifting rod (62) is sleeved in the loop bar (61), the loop bar (61) and the lifting rod (62) are locked through screws, and the cross rod (7) is connected with the lifting rod (62).
6. The bridge anti-collision wall disease data acquisition modeling system according to any one of claims 2 to 5, wherein sliding rails are arranged on the inner vertical rod (6), the cross rod (7) and the outer vertical rod (8), the inner side camera (2) is sleeved on the sliding rails of the inner vertical rod (6) and locked through screws, the top side camera (3) is sleeved on the sliding rails of the cross rod (7) and locked through screws, and the outer side camera (4) is sleeved on the sliding rails of the outer vertical rod (8) and locked through screws.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202121001754.0U CN214670726U (en) | 2021-05-11 | 2021-05-11 | Bridge anticollision wall disease data acquisition modeling system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202121001754.0U CN214670726U (en) | 2021-05-11 | 2021-05-11 | Bridge anticollision wall disease data acquisition modeling system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN214670726U true CN214670726U (en) | 2021-11-09 |
Family
ID=78487708
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202121001754.0U Active CN214670726U (en) | 2021-05-11 | 2021-05-11 | Bridge anticollision wall disease data acquisition modeling system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN214670726U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113066175A (en) * | 2021-05-11 | 2021-07-02 | 中国五冶集团有限公司 | Bridge anti-collision wall disease data acquisition modeling system and method |
| CN114979480A (en) * | 2022-05-23 | 2022-08-30 | 广州冠粤路桥检测有限公司 | Bridge disease shooting device and image distortion correction method |
-
2021
- 2021-05-11 CN CN202121001754.0U patent/CN214670726U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113066175A (en) * | 2021-05-11 | 2021-07-02 | 中国五冶集团有限公司 | Bridge anti-collision wall disease data acquisition modeling system and method |
| CN114979480A (en) * | 2022-05-23 | 2022-08-30 | 广州冠粤路桥检测有限公司 | Bridge disease shooting device and image distortion correction method |
| CN114979480B (en) * | 2022-05-23 | 2024-03-19 | 广州冠粤路桥检测有限公司 | Bridge disease shooting device and image distortion correction method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2021068848A1 (en) | Tunnel structure disease multi-scale measurement and intelligent diagnosis system and method | |
| CN214670726U (en) | Bridge anticollision wall disease data acquisition modeling system | |
| AU2019222803A1 (en) | Volume measurement apparatus and method | |
| Yu et al. | 3D reconstruction of road surfaces using an integrated multi-sensory approach | |
| CN109029277A (en) | A kind of tunnel deformation monitoring system and method | |
| CN110232736A (en) | A kind of down-hole combined mining working three-dimensional scenic fast construction method | |
| CN201977794U (en) | Automatic height measuring system | |
| CN106989683B (en) | A kind of shield tail clearance of shield machine vision measuring method | |
| CN107796331B (en) | Soil surface form monitoring device, the monitoring of soil surface form and data analysing method based on push-broom type LiDAR | |
| CN111006601A (en) | Key technology of three-dimensional laser scanning in deformation monitoring | |
| CN103247056B (en) | Human bone articular system three-dimensional model-bidimensional image spatial registration method | |
| CN103227888B (en) | A kind of based on empirical mode decomposition with the video stabilization method of multiple interpretational criteria | |
| Li et al. | Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test | |
| CN110666150A (en) | Metal ingot casting slag skimming system and method | |
| CN110111412A (en) | A kind of acquisition methods of tunnel excavation face country rock point cloud model | |
| CN111768417B (en) | Railway wagon overrun detection method based on monocular vision 3D reconstruction technology | |
| CN116399302B (en) | Method for monitoring dynamic compaction settlement in real time based on binocular vision and neural network model | |
| WO2023207257A1 (en) | Tailing dam surface deformation patrol method based on rail-mounted rail robot | |
| CN115452723A (en) | Bridge defect detection equipment and defect identification method for bridge engineering | |
| CN107819268A (en) | The control method and device of laser power in 3 D scanning system | |
| CN111145220B (en) | Tunnel target track tracking method based on visual information | |
| CN114279324B (en) | All-dimensional intelligent detection method for appearance quality of prefabricated part | |
| CN106895795A (en) | Monocular vision measurement apparatus and its 3 d modeling system | |
| CN114659463B (en) | Plant phenotype acquisition device and acquisition method thereof | |
| CN110047146B (en) | Error correction method based on single revolving body image 3D restoration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |