Multi-view real-time monitoring method and system for cantilever assembly posture of arch bridge steel truss section

Abstract

The invention discloses a multi-view real-time monitoring method and a multi-view real-time monitoring system for cantilever assembly postures of arch bridge steel truss sections, belongs to the technical field of construction monitoring, and solves the problem that the dynamic posture change of structures such as cable tower cranes under dynamic loads cannot be monitored due to the fact that a traditional precise level gauge and a total station depend on professional personnel operation and data processing. The method comprises the following steps: recording a segment manufacturing form, carrying out photogrammetry on a segment assembly attitude, carrying out photogrammetry on the segment assembly attitude, calculating an error between a current pose and a design pose in real time based on a segment assembly attitude calculation result, and finishing segment main pipe assembly deviation correction. According to the invention, the space coordinates of all key point locations can be fed back in real time, and the postures of the hoisting segments can be monitored in real time. Therefore, accurate data support is provided for rapid deviation correction, the industrial camera array with three or more meshes is adopted, non-shielding imaging of at least three non-collinear targets is ensured under the complex working condition of cantilever assembly, the working efficiency is remarkably improved, and the construction cost is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of construction monitoring, and in particular relates to a multi-eye real-time monitoring method and system for the cantilever assembly posture of arch bridge steel truss segments. Background Art

[0002] With the continuous advancement of my country's transportation infrastructure construction, long-span concrete-filled steel tube (CFST) arch bridges have become a key bridge type for crossing rivers, lakes, and seas in complex terrains such as mountainous areas and canyons, due to their strong spanning capacity, high structural rigidity, and excellent economic efficiency. The construction technology of such bridges directly impacts project progress, structural safety, and the quality of the completed bridge. Cable hoisting and cantilever assembly with cable stays have become the mainstream construction methods for long-span concrete-filled steel tube (CFST) arch bridges due to their high efficiency and reliability. The core of this method lies in the coordinated action of cable towers, cable hoist systems, and cable stays to achieve precise hoisting, temporary fixation, and linear control of arch rib segments, ultimately completing the arch rib closure. However, as arch bridge construction expands deeper into challenging mountainous areas, the construction environment becomes increasingly complex, span requirements continue to increase, labor costs continue to climb, and requirements for construction efficiency, safety, and bridge quality are rapidly increasing. Traditional construction techniques are increasingly dependent on digital and automated monitoring methods. Among them, fast and high-precision measurement technology is a key prerequisite for realizing real-time digital twins of arch bridges, dynamic control of construction processes and high-quality construction. Its technical bottleneck has become a core issue restricting the improvement of the construction level of large-span arch bridges.

[0003] At present, the industry mainly relies on the following types of measurement technologies for the spatial posture and deformation monitoring of key structures (such as pylons, cable systems, and arch rib segments) in the construction of large-span steel tube concrete arch bridges: (1) Due to their high measurement accuracy (accuracy of ±0.1mm or above), measurements in bridge construction often rely on instruments such as precision levels and total stations. They are currently the technologies with the deepest application background, the widest application range, and the highest industry reliance. (2) Real-time kinematic measurement technology (RTK) is a GNSS real-time dynamic positioning technology (GPS, Beidou, etc.). This technology receives satellite signals between the base station and the mobile station and uses carrier phase difference technology to perform differential calculations to accurately determine the spatial relative position of the base station and the mobile station. The RTK measurement results usually include the longitude, latitude, and elevation of the base station. In the cable tower displacement measurement, these data can be converted into actual three-axis translation displacement values, which are applicable to various structures and have a wide range of applications. However, RTK technology is susceptible to GPS signal loss, which is particularly evident in complex mountainous bridge construction environments. It is often blocked by buildings, trees, and mountains, resulting in a significant reduction in measurement accuracy. In addition, the use of RTK technology usually requires the establishment of a base station to provide a reference signal, which increases the cost and complexity of the monitoring system. Secondly, the transmission distance of GPS signals is limited, usually only effective within a range of tens of kilometers. Exceeding the range will directly affect the measurement accuracy. Due to the high cost of GPS, monitoring systems are only set up in individual important bridge projects, and its applicability is limited. (3) Machine vision measurement technology is gradually being applied to bridge construction measurement due to its advantages of non-contact, high precision, and real-time. However, it is an emerging technology in recent years and its application is not yet widespread.

[0004] In summary, existing optical measurement methods that rely on levels and total stations require specialized personnel for operation and data processing, resulting in high labor costs. The monitoring range is relatively limited, enabling only single-point measurements. These methods are easily obstructed by line of sight and frequently require station changes, resulting in significant time consumption and cumulative errors. Furthermore, these methods can only measure posture deformation under static loads and are unable to monitor posture deformation of cable-suspended tower structures under dynamic loads. Furthermore, while the accuracy of RTK measurement generally meets practical engineering requirements, its real-time data processing and feedback capabilities are poor, requiring significant post-processing resources and increasing construction costs. Furthermore, since deformation often occurs instantaneously, it is difficult to provide real-time feedback on posture changes in cables, towers, arches, and other structures, and to provide timely warnings. Furthermore, existing visual measurement methods for bridges generally utilize monocular vision solutions, requiring the camera plane to be parallel to the target plane. However, this measurement requirement is often difficult to achieve under complex construction conditions in mountainous areas. Furthermore, the technology for long-distance visual measurement methods is even more limited, significantly limiting their practical application. Moreover, the existing spatial posture deformation measurement technology for large-span bridge towers, arches, hanging objects, etc. can only measure displacement values, lacks the ability to monitor the entire structure, and cannot provide comprehensive and in-depth monitoring information. To address the above problems, we proposed a multi-view real-time monitoring method and system for the cantilever assembly posture of arch bridge steel truss segments. Summary of the Invention

[0005] The purpose of the present invention is to address the shortcomings of the existing technology and provide a multi-eye real-time monitoring method and system for the cantilever assembly posture of arch bridge steel truss segments, which solves the problem that traditional precision levels and total stations rely on professional personnel for operation and data processing, have high labor costs, only support single-time single-point measurement, are easily obstructed by mountains, towers, etc., and require frequent station changes, resulting in time waste and accumulated errors, and are unable to monitor the dynamic posture changes of structures such as cable towers under dynamic loads.

[0006] The present invention is achieved by providing a multi-eye real-time monitoring method for the assembly posture of the cantilever of the arch bridge steel truss segment, the multi-eye real-time monitoring method for the assembly posture of the cantilever of the arch bridge steel truss segment comprising:

[0007] S10, Segment Manufacturing Shape Recording: Calibrate four motion capture cameras, record the manufacturing shape of the arch bridge steel truss segments based on the motion capture cameras, and retain the tube body targets for subsequent measurements;

[0008] S20, photogrammetry of segment assembly posture: pre-calibrate the internal parameter matrix of the industrial RGB camera, perform camera measurement of the segment assembly posture through the industrial RGB camera, solve the segment assembly posture, and output the segment assembly posture solution result;

[0009] S30, segment main body splicing correction: load at least one set of segment assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment assembly posture solution results, determine whether the error between the current posture of the segment as a whole and the design posture meets the preset error threshold, and complete the segment main body splicing correction.

[0010] Preferably, the method for recording the manufacturing form of the arch bridge steel truss segment based on a motion capture camera includes:

[0011] S101, calibrating the four motion capture cameras in the assembly field: using a fixed-length calibration rod to calculate the point cloud scale. When calculating the point cloud scale, reflective ball holders are fixedly installed at both ends of the calibration rod. The reflective ball holders consist of reflective balls, a magnetic base, and a screw. The reflective balls are detachably mounted in the magnetic base via the screw. The distance between the two groups of reflective balls is 1 meter.

[0012] S102, using a motion capture camera to capture and process the reflective spot image, capture the reflective ball and the reflective target image, and use the RANSAC algorithm to obtain the pixel coordinates of the image center point and number them;

[0013] S103, using multi-view geometry or a 3D reconstruction algorithm to calculate the world coordinates of the centroids of the target and the reflective ball, and obtain the world coordinates of the reflective ball and the reflective target at the center pixel coordinates of the images with different numbers;

[0014] S104, fit the center coordinates of the end of the segment main pipe and convert them into the local coordinates of the segment. Repeat steps S101-S104 for the pipe segment of the steel pipe. Then remove the reflective ball fixture and retain the pipe body target for posture measurement and solution during subsequent segment assembly.

[0015] Preferably, the method of fitting the center coordinates of the main end of the segment and converting them into local coordinates of the segment includes:

[0016] S1041, triangulating the pixel points in the imaging planes of the four motion capture cameras, and obtaining the world coordinates of the center point of the i-th marker through bundle adjustment optimization of multiple views;

[0017] S1042, based on least squares fitting, obtain the coordinates of the spatial center of each main pipe end in the segment, where the spatial center of the steel pipe end and the center of the circle formed by the plurality of reflective balls fixed to the end flange are on the same axis;

[0018] S1043: Map the centroid coordinates of the flange at the end of the segment into the local coordinate system of the segment, and convert the world coordinates of the centers of the circles at both ends of the segment into the local coordinate system of the pipe body.

[0019] Preferably, the method for calculating the segment assembly posture includes:

[0020] S201: Before installing the first section, set no fewer than three non-collinear permanent control points within the field of view of each industrial RGB camera on the opposite bank. Use a total station to measure and obtain the world coordinates of the control points. Calibrate the intrinsic parameters of the industrial RGB cameras installed on the sides of the arch footings on both sides.

[0021] S202, taking a long-distance photo of the segment target and calculating the world coordinates of the target;

[0022] S203, obtaining the posture information of the current node through inverse transformation of local coordinates, transforming the center coordinates of all flange holes at the end of the segment based on the posture information of the current node, and realizing inverse transformation of local coordinates to world coordinates.

[0023] Preferably, the method for correcting the deviation of segment main pipe splicing includes:

[0024] S301, loading at least one set of segment assembly posture solution results and obtaining the segment design posture, and solving the overall posture of the segment;

[0025] S302, adjusting the overall posture of the segment based on the designed posture, calculating the error between the current posture and the designed posture in real time based on the segment assembly posture solution, outputting the overall posture solution of the segment, and determining whether the error between the overall current posture of the segment and the designed posture meets a preset error threshold;

[0026] S303, if the error between the current position and the designed position of the segment as a whole meets the preset error threshold, the flanges of the adjacent segments are tightened;

[0027] S304, interlocking and tensioning the cables;

[0028] S305, main pipe closed ring welding, complete the construction of this section.

[0029] Preferably, before solving the segment assembly posture, the intrinsic parameter matrices of the four industrial RGB cameras are pre-calibrated. In the subsequent photogrammetry operation, it is ensured that three or more industrial RGB cameras are aimed at the four targets pasted on the bottom of the segment to be assembled and tested, and at least two industrial RGB cameras are used to fully image the targets.

[0030] Preferably, the industrial RGB cameras are divided into two medium-high resolution cameras and two high-resolution cameras, one group of which is arranged on each side of the arch bridge. The high-resolution camera is used to observe the targets on the opposite bank segment, and the medium-high resolution camera is used to observe the local bank. On an arch bridge with a span of more than 300m, the medium-high resolution camera has a pixel greater than 70 million pixels, and the target size is greater than 30cm, and the target is made of reflective material.

[0031] Preferably, in step S303, if the error between the current overall posture of the segment and the designed posture does not meet the preset error threshold, the segment main pipe splicing is corrected based on the designed posture, triggering the construction equipment to adjust the industrial RGB camera parameters and re-execute steps S201-S203 until the error between the current overall posture of the segment and the designed posture meets the preset error threshold.

[0032] On the other hand, the present invention also provides a multi-eye real-time monitoring system for the assembly posture of the cantilever of the arch bridge steel truss segment, the multi-eye real-time monitoring system for the assembly posture of the cantilever of the arch bridge steel truss segment comprises:

[0033] The segment manufacturing morphology recording module is used to calibrate four motion capture cameras, record the manufacturing morphology of the arch bridge steel truss segments based on the motion capture cameras, and retain the tube body targets for subsequent measurements;

[0034] The segment assembly posture measurement module is used to pre-calibrate the internal parameter matrix of the industrial RGB camera, measure the segment assembly posture through the industrial RGB camera, solve the segment assembly posture, and output the segment assembly posture solution result;

[0035] The main body splicing correction module is used to load at least one set of segment assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment assembly posture solution results, determine whether the error between the current posture of the segment as a whole and the design posture meets the preset error threshold, and complete the segment main body splicing correction.

[0036] Preferably, the main splicing and correction module includes:

[0037] The overall posture solving unit is used to load at least one set of segment assembly posture solving results and integrate the segment assembly posture solving results to obtain the segment overall posture solving results;

[0038] The error calculation unit calculates the error between the current posture and the designed posture in real time based on the segment assembly posture solution results;

[0039] An error judgment unit is used to judge whether the error between the current posture of the segment as a whole and the designed posture meets a preset error threshold;

[0040] The correction control unit triggers the camera parameter adjustment strategy based on the error result between the current pose of the segment as a whole and the designed pose, and completes the segment main body splicing correction based on the camera parameter adjustment strategy.

[0041] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0042] In the embodiment of the present invention, the spatial coordinates of all key points can be fed back in real time, and the posture of the hoisting segment can be monitored in real time. This provides accurate data support for rapid deviation correction. By using an array of 3 or more industrial cameras and matching high and low resolution cameras on both sides, it is ensured that under the complex working conditions of cantilever assembly, at least 3 non-collinear targets can be imaged without obstruction, solving the problem of station transfer caused by single-angle line of sight obstruction and avoiding the disadvantage of forced interruption of operation due to obstruction in traditional measurement. In addition, by adopting the method of prior storage of segment geometry, only 3 targets on the main pipe body need to be measured during the formal inter-segment splicing stage, and the coordinates of the target coordinates are used to inversely calculate the coordinates of the centroid of the two ends of the main pipe, thereby greatly reducing the number of measurement points, significantly improving work efficiency, and reducing construction costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the implementation process of the multi-eye real-time monitoring method for the cantilever assembly posture of the arch bridge steel truss segment provided by the present invention.

[0044] Figure 2 The figure shows the steel pipe segment shape and the schematic diagram of target measurement.

[0045] Figure 3 The figure shows the spatial arrangement of industrial RGB cameras when assembling the main arch segments of the arch bridge.

[0046] Figure 4 The plan and elevation layout of the industrial RGB camera during the assembly of the main arch segments of the arch bridge are shown.

[0047] Figure 5 A schematic diagram showing the pan / tilt rotation angle of an industrial RGB camera is shown.

[0048] Figure 6 The figure shows the imaging and target key point matching diagram when an industrial RGB camera takes long-distance photos of a segmented target.

[0049] Figure 7 It is a structural schematic diagram of the multi-eye real-time monitoring system for the cantilever assembly posture of the arch bridge steel truss segment provided by the present invention.

[0050] Figure: 1. Segment; 2. Target; 3. Reflective ball holder; 3-1. Reflective ball; 3-2. Screw; 3-3. Magnetic mount; 4. Motion capture camera; 4-1. Imaging plane; 4-2. Center pixel; 5. Industrial RGB camera; 5-1. Medium- and high-resolution camera; 5-2. High-resolution camera; 6. Flange;

[0051] 100. Segment manufacturing shape recording module; 200. Segment assembly posture measurement module; 300. Main body splicing correction module; 310. Overall posture solution unit; 320. Error calculation unit; 330. Error judgment unit; 340. Correction control unit. DETAILED DESCRIPTION

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are only for the purpose of describing specific embodiments and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0053] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] Traditional precision levels and total stations rely on professional personnel for operation and data processing, which has high labor costs and only supports single-time single-point measurement. They are easily obstructed by mountains, towers, etc. and require frequent station changes, resulting in time waste and cumulative errors. They are even more unable to monitor the dynamic posture changes of structures such as cable towers under dynamic loads. In response to the above problems, we propose a multi-eye real-time monitoring method and system for the cantilever assembly posture of arch bridge steel truss segments. In short, when the method is implemented, multi-eye real-time monitoring of the cantilever assembly posture of arch bridge steel truss segments is achieved through segment manufacturing morphology recording, segment assembly posture photogrammetry, and segment main pipe splicing correction. In the embodiment of the present invention, the spatial coordinates of all key points can be fed back in real time, and the posture of the hoisting segment 1 can be monitored in real time. This provides accurate data support for rapid deviation correction. By adopting an array of 3 or more industrial cameras and matching high and low resolution cameras on both sides, it ensures unobstructed imaging of at least 3 non-collinear targets 2 under complex cantilever assembly conditions, solves the problem of station transfer caused by obstruction of the line of sight from a single perspective, and avoids the disadvantage of forced interruption of operations due to obstruction in traditional measurements. In addition, by adopting the method of prior storage of the geometric shape of segment 1, only 3 targets 2 of the main pipe body need to be measured in the formal inter-segment splicing stage, and the coordinates of the centroid of the two ends of the main pipe are inverted using the coordinates of target 2, thereby greatly reducing the number of measuring points, significantly improving work efficiency and reducing construction costs.

[0055] The embodiment of the present invention provides a multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment. Figure 1The present invention shows a schematic diagram of the implementation process of a multi-eye real-time monitoring method for the assembly posture of the cantilever of the arch bridge steel truss segment. The multi-eye real-time monitoring method for the assembly posture of the cantilever of the arch bridge steel truss segment specifically includes:

[0056] S10, recording the manufacturing shape of the segment: calibrate the four motion capture cameras 4, record the manufacturing shape of the arch bridge steel truss segment 1 based on the motion capture cameras 4, and retain the pipe body target 2 for subsequent measurement;

[0057] S20, photogrammetry of segment assembly posture: pre-calibrate the internal parameter matrix of the industrial RGB camera 5, perform camera measurement of the assembly posture of segment 1 through the industrial RGB camera 5, solve the assembly posture of segment 1, and output the solution result of the assembly posture of segment 1;

[0058] S30, segment main body splicing correction: load at least one set of segment 1 assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment 1 assembly posture solution results, determine whether the error between the overall current posture of segment 1 and the design posture meets the preset error threshold, and complete the segment main body splicing correction.

[0059] In the embodiment of the present invention, the spatial coordinates of all key points can be fed back in real time, and the posture of the hoisting segment 1 can be monitored in real time. This provides accurate data support for rapid deviation correction. By using an array of 3 or more industrial cameras and matching high and low resolution cameras on both sides, it is ensured that under the complex working conditions of cantilever assembly, at least 3 non-collinear targets 2 can be imaged without obstruction, solving the problem of station transfer caused by single-angle line of sight obstruction and avoiding the disadvantage of forced interruption of operation due to obstruction in traditional measurement. In addition, by adopting a method of prior storage of the geometric shape of the segment 1, only the 3 targets 2 of the main pipe body need to be measured during the formal inter-segment splicing stage, and the coordinates of the target 2 are used to inversely calculate the coordinates of the centroid of the two ends of the main pipe, thereby greatly reducing the number of measurement points, significantly improving work efficiency, and reducing construction costs.

[0060] In an embodiment of the present invention, the method for recording the manufacturing form of the arch bridge steel truss segment 1 based on the motion capture camera 4 includes:

[0061] S101, calibration of four motion capture cameras in the assembly scene: using a fixed-length calibration rod to calculate the point cloud scale.

[0062] It should be noted that segment 1 refers to a number of standardized, modular prefabricated component units that the overall structure of the bridge (such as the main arch, beam, truss, etc.) is pre-divided into according to design requirements. When solving the point cloud scale, the reflective ball holder 3 is fixedly installed at both ends of the calibration rod. The reflective ball holder 3 consists of a reflective ball 3-1, a magnetic table base 3-3 and a screw 3-2. The reflective ball 3-1 is detachably installed in the magnetic table base 3-3 through the screw 3-2. The distance between the two groups of reflective balls 3-1 is 1 meter; for example, Figure 2The figure shows the shape of the steel pipe segment 1 and a schematic diagram of target measurement, that is, a schematic diagram of the reflective ball holder 3 installed at both ends of the steel pipe segment 1, wherein the reflective ball holder 3 is detachably mounted on the flange 6 through the magnetic table seat 3-3, and the flange 6 is embedded in the steel pipe segment 1. In this embodiment, the reflective ball 3-1 is a marker ball.

[0063] S102, using the motion capture camera 4 to capture and process the reflective spot image, capture the image of the reflective ball 3-1 and the reflective target 2, and use the RANSAC algorithm to obtain the coordinates of the image center point pixel 4-2 and number them;

[0064] In this embodiment of the present invention, when capturing images of the reflective ball 3-1 and the reflective target 2, grayscale images are captured and processed. The RANSAC algorithm is used to obtain the coordinates of the center pixels 4-2 of the images of the reflective ball 3-1 and the reflective target 2 captured by each motion capture camera 4. These center pixels 4-2 are then numbered to facilitate subsequent triangulation calculations. The centerline of the reflective ball holder 3 should be aligned with the axis of symmetry of the flange 6 to accurately determine the position and orientation of the flange 6.

[0065] S103, using multi-view geometry or a 3D reconstruction algorithm to calculate the world coordinates of the centroids of the target 2 and the reflective ball 3-1, and obtain the world coordinates of the reflective ball 3-1 and the reflective target 2 at the coordinates of the center points of the pixels 4-2 in the different numbered images;

[0066] In the embodiment of the present invention, when using multi-view geometry or three-dimensional reconstruction algorithms to solve the world coordinates of the centroid of the target 2 and the reflective ball 3-1, the OpenMVG or Colmap algorithm can be used, or the projection matrix method of formula (10) in the subsequent steps can be used to solve the world coordinates of the reflective balls 3-1 and the reflective target 2 with different numbers.

[0067] S104, fit the center coordinates of the main pipe end of segment 1 and convert them into the local coordinates of segment 1, repeat steps S101-S104 for the pipe segment, then remove the reflective ball fixture 3, and retain the pipe body target 2 for posture measurement and solution during the subsequent assembly of segment 1.

[0068] In an embodiment of the present invention, the method of fitting the center coordinates of the main end of the segment and converting them into local coordinates of the segment includes:

[0069] S1041, triangulate the pixel points in the imaging plane 4-1 of the four motion capture cameras 4, and obtain the world coordinates of the center point of the i-th marker through bundle adjustment optimization (BA) of multiple views;

[0070] It should be noted that, in this embodiment, the i-th marking point is the reflective ball 3 - 1 and the reflective target 2 .

[0071] S1042, using least squares fitting, obtain the spatial center coordinates of each main pipe end in segment 1. The spatial center of the steel pipe end and the center of the circle formed by the reflective balls 3-1 fixed to the end flange 6 are coaxial. Therefore, the world coordinates of the center of the steel pipe end can be fitted using the spatial point at the center of the reflective balls 3-1. The least squares expression is as follows:

[0072]

[0073] Among them, XO i,j ,YO i,j , ZO i,j is the world coordinate of the center of the j-th end of the i-th steel pipe segment; represents the X, Y, and Z coordinates of the center point of the reflective ball 3-1 at the j-th end of the i-th steel pipe segment in the local coordinate system, R i,j represents the outer radius of the jth flange 6 of the i-th arch rib segment 1.

[0074] S1043, mapping the centroid coordinates of the flange 6 at the end of segment 1 into the local coordinate system of segment 1, and converting the world coordinates of the centers of the circles at both ends of segment 1 into the local coordinate system of the pipe body.

[0075] It should be noted that the centroid coordinates of the flange 6 at the end of segment 1 are mapped into the local coordinate system of segment 1, i.e., local coordinate transformation. First, any three reflective targets 2 are selected as reference points of the local coordinate system to establish the local coordinate system Coord of the i-th segment 1. As shown in formula (2-4) and Figure 2 As shown, norm means normalization:

[0076]

[0077] in, Respectively represent the world coordinates x, y, and z values ​​of the center point of the j-th reflective target 2, A vector is obtained by cross-producting two vectors.

[0078] In the embodiment of the present invention, the world coordinates of the centers of the two ends of segment 1 are converted to the local coordinate system of the pipe body, as shown in formula (5):

[0079]

[0080] in,

[0081] Among them, lowercase x, y, and z represent world coordinates, uppercase X, Y, and Z represent local coordinates, and T i Represents the local coordinate system transformation matrix of target 2 of segment 1 i.

[0082] It should be noted that in step S104, since the segment 1 is lying horizontally on the ground, the target 2 should be pasted on the abdomen or bottom surface of the segment 1 to avoid subsequent imaging occlusion. The number of targets 2 on each segment 1 should not be less than 3 and should not be collinear. It is advisable to set 4 at the bottom, basically forming a rectangle, and the larger the enclosed area, the better, to avoid scene degradation due to occlusion, or loss of posture information due to collinear ambiguity during solution, and to ensure the robustness of recording the relative spatial relationship of the steel pipe ports. Repeat steps S101-S104 for each section of steel pipe, then remove the reflective ball holder 3, and retain the pipe body target 2 for posture measurement and solution during subsequent segment 1 assembly.

[0083] In this embodiment of the present invention, before calculating the assembly pose of the segment 1, the intrinsic parameter matrices of the four industrial RGB cameras 5 are pre-calibrated. During subsequent photogrammetry, ensure that three or more industrial RGB cameras 5 are aligned with the four targets 2 attached to the bottom of the segment 1 in its assembled state, with at least two industrial RGB cameras 5 fully imaging each target 2. For optimal performance, all four cameras simultaneously capture the entire target 2.

[0084] In order to reduce equipment costs, the industrial RGB camera 5 can be divided into two medium-high resolution cameras 5-1 and two high-resolution cameras 5-2, one of which is arranged on each bank of the arch bridge. The high-resolution camera 5-2 is used to observe the target 2 on the opposite bank segment 1, and the medium-high resolution camera 5-1 is used to observe the bank. Figure 3 The figure shows the spatial arrangement of the industrial RGB camera 5 when the main arch segment 1 of the arch bridge is assembled. Figure 4 The plan and elevation layout of the industrial RGB camera 5 is shown when the main arch segment 1 of the arch bridge is assembled. To ensure measurement accuracy reaches the centimeter level, on arch bridges with a span of more than 300m, the medium- and high-resolution camera 5-1 must have a pixel size greater than 70 million pixels and the target 2 must be larger than 30cm. Target 2 is made of reflective material to facilitate image processing and feature detection.

[0085] In a further preferred embodiment of the present invention, a method for calculating the segment assembly posture is provided, wherein the method for calculating the segment assembly posture specifically comprises:

[0086] S201, before installing the first segment 1, set no fewer than three non-collinear permanent control points within the field of view of each industrial RGB camera 5 on the opposite bank, and use a total station to measure and obtain the world coordinates of the control points, and calibrate the internal parameters of the industrial RGB cameras 5 installed on the sides of the arch footing on both sides;

[0087] In step S201, at least three non-collinear permanent control points are first set within the field of view of each industrial RGB camera 5 on opposite sides. The world coordinates of these control points are first measured using a total station. Then, during the initial calibration of the industrial RGB cameras 5, the permanent control points within the field of view of each industrial RGB camera 5 are used to calibrate the extrinsic parameter matrix of each industrial RGB camera 5 using the projection-n-projection (PnP) method, i.e., {R|T}, where R is the rotation matrix of the camera's pose and T represents the translation vector. Prior to installing the industrial RGB cameras 5, the intrinsic parameter matrix K should be calibrated in advance. During subsequent segment 1 installation measurements, if the angle of the industrial RGB camera 5 is adjusted, PnP extrinsic parameter calibration is performed using the world coordinates of the target 2 of the previous segment 1 as the control points. Thus, at each construction stage, the world coordinates of the measured points can be obtained from the projection matrix.

[0088] S202, take a long-distance photo of target 2 in segment 1 and calculate the world coordinates of target 2. Figure 5 The diagram shows the pan-tilt angle of the industrial RGB camera 5. Figure 6 It shows a schematic diagram of imaging and key point matching of target 2 when industrial RGB camera 5 takes long-distance photography of target 2 in segment 1;

[0089] In the embodiment of the present invention, when solving the world coordinates (x, y, z) of target 2, the world coordinates (x, y, z) of the known control point (key point of target 2) are used to obtain the external parameters {R|T} according to the above method. Since the internal parameter K is known, the projection matrix of the industrial RGB camera 5 can be obtained by formula (7):

[0090] P=K·[R|T](7)

[0091] The control point and all targets 2 of the current segment 1 can be observed simultaneously in the picture. The pixel coordinates of the center points of these targets 2 in the picture of the i-th industrial RGB camera 5 are (u i , v i ). For each pixel coordinate (u i , v i ), according to the projection relationship:

[0092]

[0093] Eliminating the scale factor s i Finally, the linear equations corresponding to the 5 images of a single industrial RGB camera are obtained:

[0094]

[0095] The linear equations (9) of the three industrial RGB cameras 5 are synthesized to obtain the overdetermined equations (10). If four industrial RGB cameras 5 are used to solve the equations, the number of elements increases accordingly:

[0096]

[0097] in: Represents the projection matrix P i The mth row and nth column element of , rewrite the equation group (10) into the form of Ax = b, then:

[0098]

[0099] Where i is the number of the industrial RGB camera 5, and its maximum value is the number of industrial RGB cameras 5 selected. For example, if four industrial RGB cameras 5 are used for the solution, the number of rows of A and b is expanded to 8, and the linear least squares solution is used. Get the world coordinates (x, y, z).

[0100] S203, obtain the posture information of the current node through the inverse transformation of the local coordinates, transform the center coordinates of all flange holes at the end of segment 1 based on the posture information of the current node, and realize the inverse transformation of the local coordinates to the world coordinates.

[0101] In this embodiment, as the position of segment 1 changes continuously during the assembly process, its local coordinate system also changes continuously. In order to perform the inverse transformation, the coordinate axis vector of the local coordinate system of segment 1 needs to be reconstructed in real time. Therefore, the calculation formula (2-4) needs to be repeated in each frame of the image. According to the world coordinates of target 2 corresponding to each frame obtained in step S202, the local coordinate system Coord in step S102 is continuously refreshed. And the coordinate transformation matrix T i Therefore, the world coordinates (x, y, z) of the center of each steel pipe port and the center of the flange hole on the current segment 1 can be continuously updated and calculated through formula (11).

[0102]

[0103] The lowercase x, y, and z represent world coordinates, and the uppercase X, Y, and Z represent local coordinates. is the inverse transformation matrix, which can be obtained by calculating the inverse matrix using formula (6).

[0104] In a further preferred embodiment of the present invention, the method for correcting the splicing of segment main pipes includes:

[0105] S301, loading at least one set of segment 1 assembly posture solution results and obtaining the segment design posture, and solving the overall posture of segment 1;

[0106] S302, adjusting the overall posture of segment 1 based on the designed posture, calculating the error between the current posture and the designed posture in real time based on the assembly posture solution result of segment 1, outputting the overall posture solution of segment 1, and determining whether the error between the overall current posture of segment 1 and the designed posture meets a preset error threshold;

[0107] It should be noted that compared with the design pose, the error between the current pose and the design pose includes the spatial pose error and specific point deviation of segment 1 in the current state. The error between the overall current pose of segment 1 and the design pose is calculated by formula 12:

[0108]

[0109] where Δ i, j is the deviation of the jth nozzle center on the i-th steel pipe segment 1; are the current coordinates of the j-th nozzle on the i-th segment 1; These are the design coordinates of the j-th nozzle on the i-th segment 1 respectively.

[0110] S303: If the error between the overall current posture of segment 1 and the designed posture meets the preset error threshold, the flange 6 of the adjacent segment 1 is tightened; then the next segment 1 is hoisted, the gear is switched, and steps S201-S203 are returned to adjust the camera gimbal angle, focus, and recalibrate.

[0111] It should be noted that in step S303, if the error between the overall current posture of segment 1 and the designed posture does not meet the preset error threshold, the segment main pipe splicing is corrected based on the designed posture, triggering the construction equipment to adjust the parameters of the industrial RGB camera 5 and re-execute steps S201-S203 until the error between the overall current posture of the segment and the designed posture meets the preset error threshold.

[0112] S304, interlocking and tensioning the cables;

[0113] S305, main pipe closed ring welding, complete the construction of this section 1.

[0114] In the embodiment of the present invention, by solidifying the spatial geometric relationship between the center of the main tube of segment 1 and the flange 6 during the manufacturing stage, there is no need to repeatedly measure redundant measuring points during assembly. The posture of the entire segment 1 can be reconstructed based on only three reference targets 2, and the traditional "point-by-point measurement-point-by-point solution" mode is upgraded to "prior model-incremental update", and the measurement time of a single segment 1 is reduced.

[0115] On the other hand, the present invention also provides a multi-eye real-time monitoring system for the cantilever assembly posture of arch bridge steel truss segments. Figure 7The structure diagram of the multi-eye real-time monitoring system for the cantilever assembly posture of the steel truss segment of the arch bridge is shown. The multi-eye real-time monitoring system for the cantilever assembly posture of the steel truss segment of the arch bridge specifically includes:

[0116] The segment manufacturing shape recording module 100 is used to calibrate the four motion capture cameras 4, record the manufacturing shape of the arch bridge steel truss segment 1 based on the motion capture cameras 4, and retain the pipe body target 2 for subsequent measurement;

[0117] The segment assembly posture measurement module 200 is used to pre-calibrate the internal parameter matrix of the industrial RGB camera 5, perform video measurement of the segment 1 assembly posture through the industrial RGB camera 5, solve the segment 1 assembly posture, and output the segment 1 assembly posture solution result;

[0118] The main splicing correction module 300 is used to load at least one set of segment 1 assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment 1 assembly posture solution results, determine whether the error between the overall current posture of segment 1 and the design posture meets the preset error threshold, and complete the segment main splicing correction.

[0119] In this embodiment, the main splicing and correction module 300 includes:

[0120] The overall posture solving unit 310 is used to load at least one set of segment 1 assembly posture solving results and integrate the segment 1 assembly posture solving results to obtain the overall posture solving result of segment 1;

[0121] The error calculation unit 320 calculates the error between the current posture and the designed posture in real time based on the assembly posture solution result of segment 1;

[0122] An error judgment unit 330 is used to judge whether the error between the overall current posture of segment 1 and the designed posture meets a preset error threshold;

[0123] The correction control unit 340 triggers the camera parameter adjustment strategy based on the error between the overall current posture of segment 1 and the designed posture, and completes the segment main body splicing correction based on the camera parameter adjustment strategy.

[0124] It should be noted that the multi-eye real-time monitoring system for the cantilever assembly posture of the arch bridge steel truss segment provided in the embodiment of the present invention corresponds to the steps of the above-mentioned multi-eye real-time monitoring method for the cantilever assembly posture of the arch bridge steel truss segment. For details, please refer to the implementation steps of the above-mentioned multi-eye real-time monitoring method for the cantilever assembly posture of the arch bridge steel truss segment, which will not be repeated here.

[0125] In summary, the present invention provides a multi-eye real-time monitoring method and system for the cantilever assembly posture of the steel truss segment of an arch bridge. In the embodiment of the present invention, the spatial coordinates of all key points can be fed back in real time, and the posture of the hoisting segment 1 can be monitored in real time. This provides accurate data support for rapid deviation correction. By using an array of 3 or more industrial cameras and matching high and low resolution cameras on both sides, it is ensured that under the complex working conditions of the cantilever assembly, at least 3 non-collinear targets 2 can be imaged without obstruction, solving the problem of station transfer caused by obstruction of the line of sight from a single perspective, and avoiding the disadvantage of forced interruption of operations due to obstruction in traditional measurement. In addition, by adopting a method of prior storage of the geometric shape of the segment 1, only the 3 targets 2 of the main pipe body need to be measured during the formal inter-segment splicing stage, and the coordinates of the target 2 are used to inversely calculate the coordinates of the centroid of the two ends of the main pipe, thereby greatly reducing the number of measuring points, significantly improving work efficiency, and reducing construction costs.

[0126] It should be noted that for the aforementioned embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps may be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0127] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the invention. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. Based on these embodiments, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field can still combine, add, delete or make other adjustments to the features in the various embodiments of the present invention according to the circumstances without conflict, without making creative work, so as to obtain different other technical solutions that do not deviate from the concept of the present invention in essence, and these technical solutions also fall within the scope of protection of the present invention.

Claims

1. A multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment, characterized in that: The method comprises: S10, Segment Manufacturing Shape Recording: Calibrate four motion capture cameras, record the manufacturing shape of the arch bridge steel truss segments based on the motion capture cameras, and retain the tube body targets for subsequent measurements; S20, photogrammetry of segment assembly posture: pre-calibrate the internal parameter matrix of the industrial RGB camera, perform camera measurement of the segment assembly posture through the industrial RGB camera, solve the segment assembly posture, and output the segment assembly posture solution result; S30, segment main body splicing correction: load at least one set of segment assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment assembly posture solution results, determine whether the error between the current posture of the segment as a whole and the design posture meets the preset error threshold, and complete the segment main body splicing correction.

2. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 1, characterized in that: The method for recording the manufacturing form of the arch bridge steel truss segment based on the motion capture camera includes: S101, calibrating the four motion capture cameras in the assembly field: using a fixed-length calibration rod to calculate the point cloud scale. When calculating the point cloud scale, reflective ball holders are fixedly installed at both ends of the calibration rod. The reflective ball holders consist of reflective balls, a magnetic base, and a screw. The reflective balls are detachably mounted in the magnetic base via the screw. The distance between the two groups of reflective balls is 1 meter. S102, using a motion capture camera to capture and process the reflective spot image, capture the reflective ball and the reflective target image, and use the RANSAC algorithm to obtain the pixel coordinates of the image center point and number them; S103, using multi-view geometry or a 3D reconstruction algorithm to calculate the world coordinates of the centroids of the target and the reflective ball, and obtain the world coordinates of the reflective ball and the reflective target at the center pixel coordinates of the images with different numbers; S104, fit the center coordinates of the end of the segment main pipe and convert them into the local coordinates of the segment. Repeat steps S101-S104 for the pipe segment of the steel pipe. Then remove the reflective ball fixture and retain the pipe body target for posture measurement and solution during subsequent segment assembly.

3. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 2, characterized in that: The method of fitting the center coordinates of the main end of the segment and converting them into local coordinates of the segment includes: S1041, triangulating the pixel points in the imaging planes of the four motion capture cameras, and obtaining the world coordinates of the center point of the i-th marker through bundle adjustment optimization of multiple views; S1042, based on least squares fitting, obtain the coordinates of the spatial center of each main pipe end in the segment, where the spatial center of the steel pipe end and the center of the circle formed by the plurality of reflective balls fixed to the end flange are on the same axis; S1043: Map the centroid coordinates of the flange at the end of the segment into the local coordinate system of the segment, and convert the world coordinates of the centers of the circles at both ends of the segment into the local coordinate system of the pipe body.

4. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 3 is characterized by: The method for calculating the segment assembly posture includes: S201: Before installing the first section, set no fewer than three non-collinear permanent control points within the field of view of each industrial RGB camera on the opposite bank. Use a total station to measure and obtain the world coordinates of the control points. Calibrate the intrinsic parameters of the industrial RGB cameras installed on the sides of the arch footings on both sides. S202, taking a long-distance photo of the segment target and calculating the world coordinates of the target; S203, obtaining the posture information of the current node through inverse transformation of local coordinates, transforming the center coordinates of all flange holes at the end of the segment based on the posture information of the current node, and realizing inverse transformation of local coordinates to world coordinates.

5. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 4 is characterized by: The method for correcting the deviation of segment main pipe splicing includes: S301, loading at least one set of segment assembly posture solution results and obtaining the segment design posture, and solving the overall posture of the segment; S302, adjusting the overall posture of the segment based on the designed posture, calculating the error between the current posture and the designed posture in real time based on the segment assembly posture solution, outputting the overall posture solution of the segment, and determining whether the error between the overall current posture of the segment and the designed posture meets a preset error threshold; S303, if the error between the current position and the designed position of the segment as a whole meets the preset error threshold, the flanges of the adjacent segments are tightened; S304, interlocking and tensioning the cables; S305, main pipe closed ring welding, complete the construction of this section.

6. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 4, characterized in that: Before solving the segment assembly posture, pre-calibrate the intrinsic parameter matrices of the four industrial RGB cameras. In the subsequent photogrammetry operation, ensure that three or more industrial RGB cameras are aimed at the four targets pasted on the bottom of the segment to be assembled and tested, and at least two industrial RGB cameras are used to fully image the targets.

7. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 6, characterized in that: The industrial RGB cameras are divided into two medium-high-resolution cameras and two high-resolution cameras, one group of which is arranged on each side of the arch bridge. The high-resolution camera is used to observe the targets on the opposite bank segment, and the medium-high-resolution camera is used to observe the local bank. On arch bridges with a span of more than 300m, the medium-high-resolution camera has a pixel size greater than 70 million pixels, and the target size is greater than 30cm, and the target is made of reflective material.

8. The multi-eye real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 5, characterized in that: In step S303, if the error between the current overall posture of the segment and the designed posture does not meet the preset error threshold, the segment main pipe splicing is corrected based on the designed posture, triggering the construction equipment to adjust the industrial RGB camera parameters and re-execute steps S201-S203 until the error between the current overall posture of the segment and the designed posture meets the preset error threshold.

9. A multi-view real-time monitoring system for the cantilever assembly posture of an arch bridge steel truss segment, implemented using the multi-view real-time monitoring method for the cantilever assembly posture of an arch bridge steel truss segment according to claim 1, characterized in that: The multi-eye real-time monitoring system for the cantilever assembly posture of the arch bridge steel truss segment includes: The segment manufacturing morphology recording module is used to calibrate four motion capture cameras, record the manufacturing morphology of the arch bridge steel truss segments based on the motion capture cameras, and retain the tube body targets for subsequent measurements; The segment assembly posture measurement module is used to pre-calibrate the internal parameter matrix of the industrial RGB camera, measure the segment assembly posture through the industrial RGB camera, solve the segment assembly posture, and output the segment assembly posture solution result; The main body splicing correction module is used to load at least one set of segment assembly posture solution results, calculate the error between the current posture and the design posture in real time based on the segment assembly posture solution results, determine whether the error between the current posture of the segment as a whole and the design posture meets the preset error threshold, and complete the segment main body splicing correction.

10. The multi-eye real-time monitoring system for the cantilever assembly posture of an arch bridge steel truss segment according to claim 9, characterized in that: The main splicing and correction module includes: The overall posture solving unit is used to load at least one set of segment assembly posture solving results and integrate the segment assembly posture solving results to obtain the segment overall posture solving results; The error calculation unit calculates the error between the current posture and the designed posture in real time based on the segment assembly posture solution results; An error judgment unit is used to judge whether the error between the current posture of the segment as a whole and the designed posture meets a preset error threshold; The correction control unit triggers the camera parameter adjustment strategy based on the error result between the current pose of the segment as a whole and the designed pose, and completes the segment main body splicing correction based on the camera parameter adjustment strategy.

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