A vision-based verticality detection system for arch bridge towers

Abstract

The present invention discloses a vision-based arch bridge tower verticality detection system, comprising: a visual information acquisition module, which is used to perform vertical climbing visual imaging of the front and side of the arch bridge tower through an unmanned aerial vehicle equipped with an imaging device, and simultaneously record the status data of the unmanned aerial vehicle and the imaging device; an imaging analysis module, which is used to select a coordinate reference point on the climbing visual image, convert the reference point to the same image coordinate system according to the image spatial resolution and the status data of the unmanned aerial vehicle, and then calculate the verticality of the arch bridge tower according to the relative coordinates of the reference point. The present invention realizes the automated and efficient measurement of the verticality of the arch bridge tower by combining unmanned aerial vehicle technology and image processing algorithms. It provides an innovative solution for bridge inspection and maintenance, which helps to improve the safety and reliability of bridge structures.

Description

Technical Field

[0001] The invention belongs to the technical field of engineering measurement, and in particular relates to a vision-based verticality detection system for an arch bridge tower. Background Art

[0002] In the field of civil engineering, arch bridges are a common bridge structure, and their stability and safety are crucial to traffic and public safety. The verticality of arch bridge towers is one of the key indicators for evaluating their structural integrity and construction quality. Traditional verticality detection methods, such as using theodolites or total stations, usually rely on manual operation, which is not only inefficient but also difficult to achieve high-precision measurements, especially in complex construction environments.

[0003] With the development of drone technology, drones have begun to be used for bridge inspection, providing a new means of data collection. However, existing drone inspection technology still faces challenges in handling accurate measurements in dynamic environments. For example, small offsets and rotations of drones during flight may cause imaging deviations, affecting the accuracy of measurement results. In addition, existing technologies often lack sufficient accuracy and automation in image processing and data analysis, which limits their application in actual engineering, resulting in less application of drone visual inspection in existing arch bridge tower verticality inspection projects. Summary of the invention

[0004] In view of this, the purpose of the present invention is to propose a vision-based arch bridge tower verticality detection system, which can realize the automatic and efficient measurement of the verticality of the arch bridge tower by combining drone technology and image processing algorithms. This method provides an innovative solution for bridge inspection and maintenance, and helps to improve the safety and reliability of bridge structures.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] The present invention provides a visual-based arch bridge tower verticality detection system, comprising:

[0007] The visual information acquisition module is used to use the imaging equipment carried by the drone to perform vertical climbing visual imaging on the front and sides of the arch bridge tower, and to record the status data of the drone and the imaging equipment at the same time;

[0008] The imaging analysis module is used to select coordinate reference points on the climbing visual image, convert the reference points to the same image coordinate system according to the image spatial resolution and the status data of the drone, and then calculate the verticality of the arch bridge tower according to the relative coordinates of the reference points.

[0009] Preferably, the visual information acquisition module includes:

[0010] The UAV equipment is used to perform vertical climbing action relative to the arch bridge tower according to the control command and record the state parameters of the UAV, wherein the state parameters include the relative coordinate position of the UAV and the deflection angle of the UAV;

[0011] Imaging equipment, used to collect images of the arch bridge tower while the UAV is performing vertical climbing actions;

[0012] A distance detection unit is used to detect the vertical distance between the drone and the arch bridge tower;

[0013] The laser marking unit is a cross-line laser emitting device mounted on the UAV. The up-down direction of the cross-line laser is perpendicular to the horizontal direction of the UAV, and the left-right direction of the cross-line laser is perpendicular to the up-down direction of the UAV.

[0014] Preferably, the visual information acquisition module performs the following operations:

[0015] The initial image information of the environment around the UAV equipment is obtained through the imaging device, and the specific position of the arch bridge tower is determined based on the initial image information and the preset target graphic features;

[0016] Perform surround image acquisition on the arch bridge tower, and determine the position of the symmetry axis of the front or side image of the arch bridge tower based on the image acquisition result analysis;

[0017] The UAV is adjusted to a position close to the ground when it is aligned with the symmetry axis, and the distance between the UAV and the arch bridge tower is adjusted according to the distance detection result fed back by the distance detection unit;

[0018] After the imaging device carried by the drone is aligned with the symmetry axis of the arch bridge tower, the drone is controlled to climb in the vertical direction, and continuous imaging is performed through the imaging device, while the state parameters of the drone are recorded.

[0019] Preferably, the imaging analysis module performs the following steps:

[0020] Based on the arch bridge tower image collected by the imaging device, the cross laser feature retained in the arch bridge tower image is analyzed and determined;

[0021] The multi-frame arch bridge tower images are linearly aligned and stitched in the longitudinal direction based on the cross laser feature longitudinal laser to correct the image deflection caused by the movement offset of the drone;

[0022] Analyze the verticality of the arch bridge tower based on the overall image after splicing.

[0023] Preferably, the imaging analysis module further performs:

[0024] Determine the first image taken by the drone at the bottom of the arch bridge tower And the first image The corresponding first imaging coordinate system ,in Indicates taking the first image The distance between the camera and the arch bridge tower, Indicates the camera rotation angle, Indicates the camera position;

[0025] Determine the second image taken by the drone at the bottom of the arch bridge tower And the second image The corresponding second imaging coordinate system ,in Indicates taking the second image The distance between the camera and the arch bridge tower, Indicates the camera rotation angle, Indicates the camera position;

[0026] Select a feature point on the top of the arch bridge tower as the first reference point , select a feature point at the bottom of the arch bridge tower as the second reference point ;

[0027] The edge features of the arch bridge tower in the first image and the second image are extracted by image processing technology, and the pixel length of the standard section of the arch bridge tower is determined according to the extraction results;

[0028] Based on the known actual length of the standard section and the determined pixel length of the standard section in the first image and the second image, the spatial resolution of the first image and the second image are calculated and determined respectively. , , where the spatial resolution is the ratio of the actual length to the pixel length;

[0029] The second reference point is calculated based on the pinhole imaging principle and the spatial resolution of the first image and the second image. In the preset coordinate system The coordinate position of , then:

[0030]

[0031]

[0032] Based on coordinate location And the position offset of the drone during imaging, calculate the second reference point In the first imaging coordinate system Coordinates in ,in:

[0033]

[0034]

[0035] in, as well as Respectively represent the camera coordinate positions when the camera is shooting at the bottom and top;

[0036] Calculate the verticality of the arch bridge tower:

[0037]

[0038] in, Indicates the verticality of the arch bridge tower.

[0039] The present invention has achieved at least the following beneficial effects:

[0040] 1. By combining drone technology and image processing algorithms, the verticality of arch bridge towers can be measured automatically and efficiently. This method provides an innovative solution for bridge inspection and maintenance, helping to improve the safety and reliability of bridge structures.

[0041] 2. The application of laser marking unit not only improves the feature recognition and positioning accuracy in the image acquisition process, but also provides effective assistance for the navigation and shooting of UAVs in complex environments, which is conducive to the detection of tall structures such as arch bridge towers.

[0042] 3. Through the cross laser active marking method, precise image feature recognition, alignment splicing and verticality analysis, the verticality of the arch bridge tower can be measured efficiently and accurately. This method not only improves the degree of automation of measurement, but also reduces the error of manual operation, which has important practical value for bridge inspection and maintenance.

[0043] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0045] Figure 1 Schematic diagram of the structure of a vision-based arch bridge tower verticality detection system in an embodiment of the present invention;

[0046] Figure 2 is a flowchart of the execution steps of the visual information acquisition module in an embodiment of the present invention;

[0047] Figure 3 It is a side and front schematic diagram of the arch bridge tower in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] The present invention provides a visual-based arch bridge tower verticality detection system, referring to Figure 1 ,include:

[0050] The visual information acquisition module is used to use the imaging equipment carried by the drone to perform vertical climbing visual imaging on the front and sides of the arch bridge tower, and to record the status data of the drone and the imaging equipment at the same time;

[0051] The imaging analysis module is used to select coordinate reference points on the climbing visual image, convert the reference points to the same image coordinate system according to the image spatial resolution and the status data of the drone, and then calculate the verticality of the arch bridge tower according to the relative coordinates of the reference points.

[0052] The working principle and beneficial effects of the above technical solution are as follows: the visual information acquisition module uses the imaging device carried by the drone to perform vertical climbing visual imaging of the front and side of the arch bridge tower. This all-round imaging method can capture multiple viewing angles of the tower, thereby enhancing the comprehensiveness and accuracy of the detection, and can also realize the detection of the verticality of the tower in all directions. The imaging analysis module selects coordinate reference points on the climbing visual image, and converts these reference points to a unified image coordinate system using the image spatial resolution and the state data of the drone. This step ensures the accuracy of data processing and provides a reliable basis for subsequent verticality calculations. Through the automated imaging analysis module, the present invention can efficiently identify reference points from the image and calculate the verticality of the arch bridge tower without the need for tedious manual measurement and calculation. This method not only improves the efficiency of measurement, but also reduces human errors, and realizes automated and efficient verticality detection. The present invention realizes automated and efficient measurement of the verticality of the arch bridge tower by combining drone technology and image processing algorithms. This method provides an innovative solution for bridge inspection and maintenance, which helps to improve the safety and reliability of bridge structures.

[0053] In a preferred embodiment, the visual information acquisition module includes:

[0054] The UAV equipment is used to perform vertical climbing action relative to the arch bridge tower according to the control command and record the state parameters of the UAV, wherein the state parameters include the relative coordinate position of the UAV and the deflection angle of the UAV;

[0055] Imaging equipment, used to collect images of the arch bridge tower while the UAV is performing vertical climbing actions;

[0056] A distance detection unit is used to detect the vertical distance between the drone and the arch bridge tower;

[0057] The laser marking unit is a cross-line laser emitting device mounted on the UAV. The up-down direction of the cross-line laser is perpendicular to the horizontal direction of the UAV, and the left-right direction of the cross-line laser is perpendicular to the up-down direction of the UAV.

[0058] The working principle and beneficial effects of the above technical solution are as follows: by performing vertical climbing action and recording detailed state parameters, including relative coordinate position and deflection angle, the present invention can accurately control the shooting position and posture of the drone, thereby improving the accuracy and reliability of visual information acquisition, and can effectively prevent the drone from being affected by environmental wind and causing the collected information to not meet the requirements through the self-feedback mechanism, and control the deviation of the drone and the detected error within a small range. The use of the distance detection unit enables the vertical distance between the drone and the arch bridge tower to be detected and calibrated in real time, which is crucial to ensure the image quality collected by the imaging device and the accuracy of the tower verticality measurement. The cross-line laser emitting device of the laser marking unit provides an intuitive reference frame, so that the imaging device can clearly identify and locate the features of the arch bridge tower when collecting images. This laser marking method can enhance the recognition and positioning of image features, thereby providing an accurate reference benchmark for subsequent image analysis and verticality calculation. The application of the laser marking unit in the embodiment of the present invention not only improves the feature recognition and positioning accuracy in the image acquisition process, but also provides effective assistance for the navigation and shooting of the drone in a complex environment, which is conducive to the detection of tall structures such as arch bridge towers.

[0059] In a preferred embodiment, referring to Figure 2 and Figure 3 , the visual information acquisition module performs the following operations:

[0060] The initial image information of the environment around the UAV equipment is obtained through the imaging device, and the specific position of the arch bridge tower is determined based on the initial image information and the preset target graphic features;

[0061] Perform surround image acquisition on the arch bridge tower, and determine the position of the symmetry axis of the front or side image of the arch bridge tower based on the image acquisition result analysis;

[0062] The UAV is adjusted to a position close to the ground when it is aligned with the symmetry axis, and the distance between the UAV and the arch bridge tower is adjusted according to the distance detection result fed back by the distance detection unit;

[0063] After the imaging device carried by the drone is aligned with the symmetry axis of the arch bridge tower, the drone is controlled to climb in the vertical direction, and continuous imaging is performed through the imaging device, while the state parameters of the drone are recorded.

[0064] The working principle and beneficial effects of the above technical solution are as follows: when the staff places the drone equipment in the vicinity of the detection target and starts it, the drone will obtain the initial image information of the environment around the equipment through the imaging device, and determine the specific position of the arch bridge tower based on the initial image information and the preset target graphic features, thereby realizing the automatic measurement of the arch bridge tower; perform surround image acquisition on the arch bridge tower, and determine the position of the symmetry axis of the front or side image of the arch bridge tower based on the image acquisition result analysis, so as to ensure that the drone can face the arch bridge tower, which can effectively reduce the calculation difficulty of the subsequent coordinate transformation; adjust the drone to the near-ground position when facing the symmetry axis, adjust the distance between the drone and the arch bridge tower through the distance detection result fed back by the distance detection unit, and through the high-precision distance detection device, the error can be reduced to the centimeter level, so that the subsequent verticality detection result is more accurate; after the imaging device carried by the drone faces the symmetry axis of the arch bridge tower, control the drone to climb in the vertical direction, and perform continuous imaging through the imaging device, and record the state parameters of the drone at the same time, thereby realizing the acquisition of high-precision front images of the arch bridge tower. This technical solution method not only improves the degree of automation of detection, but also reduces the errors caused by manual operation, and has important practical value for bridge detection and maintenance.

[0065] In a preferred embodiment, the imaging analysis module performs the following steps:

[0066] Based on the arch bridge tower image collected by the imaging device, the cross laser feature retained in the arch bridge tower image is analyzed and determined;

[0067] The multi-frame arch bridge tower images are linearly aligned and stitched in the longitudinal direction based on the cross laser feature longitudinal laser to correct the image deflection caused by the movement offset of the drone;

[0068] Analyze the verticality of the arch bridge tower based on the overall image after splicing.

[0069] The working principle and beneficial effects of the above technical solution are as follows: by analyzing the cross laser features in the arch bridge tower image collected by the imaging device, the key reference points of the tower can be accurately identified and tracked. This feature-based analysis method improves the accuracy of image processing and provides a reliable basis for subsequent image stitching and verticality analysis. Linear alignment and stitching of multiple frames of images based on the cross laser features effectively corrects the image deflection caused by the slight movement offset of the drone. This longitudinal laser linear alignment technology ensures that the overall image after stitching has a high degree of consistency and accuracy, thereby providing high-quality visual data for verticality analysis. The transverse laser features can also effectively assist in determining the horizontal deflection state of the image. Using the stitched overall image of the arch bridge tower for verticality analysis, the verticality of the tower can be comprehensively evaluated. This method enhances the reliability and accuracy of verticality measurement by integrating data from multiple perspectives. In addition, by eliminating the image offset caused by the movement of the drone, the authenticity and validity of the measurement results are ensured. This technical solution realizes efficient and accurate measurement of the verticality of the arch bridge tower through the cross laser active marking method, precise image feature recognition, alignment stitching and verticality analysis. This method not only improves the degree of automation of measurement, but also reduces the errors caused by manual operation, and has important practical value for bridge inspection and maintenance.

[0070] In a preferred embodiment, the imaging analysis module further performs the following steps:

[0071] Determine the first image taken by the drone at the bottom of the arch bridge tower And the first image The corresponding first imaging coordinate system ,in Indicates taking the first image The distance between the camera and the arch bridge tower, Indicates the camera rotation angle, Indicates the camera position;

[0072] Determine the second image taken by the drone at the bottom of the arch bridge tower And the second image The corresponding second imaging coordinate system ,in Indicates taking the second image The distance between the camera and the arch bridge tower, Indicates the camera rotation angle, Indicates the camera position;

[0073] Select a feature point on the top of the arch bridge tower as the first reference point , select a feature point at the bottom of the arch bridge tower as the second reference point ;

[0074] The edge features of the arch bridge tower in the first image and the second image are extracted by image processing technology, and the pixel length of the standard section of the arch bridge tower is determined according to the extraction results;

[0075] Based on the known actual length of the standard section and the determined pixel length of the standard section in the first image and the second image, the spatial resolution of the first image and the second image are calculated and determined respectively. , , where the spatial resolution is the ratio of the actual length to the pixel length;

[0076] The second reference point is calculated based on the pinhole imaging principle and the spatial resolution of the first image and the second image. In the preset coordinate system The coordinate position of , then:

[0077]

[0078]

[0079] Based on coordinate location And the position offset of the drone during imaging, calculate the second reference point In the first imaging coordinate system Coordinates in ,in:

[0080]

[0081]

[0082] in, as well as Respectively represent the camera coordinate positions when the camera is shooting at the bottom and top;

[0083] Calculate the verticality of the arch bridge tower:

[0084]

[0085] in, Indicates the verticality of the arch bridge tower.

[0086] The working principle and beneficial effects of the above technical solution are as follows: by calculating the spatial resolution of the first image and the second image respectively, the present invention can provide an accurate measurement benchmark for the verticality detection of the arch bridge tower. This resolution determination method based on the ratio of actual length to pixel length improves the accuracy and reliability of measurement. By determining the images taken by the drone at different positions and their corresponding imaging coordinate systems, the present invention realizes effective alignment and coordinate conversion between images. This method can correct the image deflection caused by the motion offset of the drone, ensuring the accuracy of image analysis. Using the pinhole imaging principle and the calculated spatial resolution, the present invention can automatically calculate the verticality of the arch bridge tower. Through precise image processing technology and coordinate conversion formula, the present invention provides an efficient and accurate verticality detection method, which is of great significance for the engineering quality assessment and maintenance of the arch bridge tower. The present invention realizes the automation and accurate measurement of the verticality of the arch bridge tower by combining drone shooting, image processing technology and spatial resolution calculation. This method not only improves the measurement efficiency, but also reduces human errors, providing advanced technical means for bridge inspection and maintenance.

[0087] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A vision-based arch bridge tower verticality detection system, characterized in that: include: The visual information acquisition module is used to use the imaging equipment carried by the drone to perform vertical climbing visual imaging on the front and sides of the arch bridge tower, and to record the status data of the drone and the imaging equipment at the same time; The imaging analysis module is used to select coordinate reference points on the climbing visual image, convert the reference points to the same image coordinate system according to the image spatial resolution and the status data of the drone, and then calculate the verticality of the arch bridge tower according to the relative coordinates of the reference points; The visual information acquisition module comprises: The UAV equipment is used to perform vertical climbing action relative to the arch bridge tower according to the control command and record the state parameters of the UAV, wherein the state parameters include the relative coordinate position of the UAV and the deflection angle of the UAV; Imaging equipment, used to collect images of the arch bridge tower while the UAV is performing vertical climbing actions; A distance detection unit is used to detect the vertical distance between the drone and the arch bridge tower; The laser marking unit is a cross-line laser emitting device mounted on the drone, the vertical direction of the cross-line laser is perpendicular to the horizontal direction of the drone, and the left and right direction of the cross-line laser is perpendicular to the vertical direction of the drone; The imaging analysis module performs the following steps: Based on the arch bridge tower image collected by the imaging device, the cross laser features retained in the arch bridge tower image are analyzed and determined; The multi-frame arch bridge tower images are linearly aligned and stitched in the longitudinal direction based on the cross laser feature longitudinal laser to correct the image deflection caused by the movement offset of the drone; Analyze the verticality of the arch bridge tower based on the overall image after splicing.

2. The visual-based arch bridge tower verticality detection system according to claim 1, characterized in that: The visual information acquisition module performs the following operations: The initial image information of the environment around the UAV equipment is obtained through the imaging device, and the specific position of the arch bridge tower is determined based on the initial image information and the preset target graphic features; Perform surround image acquisition on the arch bridge tower, and determine the position of the symmetry axis of the front or side image of the arch bridge tower based on the image acquisition result analysis; The UAV is adjusted to a position close to the ground when it is aligned with the symmetry axis, and the distance between the UAV and the arch bridge tower is adjusted according to the distance detection result fed back by the distance detection unit; After the imaging device carried by the drone is aligned with the symmetry axis of the arch bridge tower, the drone is controlled to climb in the vertical direction, and continuous imaging is performed through the imaging device, while the state parameters of the drone are recorded.

3. The visual-based verticality detection system for arch bridge towers according to claim 1 is characterized in that: The imaging analysis module also includes: Determine a first image P1 captured by the drone at the bottom of the arch bridge tower and a first imaging coordinate system (D1, θ1, W1) corresponding to the first image P1, where D1 represents the distance between the camera and the arch bridge tower when the first image P1 is captured, θ1 represents the rotation angle of the camera, and W1 represents the camera position; Determine a second image P2 taken by the drone at the bottom of the arch bridge tower and a second imaging coordinate system (D2, θ2, W2) corresponding to the second image P2, where D2 represents the distance between the camera and the arch bridge tower when the second image P2 is taken, θ2 represents the rotation angle of the camera, and W2 represents the camera position; Select a characteristic point on the top of the arch bridge tower as the first reference point C1 (x1, y1), and select a characteristic point on the bottom of the arch bridge tower as the second reference point C2 (x2, y2); The edge features of the arch bridge tower in the first image and the second image are extracted by image processing technology, and the pixel length of the standard section of the arch bridge tower is determined according to the extraction results; Based on the known actual length of the standard section and the determined pixel length of the standard section in the first image and the second image, the spatial resolution (k x1 , k y1 )、(k x2 , k y2 ), where spatial resolution is the ratio of actual length to pixel length; The coordinate position H2 (x2, y2) of the second reference point C2 (x2, y2) in the preset coordinate system (D1, θ2, W2) is calculated based on the pinhole imaging principle and the spatial resolution of the first image and the second image. H2 ,y H2 ), then: Based on the coordinate position H2(x H2 ,y H2 ) and the position offset of the drone during imaging, calculate the coordinates H1 (x2, y2) of the second reference point C2 (x2, y2) in the first imaging coordinate system (D1, θ1, W1) H1 ,y H1 ),in: in, as well as Respectively represent the camera coordinate positions when the camera is shooting at the bottom and top; Calculate the verticality of the arch bridge tower: Among them, ΔL represents the verticality of the arch bridge tower.

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