A method and system for measuring three-dimensional deformation of a joint of a fabricated concrete member

Abstract

This application relates to the field of structural deformation optical measurement technology, and discloses a method and system for measuring the three-dimensional deformation of joints in prefabricated concrete components. The method includes: arranging visual markers with non-repeating coded patterns on both sides of the joint; simultaneously acquiring images of the joint area using at least two image acquisition devices arranged at spatial angles; calculating the first three-dimensional coordinates based on the joint area images and according to the principle of multi-view forward intersection; repeatedly acquiring and calculating the second three-dimensional coordinates after loading; calculating the three-dimensional spatial displacement field on both sides of the joint based on the two sets of coordinates; and resolving the relative deformation of the joint in three-dimensional space by comparing and analyzing the spatial vector relationship of the displacement field, including the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface. This application achieves non-contact, full-field, high-precision measurement of the three-dimensional deformation of the joint and can directly output engineering parameters for evaluating the connection performance.

Description

Technical Field

[0001] This application relates to the field of optical measurement technology for structural deformation, and in particular to a method and system for measuring the three-dimensional deformation of joints in prefabricated concrete components. Background Technology

[0002] The overall performance and safety of prefabricated concrete structures are highly dependent on the reliability of the joints between components. Under load or environmental action, joints may experience complex three-dimensional relative deformations, such as opening and slippage perpendicular to the joint surface and sliding parallel to the joint surface. These deformations are key indicators for evaluating the connection performance, verifying design theories, and diagnosing structural damage.

[0003] Currently, the measurement of this type of joint deformation mostly relies on contact displacement sensors or traditional single-point non-contact measurements. Contact sensors are complex to install, may interfere with the structure's own behavior, and can only acquire displacements at a limited number of discrete points along a preset one-dimensional direction, making it difficult to capture the full-field deformation distribution of the joint area, let alone directly separate the coupled three-dimensional relative deformation components such as opening, slip, and displacement. Although traditional optical measurement methods based on ordinary speckle or feature points can achieve non-contact full-field measurements, the stability and accuracy of feature matching are challenged in scenarios where concrete surface textures are repetitive and marker points are easily confused or lost during long-term measurements. Moreover, the measurement results are usually a global displacement field, requiring further complex post-processing and analysis to extract the relative deformation parameters with clear mechanical significance specific to the joint interface. Therefore, there is currently a lack of an efficient measurement method that can stably, accurately, and directly analyze the three-dimensional relative deformation of prefabricated concrete component joints. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of this application provide a method for measuring the three-dimensional deformation of joints in prefabricated concrete components to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, this application provides a method for measuring the three-dimensional deformation of joints in prefabricated concrete components, including:

[0006] S1. On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple visual markers with non-repeating coded patterns are arranged.

[0007] S2. Using at least two image acquisition devices arranged at a spatial angle, synchronously acquire images of the seam area containing all the visual markers;

[0008] S3. Based on the seam area image, identify the non-repeating coding pattern of each visual marker point, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection.

[0009] S4. After the prefabricated concrete component is subjected to load, repeat steps S2 to S3 to obtain the second three-dimensional coordinates of each visual marker point;

[0010] S5. Based on the first three-dimensional coordinates and the second three-dimensional coordinates, calculate the three-dimensional spatial displacement field of the visual marker point groups located on both sides of the seam;

[0011] S6. By comparing and analyzing the spatial vector relationship of the three-dimensional spatial displacement field, the relative deformation of the joint in the three-dimensional space is analyzed. The relative deformation includes at least the opening perpendicular to the joint surface, the slippage parallel to the joint surface, and the displacement perpendicular to the joint surface.

[0012] To address the aforementioned problems, this application also provides a three-dimensional deformation measurement system for joints of prefabricated concrete components, the system comprising:

[0013] The visual marker placement module is used to place multiple visual markers with non-repeating coded patterns on the concrete surface on both sides of the joint of prefabricated concrete components.

[0014] A synchronous image acquisition module is used to synchronously acquire images of the seam area containing all the visual markers using at least two image acquisition devices arranged at a spatial angle.

[0015] The three-dimensional coordinate calculation module is communicatively connected to the synchronous image acquisition module. It is used to identify the non-repeating coding pattern of each visual marker point based on the seam area image, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection.

[0016] The deformation trigger acquisition module works in conjunction with the synchronous image acquisition module and the three-dimensional coordinate calculation module to trigger the synchronous image acquisition module to acquire images again when the prefabricated concrete component is subjected to load, and the three-dimensional coordinate calculation module calculates the second three-dimensional coordinates of each visual marker point based on the newly acquired images.

[0017] The seam deformation analysis module is used to calculate the three-dimensional spatial displacement field of the visual marker point group located on both sides of the seam based on the first three-dimensional coordinates and the second three-dimensional coordinates.

[0018] The deformation analysis module is used to analyze the spatial vector relationship of the three-dimensional displacement field to determine the relative deformation of the joint in three-dimensional space. The relative deformation includes at least the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface.

[0019] Compared with the prior art, this application has the following beneficial effects:

[0020] First, this application achieves high-precision, full-field, non-contact dynamic measurement of joint deformation in prefabricated concrete components. By deploying visual markers that integrate unique ID codes and random speckle textures, and combining multi-view synchronous acquisition with forward intersection technology, it is possible to acquire high-resolution three-dimensional displacement field data of the surfaces on both sides of the joint throughout the entire load process without disturbing the structure, overcoming the limitations of traditional point-based and contact-based measurements.

[0021] Secondly, this application creatively adapts general optical measurement technology to the specific engineering scenario of joint deformation assessment, enabling the direct output of relative joint deformation parameters with clear engineering evaluation significance. By establishing a local coordinate system based on the joint surface and performing vector projection and synthetic analysis on the displacement fields on both sides, this method can accurately decouple from complex spatial motion data and quantitatively output the opening amount perpendicular to the joint surface, the slip amount parallel to the joint surface, and the displacement amount perpendicular to the joint surface. This provides users with key quantitative indicators that can be directly used to judge the bending, shear, and tensile properties of joints, eliminating the need for complex indirect derivations or data interpretations. This greatly improves the intuitiveness and engineering practicality of the measurement results, providing a powerful technical tool for the safety assessment and performance research of prefabricated structures. Attached Figure Description

[0022] Figure 1 A flowchart illustrating a method for measuring the three-dimensional deformation of joints in prefabricated concrete components, provided in an embodiment of this application;

[0023] Figure 2 A functional module diagram of a three-dimensional deformation measurement system for joints of prefabricated concrete components provided in an embodiment of this application;

[0024] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0026] This application provides a method for measuring the three-dimensional deformation of joints in prefabricated concrete components. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for measuring the three-dimensional deformation of joints in prefabricated concrete components can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0027] Reference Figure 1 The diagram shown is a flowchart illustrating a method for measuring the three-dimensional deformation of joints in prefabricated concrete components according to an embodiment of this application. In this embodiment, the method for measuring the three-dimensional deformation of joints in prefabricated concrete components includes:

[0028] S1. On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple visual markers with non-repeating coded patterns are arranged.

[0029] In some embodiments, multiple visual markers with non-repeating coded patterns are arranged on the concrete surface on both sides of the joint of the prefabricated concrete component, specifically including:

[0030] On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple physical code markers with unique ID codes are pre-set.

[0031] On the concrete surface area where the pre-set physical coding markers are located, auxiliary speckles are then sprayed to form a random distribution.

[0032] The overall pattern formed by the physical coding marker and the auxiliary speckle is defined as the visual marker.

[0033] A visual marker is a composite pattern that is pre-made and attached to the concrete surface to be measured. Its function is to serve as a physical feature that can be clearly identified and located with high precision by the image acquisition device. The non-repeating coded pattern refers to the unique coded information and random texture features contained in each visual marker, which enables the measurement system to unambiguously identify and match the same physical point in multiple images and at multiple time points.

[0034] Physically encoded markers are artificially created markers with specific structures. In this embodiment, multiple such markers are firmly adhered to the concrete surfaces on both sides of the joint. A specific implementation involves creating circular markers using high-contrast material, with a solid center circle to provide a clear target, surrounded by an annular band with a specific black-and-white interval sequence. The binary or other encoding rules carried by this annular band constitute the unique ID code.

[0035] For example, a ring-shaped coding strip with 8 independent sectors can theoretically provide a sufficient number of unique identifiers. These physical coding markers are arranged in a certain spatial layout, such as at equal intervals at a certain distance from the edge of the seam, to ensure that there are at least three non-collinear markers on each side of the seam, so as to facilitate subsequent spatial analysis.

[0036] Auxiliary speckle patterns are random textures formed directly on the concrete surface. In this embodiment, within a local area where physical coding markers have been pasted, a paint with high contrast to the concrete background color is sprayed to generate a large number of tiny, irregularly distributed speckles. These speckles themselves do not carry coding information, but their natural random distribution provides rich and traceable grayscale variation features for image processing algorithms.

[0037] Visual markers are defined by combining physical coded markers with auxiliary speckle patterns. During the construction or measurement preparation phase, physical coded markers are first deployed, followed by the spraying of auxiliary speckle patterns around them. This embeds each physical coded marker within a unique, highly textured random speckle field. Thus, a visual marker simultaneously possesses two features: its central coded marker provides stable and reliable identification, ensuring correct recognition even in long-term measurements or complex backgrounds; while the overall random speckle area enables sub-pixel-level precise positioning, as the algorithm can utilize the rich grayscale information of this area for relevant calculations, obtaining center coordinates with accuracy far exceeding that of a single pixel. This integration of techniques creatively solves the challenge of achieving long-term, stable, and high-precision target tracking in industrial environments such as concrete surfaces where textures may be repetitive and single features are easily disturbed. For example, even if some speckle patterns change due to lighting or contamination, the core coded information still ensures correct point matching; and the rich speckle texture greatly improves positioning accuracy, overcoming the limited positioning accuracy of simply using large-size coded markers.

[0038] The technical effect of this step is to establish a reliable and high-precision physical information carrier for the entire measurement system. The layout of visual markers transforms the concrete surface, which may originally have uniform or unstable optical features, into a characteristic surface that is easy for machine vision systems to recognize. This directly lays an indispensable physical foundation for realizing full-field, non-contact measurement. Without these pre-laid markers with unique identities and high texture features, subsequent multi-view image matching, three-dimensional coordinate calculation, and displacement field analysis would not be possible.

[0039] The output of step S1, namely a series of visual markers with known relative spatial relationships placed on both sides of the joint, is the direct object of the image acquisition device in step S2. The quality and layout of these markers directly determine the success rate of feature matching and the accuracy of three-dimensional coordinate calculation in step S3, and ultimately affect the accuracy and reliability of the displacement field and the analysis of the relative deformation of the joint in steps S5 and S6.

[0040] In some embodiments, a plurality of physical coding markers with unique ID codes are preset, specifically including: a plurality of markers with a high-contrast solid circle at the center, wherein at least some of the markers are surrounded by annular coding bands with specific black and white intervals, to constitute the physical coding markers with unique ID codes.

[0041] The high-contrast solid circle is the core for locating physical coding markers. In this embodiment, a circular region with extremely high optical contrast is created, such as a circular spot with a color depth close to pure black placed on a background with a color close to pure white, or it can be achieved using a highly reflective material. The physical size D1 of this solid circle needs to be precisely designed so that it occupies a sufficient pixel area in the image at a predetermined shooting distance to ensure stable extraction. For example, its imaging diameter is between 10 and 30 pixels. The primary function of this high-contrast solid circle is to serve as a fast coarse positioning bullseye for the markers. The image processing algorithm can first quickly lock all such circular regions in the image through methods such as threshold segmentation or spot detection, thereby initially finding the position of each marker.

[0042] The circular coding band is a functional structure that carries unique identification information. In this embodiment, a concentric circular ring region is set around the high-contrast solid circle, and the ring is divided into N independent sectors. By regularly setting each sector to black or white, a binary coding sequence of length N bits can be formed. For example, if a ring is divided into 8 sectors, there are 2^8 combinations of black and white sequences, enough to generate 256 different unique IDs. A specific application example is that, according to a predetermined coding table, the ring coding band of the marker with ID 5 is set to the sequence "black-white-black-white-white-black-black-white". This design allows the identity information (ID) to be directly encoded on the visual appearance of the marker, becoming a self-contained data structure.

[0043] The physical coded marker with a unique ID is constructed by integrating the aforementioned positioning core and coding structure into a whole. In the embodiments of this application, a high-contrast solid circle and the surrounding annular coding strip are pre-printed or fabricated on the same robust base material to form a complete, adhesive label. Its layout strategy follows the principles of metrology. At least three such coding points need to be arranged in the measurement area on both sides of the seam to define a plane or perform coordinate system transformation, and more points are usually arranged to improve reliability and displacement field density. The unique ID of each marker is recorded during deployment and associated with its preset logical position. The key to this technique lies in separating the two crucial functions of physical point identification (by decoding the ring band) and spatial positioning (by extracting the center of the solid circle) onto different structural parts of the same marker point, and then firmly combining them through precise geometric relationships (concentric circles). This design is innovative because it solves the core problem of stable and unambiguous tracking of a large number of visually similar points in multi-target, long-sequence measurements. For example, after loading, even if the surface of the component undergoes significant displacement or rotation, the system can immediately confirm which specific physical point a marker point in the image corresponds to during deployment by quickly decoding the ring band, thereby skipping the time-consuming and potentially erroneous global matching process based on grayscale texture, greatly improving the accuracy of matching and the robustness of the entire system.

[0044] This specific step ensures that observation data of the same physical point can be automatically and accurately correlated in images acquired from different angles and at different times. This is the data association foundation for subsequent precise 3D coordinate calculations and displacement vector analysis. Without this pre-coded unique identifier, target confusion can easily occur in multi-point, dynamic measurements, leading to measurement failure.

[0045] The physical coding markers defined in this step provide a spatial positioning reference frame for subsequent spraying auxiliary speckle patterns. At the same time, the stable ID information they provide, combined with the high-precision sub-pixel positioning capability provided by the auxiliary speckle patterns, together constitute the two pillars of the powerful function of visual markers. Neither can be dispensed with, and they work together to achieve the core technical goal of full-field, stable, and high-precision measurement.

[0046] S2. Using at least two image acquisition devices arranged at a spatial angle, simultaneously acquire images of the seam area containing all the visual markers.

[0047] In some embodiments, at least two image acquisition devices arranged at a spatial angle are used to simultaneously acquire images of the seam region containing all the visual marker points, specifically including:

[0048] The optical axes of at least two image acquisition devices are arranged in space at an angle that is not orthogonal to the main direction of the estimated deformation of the joint.

[0049] All the image acquisition devices are driven to simultaneously acquire images of the seam area, generating a synchronized image frame containing all the visual markers, which serves as the image of the seam area.

[0050] An image acquisition device is a hardware device for capturing optical images. In this embodiment, two or more high-resolution industrial digital cameras with precise optical calibration are selected and equipped with high-quality lenses with fixed focal lengths and suitable apertures. These cameras are mounted on stable tripods or special supports, and their internal parameters, such as focal length, principal point coordinates, and lens distortion coefficients, are accurately acquired and stored in advance through a calibration plate. This is a prerequisite for subsequent high-precision three-dimensional intersection calculations.

[0051] Spatial angle arrangement refers to the arrangement of multiple image acquisition devices in three-dimensional space, pointing towards the same area under test from different observation directions. In this embodiment, at least two cameras are first required to be positioned in front of or to the side of the seam area to ensure that all or most of the visual markers on both sides of the seam can be observed without obstruction from the perspective of each camera. A more creative key technical means lies in the specific setting of the optical axis direction, that is, the optical axis of each image acquisition device is set to be tilted at a non-orthogonal angle to the estimated main deformation direction of the seam. The estimated main deformation direction usually refers to the normal direction perpendicular to the seam surface, that is, the direction in which the seam is most likely to open or close. In specific implementation, the operator estimates the normal direction based on the geometric position of the seam, and then symmetrically arranges the optical axes of the two cameras on both sides of the normal, forming a significant angle with the normal, for example, between 30 degrees and 60 degrees. This arrangement strategy is not arbitrary, and its fundamental principle is to use the parallax principle in stereo vision for three-dimensional reconstruction. If the camera optical axis is orthogonal to the main deformation direction (i.e., parallel to the seam surface), the pixel-level changes produced by the small displacement of the seam along the normal direction in the left and right camera images will be extremely weak or even have no parallax, resulting in a sharp decrease in the measurement sensitivity in this direction. By employing an angled arrangement, any displacement of the seam along the normal direction will produce clear and measurable pixel displacements in opposite directions in the images of the two cameras, thereby significantly improving the sensitivity and accuracy of measuring key deformation quantities (such as opening amount). For example, to measure the opening deformation of a vertical seam, two cameras can be arranged on the left and right sides in front of the seam, so that their optical axes intersect in the seam area and form an angle with the vertical plane normal (horizontal direction) of the seam.

[0052] Synchronous acquisition refers to controlling all image acquisition devices to complete exposure and image data capture within the same absolute time point or a very short time interval. In the embodiments of this application, all cameras are driven by an external hardware trigger or a precise synchronization signal issued by the main control computer. Specifically, a synchronization controller can be used to generate electrical pulse signals, which are simultaneously sent to the trigger ports of all cameras via cables; or, in software-based triggering, precise real-time instructions ensure that all cameras start exposure simultaneously. This strict synchronization is to "freeze" the instantaneous deformation morphology of the prefabricated component under a specific load state. If the acquisition is not synchronized, during dynamic loading, images captured sequentially may correspond to different deformation states of the component, and the calculated three-dimensional coordinates will contain errors introduced by the time difference, resulting in displacement field distortion.

[0053] A seam area image refers to a set of digital images containing complete, clear seam information and information on all visual markers on both sides. In this embodiment, when a synchronization trigger signal is issued, all cameras expose simultaneously, converting the two-dimensional optical image of the seam area at the current moment into a digital image, with each camera generating one image. This set of images taken from different perspectives and with strictly aligned timestamps together constitutes the "seam area image" for subsequent processing. The key technical aspect is that each image must ensure that all visual markers of interest are clearly imaged without overexposure or underexposure, which typically requires pre-adjusting the camera aperture, shutter speed, and gain parameters.

[0054] This step acquires spatiotemporally synchronized multi-view raw observation data that can be used for high-precision 3D reconstruction. Through a carefully designed spatial angle arrangement, it optimizes the measurement capability of key deformation directions; through strict synchronization control, it eliminates time asynchrony errors in dynamic measurements, thus providing the most basic data guarantee for the entire method to achieve "dynamic" and "high-precision" measurement capabilities.

[0055] This step directly uses the visual markers placed on the concrete surface in step S1 as the shooting target, and converts their physical state into digital image information; at the same time, the synchronous image frame it outputs (i.e. the joint area image) is the only input data source for visual marker recognition, matching and three-dimensional coordinate calculation in step S3.

[0056] S3. Based on the seam area image, identify the non-repeating coding pattern of each visual marker point, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection.

[0057] In some embodiments, based on the seam area image, a non-repeating coded pattern for each visual marker is identified, and according to the principle of multi-view forward intersection, the first three-dimensional coordinates of each visual marker in a predetermined three-dimensional coordinate system are calculated, specifically including:

[0058] Based on the seam area image, the sub-pixel precision image coordinates of each visual marker point are extracted using the gray-scale centroid method.

[0059] Based on the non-repeating coding pattern of the visual markers, feature matching is performed on the sub-pixel precision image coordinates from different image acquisition devices to determine the corresponding coordinates of the same physical point in all images;

[0060] Based on the sub-pixel precision image coordinate set that has been feature-matched, spatial triangulation calculation is performed according to the multi-view visual forward intersection principle to generate the first three-dimensional coordinates of each visual marker point in the predetermined three-dimensional coordinate system.

[0061] In this embodiment of the application, step S3 aims to convert the two-dimensional image data acquired in step S2 into the precise position coordinates of visual marker points in three-dimensional space. This is the core computational step for realizing the reconstruction of three-dimensional geometric information from two-dimensional images.

[0062] Subpixel-precision image coordinates refer to the position coordinates of image points obtained through algorithms with a precision higher than that of a single physical pixel. In this embodiment, the specific technical means employed is the gray-scale centroid method. The algorithm's implementation process involves selecting a local calculation window centered on the integer pixel coordinates of each visual marker point that has been preliminarily located in the image (typically with the center of its high-contrast solid circle as the approximate region). Then, using the gray value of each pixel within this window as a weight, the gray-scale centroid of the entire window is calculated. Mathematically, the gray-scale centroid method expresses this as follows: for a calculation window, its central subpixel coordinates are obtained by multiplying the coordinates of all pixels within the window by their gray values, summing the results, and then dividing by the total gray values. This calculation process utilizes the rich gray-scale gradient information provided by the random speckles in the visual marker points, enabling the positioning accuracy to be improved from the pixel level to the subpixel level, for example, reaching 0.1 pixels or even higher. This is the first key data preprocessing step for achieving subsequent high-precision 3D measurement.

[0063] Feature matching refers to the process of establishing a correspondence between imaging points in different images and the same physical point in the real world. In the embodiments of this application, its implementation relies on the non-repeating encoding pattern designed for visual markers in step S1. Specifically, for all visual marker candidates extracted from each image, the system first performs a decoding operation, that is, identifies the unique ID code carried by its circular encoding band. After decoding, the matching operation is simplified to a search process based on ID number: in all images, visual markers that decode the same ID are determined to be different images of the same physical point, thereby automatically grouping their sub-pixel precision image coordinates in different images into one group. This matching method based on pre-encoded identity recognition is a creative design of this step. It fundamentally avoids the problems of mismatch and ambiguous matching that may occur when matching based on image grayscale or feature descriptors in the traditional way. It is particularly suitable for engineering measurement scenarios with complex on-site environments and numerous target points, ensuring the absolute reliability of data association and laying an accurate data foundation for subsequent calculations.

[0064] The multi-view forward intersection principle refers to a theoretical method that uses direction lines obtained from observing the same point from multiple viewpoints to intersect the three-dimensional position of that point through spatial triangulation. In the embodiments of this application, based on a set of corresponding image coordinates determined by feature matching, and the precise intrinsic and extrinsic parameters of each image acquisition device obtained through pre-calibration, for a specific visual marker point, assuming that its matching coordinates in the two camera images have been normalized to homogeneous coordinates, and the projection matrices of the two cameras are known, then the three-dimensional coordinates of that point can be obtained by solving a system of linear equations composed of projection equations. The general form of this projection equation expresses the linear relationship between image coordinates, camera parameters, and three-dimensional spatial coordinates. In actual calculations, due to observation errors, optimization algorithms such as the least squares method are usually used to solve the overdetermined system of equations, thereby obtaining the optimal three-dimensional coordinate estimate of the point in a predetermined three-dimensional coordinate system. This predetermined three-dimensional coordinate system can be the coordinate system of a selected camera or a custom world coordinate system. Through this calculation, the spatial positions of all visual marker points before the load is applied, i.e., the first three-dimensional coordinates, are accurately reconstructed.

[0065] This step successfully and accurately reconstructs the synchronously acquired 2D image sequence into 3D point cloud data of key points on the surface of the measured object. It improves the accuracy of the original data through sub-pixel extraction, ensures the robustness of data association through code-based feature matching, and finally achieves a fundamental leap from 2D to 3D through spatial intersection calculation, generating a benchmark 3D model for deformation comparison.

[0066] This step directly inputs the synchronized image frame output from step S2. After a series of image processing and geometric calculations, it outputs the precise first three-dimensional coordinates of each visual marker point. This output serves as the reference for obtaining the second three-dimensional coordinates under load in step S4, and is also the direct input data source for calculating the three-dimensional displacement vector of each point in step S5.

[0067] S4. After the prefabricated concrete component is subjected to load, repeat steps S2 to S3 to obtain the second three-dimensional coordinates of each visual marker point.

[0068] In some embodiments, after the prefabricated concrete component is subjected to load, steps S2 to S3 are repeated to obtain the second three-dimensional coordinates of each visual marker point, specifically including:

[0069] When the prefabricated concrete component begins to bear the load, all the image acquisition devices simultaneously acquire images of the joint area containing all the visual markers, as synchronous image frames after the load is applied.

[0070] Based on the synchronized image frame after the load is applied, repeat step S3 to calculate the second three-dimensional coordinates of each visual marker point in the predetermined three-dimensional coordinate system.

[0071] In this embodiment of the application, step S4 aims to obtain the precise three-dimensional spatial position of the visual marker points in the joint area of ​​the prefabricated concrete component after it has been subjected to external loads or environmental effects, thereby providing key comparative data for subsequent deformation calculation.

[0072] The period following load application is a definite temporal state description, referring to any one or more specific moments after the prefabricated concrete component begins or continues to bear design loads, test loads, or actual environmental effects. In the embodiments of this application, its implementation is closely related to the triggering strategy of the entire measurement system. Specifically, the measurement system is configured to automatically or manually trigger image acquisition during key stages of load application. For example, in a structural static loading test, the system can send a trigger signal by the test control system after each load level is completed and stabilized; in long-term health monitoring, the system can periodically acquire data at preset time intervals or triggered by sensors. The accurate recording of this time point and the correlation with the corresponding load value are the basis for directly linking physical effects with geometric deformation.

[0073] Obtaining the second three-dimensional coordinates is a repetitive data acquisition and processing procedure, the core of which lies in strictly reproducing the measurement conditions and calculation process under the reference state. In the embodiments of this application, its specific implementation includes two consecutive technical actions. The first action is to completely repeat step S2, that is, at the moment after the selected load is applied, drive all image acquisition devices to capture a new set of seam area images again in the same synchronous acquisition mode. This set of images is called the synchronous image frame after the load is applied. This operation must ensure that the spatial position, attitude, optical parameters, and lighting conditions of the camera remain absolutely unchanged since the initial state to ensure the comparability of the two measurement results. The second action is to immediately repeat the entire calculation process of step S3, taking the newly acquired synchronous image frame after the load is applied as input, and using the same image processing algorithm, namely sub-pixel coordinate extraction, feature matching based on unique ID encoding, and multi-view forward intersection calculation based on the same camera parameters, to finally calculate the new position coordinates of the same set of visual markers in the same predetermined three-dimensional coordinate system. These coordinates are the second three-dimensional coordinates.

[0074] This step enables precise comparison of three-dimensional spatial positions of the same physical target under different mechanical states. Through a completely consistent observation and calculation link, it ensures that the difference between the "first three-dimensional coordinates" and the "second three-dimensional coordinates" purely and faithfully reflects the actual structural deformation caused by the load, minimizing the systematic errors introduced by the measurement system itself. This provides crucial data pairs for upgrading from static measurement to truly dynamic process measurement.

[0075] This step relies entirely on the stable measurement benchmark established by S1 and the mature data acquisition and reconstruction processes established by S2 and S3. Its input is the new physical state of the component under load. By utilizing the process capabilities of S2 and S3, it outputs data products that can be directly compared with the results of S3. Therefore, S4 is the actual switch that triggers deformation calculations. It expands the static benchmark coordinates established by S3 into a coordinate sequence that can be used for dynamic comparison, providing direct and corresponding data input for subsequent displacement field calculations. It is an indispensable bridge connecting "state measurement" and "deformation analysis".

[0076] S5. Based on the first three-dimensional coordinates and the second three-dimensional coordinates, calculate the three-dimensional spatial displacement field of the visual marker point groups located on both sides of the seam.

[0077] In some embodiments, the three-dimensional spatial displacement field of the visual marker point groups located on both sides of the seam is calculated based on the first three-dimensional coordinates and the second three-dimensional coordinates, specifically including:

[0078] For each visual marker point, the vector difference between its second three-dimensional coordinates and its first three-dimensional coordinates is calculated to obtain the three-dimensional displacement vector of that point;

[0079] Based on the placement of each visual marker point on both sides of the joint, the calculated three-dimensional displacement vectors are assigned to the first side displacement vector set and the second side displacement vector set, respectively.

[0080] Based on the first set of side displacement vectors and the second set of side displacement vectors, a three-dimensional spatial displacement field is generated that respectively characterizes the motion state of the concrete surfaces on both sides of the joint.

[0081] In this embodiment, step S5 aims to transform the discrete visual marker point coordinate changes into structured data that can comprehensively characterize the motion state of the concrete surfaces on both sides of the joint. This is a key transitional step from point displacement analysis to overall joint deformation analysis.

[0082] A three-dimensional displacement vector describes the change in spatial position of a point as it moves from its initial position to its position after being loaded. It is a spatial geometric quantity with magnitude and direction.

[0083] The method for calculating the three-dimensional displacement vector of each visual marker point is based on strict vector subtraction. Specifically, for a specific visual marker point, assuming its three-dimensional coordinates before the load are point A and its three-dimensional coordinates after the load are point B, both of which are defined in the same predetermined three-dimensional coordinate system, the three-dimensional displacement vector of this point is the spatial vector from point A to point B. Each component of this three-dimensional displacement vector is calculated by subtracting the corresponding component of the coordinate before the load from the corresponding component of the coordinate after the load. For example, using the calculation results of steps S3 and S4, for a certain visual marker point, its first three-dimensional coordinate is and its second three-dimensional coordinate is . Then, the X, Y, and Z components of the three-dimensional displacement vector of this point will be calculated by the above formulas respectively. This calculation process is clear and direct, transforming the absolute change in coordinates into a relative motion vector with clear physical meaning.

[0084] The method of assigning three-dimensional displacement vectors to different sets relies on the layout location information pre-planned and recorded in step S1. In this embodiment, the measurement system stores the unique ID of each visual marker point and its corresponding joint side (e.g., side A or side B) during initialization. After the displacement vector calculation of all points is completed, the system automatically classifies them according to this correspondence. The displacement vectors of all points marked as belonging to the first side of the joint (e.g., the left component) are assigned to the first side displacement vector set; the displacement vectors of all points belonging to the second side (e.g., the right component) are assigned to the second side displacement vector set. This classification operation is a prerequisite for the subsequent independent analysis of the movement on both sides of the joint and the final calculation of the relative deformation.

[0085] The method for generating a three-dimensional spatial displacement field is to associate all three-dimensional displacement vectors belonging to the same side with the initial spatial positions of their corresponding visual markers, forming a spatial distribution description of the vector field. In the embodiments of this application, this is not a complex calculation, but a data structure organization process. Specifically, the three-dimensional spatial displacement field is a dataset composed of the spatial position coordinates of all visual markers on that side and their corresponding three-dimensional displacement vectors. For example, for the first side of the joint, its displacement field can be represented as a set, where represents the initial spatial position of the i-th marker on that side, and represents its calculated displacement vector. This dataset not only contains information on how much each point has moved, but also contains the original position information of these points, thereby characterizing the overall motion pattern of the surface on that side, such as overall rigid body translation, rotation, or bending deformation. This step integrates the originally isolated point displacement information into spatially continuous field data that can reflect the overall motion state of the component surface area.

[0086] This step organizes the discrete coordinate comparison results into structured displacement data divided by physical regions, which can be used for advanced spatial analysis. It realizes the leap from "point displacement" to "surface motion field", and prepares the data for the next step of directly calculating the relative deformation between the two sides of the joint.

[0087] This step directly inputs the first three-dimensional coordinates output from step S3 and the second three-dimensional coordinates output from step S4. Through vector operations and logical classification, a three-dimensional spatial displacement field is generated that is independently organized on both sides of the joint. This displacement field, namely the set of displacement vectors on the first and second sides, is the direct and unique input data for analyzing key relative deformation quantities such as joint opening, slippage, and displacement in step S6.

[0088] S6. By comparing and analyzing the spatial vector relationship of the three-dimensional spatial displacement field, the relative deformation of the joint in the three-dimensional space is analyzed. The relative deformation includes at least the opening perpendicular to the joint surface, the slippage parallel to the joint surface, and the displacement perpendicular to the joint surface.

[0089] In some embodiments, by comparing and analyzing the spatial vector relationships of the three-dimensional displacement field, the relative deformation of the joint in three-dimensional space is analyzed. The relative deformation includes at least the opening perpendicular to the joint surface, the slippage parallel to the joint surface, and the displacement perpendicular to the joint surface, specifically including:

[0090] Based on the pre-defined geometric features of the seam, a local three-dimensional coordinate system is established with the seam surface as the reference.

[0091] Project all three-dimensional displacement vectors in the first side displacement vector set and the second side displacement vector set onto the three coordinate axes of the local three-dimensional coordinate system to obtain the displacement component set of the visual marker point group on both sides in each coordinate axis direction;

[0092] The displacement components on both sides of the joint in each coordinate axis direction are vector synthesized to obtain the overall relative displacement of both sides of the joint along the coordinate axis direction.

[0093] Based on the geometric relationship between each coordinate axis of the local three-dimensional coordinate system and the joint surface, the calculated overall relative displacement of each axis is defined as the opening amount perpendicular to the joint surface, the sliding amount parallel to the joint surface, and the displacement amount perpendicular to the joint surface.

[0094] In this embodiment of the application, step S6 aims to transform the complex surface motion data on both sides of the joint into relative deformation parameters that directly characterize the mechanical properties of the joint interface and have clear engineering significance.

[0095] The relative deformation of a joint in three-dimensional space refers to the relative spatial motion component of the concrete components on both sides of the joint at the interface. It eliminates the possibility of overall rigid body displacement of the components and directly describes the deformation behavior of the connection interface itself.

[0096] Establishing a local three-dimensional coordinate system based on the joint surface, using the pre-defined geometric features of the joint, is the primary creative step for targeted deformation analysis. Specifically, the establishment of this coordinate system relies on prior knowledge or initial measurements of the joint geometry. A typical implementation is as follows: using the first three-dimensional coordinates of the visual markers before the load is applied (i.e., obtained in step S3), three-dimensional spatial plane fitting is performed on the groups of markers located on both sides of the joint to obtain two initial planes. The average normal vector direction of these two initial planes is calculated, and this direction is defined as the Y-axis of the local coordinate system. This axis direction is conventionally defined as perpendicular to the joint surface. Next, according to the actual direction of the joint (e.g., vertical or horizontal), a direction that is perpendicular to the Y-axis and approximately parallel to the joint length direction is selected and defined as the X-axis (parallel to the joint surface). Finally, according to the right-hand rule, the direction of the Z-axis is determined by calculating the cross product of the X-axis and the Y-axis. This axis is both perpendicular to and parallel to the joint surface and is used to characterize possible displacement. For example, for a vertical wall joint, the X-axis can be defined as horizontal and parallel to the joint, the Y-axis as horizontal and perpendicular to the joint pointing outward, and the Z-axis as vertical and upward. The establishment of this local coordinate system allows all subsequent analyses to be performed within an intuitive reference framework that is closely integrated with the geometry of the joint itself.

[0097] The method of projecting displacement vectors onto the coordinate axes of the local three-dimensional coordinate system is to decompose the data using the mathematical principles of vector projection. For each three-dimensional displacement vector d in the first and second side displacement vector sets obtained in step S5, its scalar projection on the unit vector directions of the X, Y, and Z coordinate axes of the local coordinate system is calculated. The essence of this projection calculation is to solve for the dot product of the displacement vector and the unit vectors of each coordinate axis. For example, the magnitude of the projection component of the displacement vector d on the Y-axis is d·e_y, where e_y is the unit direction vector of the Y-axis. By performing this operation on all displacement vectors on each side, the set of scalar values ​​of the displacement components of all marked points on that side in the X, Y, and Z directions can be obtained, which respectively characterize the amount of motion of the surface on that side along each local coordinate axis direction.

[0098] Another creative core of this step is to perform vector synthesis calculation of the displacement components on both sides of the joint in each coordinate axis direction to obtain the overall relative displacement. This is not a simple subtraction of the components at corresponding points on both sides, but a comprehensive consideration of the overall motion mode of each side surface. A preferred implementation method is to use a plane fitting and relative calculation method. Specifically, for all displacement components of a certain side of the joint (e.g., side A) in a certain coordinate axis direction (e.g., the Y-axis), a two-dimensional spatial function, such as a plane equation, characterizing the displacement distribution of that side along the Y direction is fitted by combining the initial two-dimensional spatial positions (projected coordinates on the local coordinate system XZ plane) corresponding to these points. The same fitting operation is performed on side B. The overall relative displacement of the two sides of the joint along the coordinate axis direction is obtained by calculating the difference of function values ​​of the two fitted planes at a series of XZ coordinate points representing the joint position. This method effectively eliminates the interference of small rigid body rotation or bending deformation that may exist on each side surface on the calculation of the relative displacement of the interface. What is extracted is the pure average relative separation or slip between the two interfaces. For example, the overall relative displacement in the Y direction obtained by this method more realistically reflects the average opening trend of the joint as a whole, rather than the accidental change at a certain point.

[0099] Defining deformation parameters based on the geometric relationship between the coordinate axes of the local coordinate system and the joint surface is a direct mapping that ultimately gives meaning to data engineering. Based on the established local coordinate system definition, the opening perpendicular to the joint surface is directly defined as the overall relative displacement along the Y-axis, the slip parallel to the joint surface is defined as the overall relative displacement along the X-axis, and the misalignment perpendicular to the joint surface is defined as the overall relative displacement along the Z-axis. This describes the shear misalignment on both sides of the joint in the direction perpendicular to the joint surface, i.e., the "step" effect. For example, for a horizontal joint, the relative displacement along the X-axis is horizontal slip, along the Y-axis is vertical opening, and along the Z-axis is horizontal misalignment.

[0100] This step solves the core technical problem of how to directly and quantitatively extract the key indicators necessary for evaluating the connection performance of prefabricated components from non-contact full-field measurement data. By establishing a local reference system that matches the joint characteristics and using vector synthesis analysis, it accurately decouples the complex spatial displacement field into three orthogonal relative deformation quantities with clear mechanical and engineering significance: opening, slip, and displacement. This provides a direct and reliable input for structural safety assessment.

[0101] This step directly inputs the three-dimensional spatial displacement field generated by step S5, which is divided by side. Through a series of analyses such as coordinate transformation, projection decomposition, and synthesis calculation, the final output is the relative deformation that characterizes the working state of the joint.

[0102] In some embodiments, the displacement component sets on both sides of the joint in each coordinate axis direction are vector synthesized. Specifically, the displacement component sets on both sides of the joint are respectively fitted to a plane, and the relative displacement of the two fitted planes in the corresponding coordinate axis direction is calculated as the overall relative displacement in that coordinate axis direction.

[0103] Plane fitting is a process of finding the best approximation of a flat surface for a given set of spatial data points using mathematical methods. In the embodiments of this application, its specific implementation means that for a certain side of the joint (e.g., side A), the displacement components in a certain coordinate axis direction (e.g., the Y-axis direction of the local coordinate system) are considered. Each data point in this set contains two pieces of information: first, the two-dimensional position coordinates of the point on its own surface, which are usually obtained by projecting its initial three-dimensional coordinates onto a plane perpendicular to the analyzed coordinate axis; second, the displacement scalar value of the point along the analyzed coordinate axis direction. Using mathematical optimization algorithms such as the least squares method, a two-dimensional plane equation can be fitted. This equation can best characterize the spatial distribution trend of the displacement of all measured points on the side surface along this direction. For example, for the displacement of side A in the Y direction, a plane of the form can be fitted, where x and z are the position coordinates of the point on the local coordinate system XZ plane.

[0104] Overall relative displacement is a single scalar value characterizing the degree of overall relative movement between the interfaces on both sides of a joint along a certain direction. In the embodiments of this application, the inventive technical means to obtain this value is that, after completing the plane fitting of the displacement component sets on both sides of the joint along the same coordinate axis, instead of simply comparing the displacement difference of individual points, the relative displacement of the two fitted planes along the corresponding coordinate axis is calculated. Specifically, for the established local coordinate system, a series of representative coordinate points are selected within the XZ plane representing the joint interface region. For each such coordinate point, the predicted displacement value of the fitted planes on both sides at that point is calculated, and then the difference between the two predicted values ​​is calculated. Finally, by statistically calculating the difference at all selected points (such as taking the average or maximum value), the result is determined as the overall relative displacement along the coordinate axis. This value is essentially a reflection of the average vertical distance between the two fitted planes in space along the coordinate axis.

[0105] This specific step is the core of achieving highly robust deformation analysis. Its innovative approach lies in abandoning the simple, direct difference method based on individual point displacements on both sides, which is susceptible to random errors. Due to the non-uniformity of the concrete surface, local minor defects, or measurement noise, the displacement of a single visual marker point may not fully represent the overall behavior of its region. By performing planar fitting on the displacement fields on both sides, this method effectively extracts the "mainstream trend" or "average state" of the surface movement along that direction on each side, filtering out local abnormal fluctuations. Subsequently, by comparing two planes representing the "average state," the resulting relative displacement is a robust and statistically more reliable estimate. This method deeply understands that joint deformation is a holistic interaction between the interfaces of the two components, and its results are more consistent with the macroscopic understanding of interface deformation behavior in engineering mechanics. Therefore, the final analyzed opening, slip, and displacement are more stable and reliable, truly reflecting the overall working condition of the joint.

[0106] This step significantly improves the anti-interference capability and engineering representativeness of the final deformation analysis results. It ensures that even if there are deviations in the data of individual measurement points, it will not have a decisive impact on the overall deformation assessment conclusion, thereby improving the reliability and practicality of the measurement method in complex engineering environments.

[0107] This step directly relies on the set of displacement components for each side, which has already been projected and decomposed in the local coordinate system, provided in the previous step. By performing plane fitting and relative displacement calculation in this step, we obtain the overall relative displacement with clear statistical significance along each local coordinate axis. This calculation result is directly used as the input data for defining specific deformation parameters (opening, slip, and displacement) in the next step.

[0108] like Figure 2 The diagram shown is a functional block diagram of a three-dimensional deformation measurement system for joints of prefabricated concrete components provided in an embodiment of this application.

[0109] The three-dimensional deformation measurement system 100 for prefabricated concrete component joints described in this application can be installed in an electronic device. Depending on the functions implemented, the three-dimensional deformation measurement system 100 for prefabricated concrete component joints may include a visual marker point layout module 101, a synchronous image acquisition module 102, a three-dimensional coordinate calculation module 103, a deformation trigger acquisition module 104, a joint deformation analysis module 105, and a deformation analysis module 106. The modules described in this application can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0110] In this embodiment, the functions of each module / unit are as follows:

[0111] The visual marker placement module 101 is used to place multiple visual markers with non-repeating coded patterns on the concrete surface on both sides of the joint of the prefabricated concrete component.

[0112] The synchronous image acquisition module 102 is used to synchronously acquire seam area images containing all the visual markers using at least two image acquisition devices arranged at a spatial angle.

[0113] The three-dimensional coordinate calculation module 103 is communicatively connected to the synchronous image acquisition module. It is used to identify the non-repeating coding pattern of each visual marker point based on the seam area image, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection.

[0114] The deformation trigger acquisition module 104 works in conjunction with the synchronous image acquisition module and the three-dimensional coordinate calculation module. When the prefabricated concrete component is subjected to load, it triggers the synchronous image acquisition module to acquire images again, and the three-dimensional coordinate calculation module calculates the second three-dimensional coordinates of each visual marker point based on the newly acquired images.

[0115] The joint deformation analysis module 105 is used to calculate the three-dimensional spatial displacement field of the visual marker point group located on both sides of the joint based on the first three-dimensional coordinate and the second three-dimensional coordinate.

[0116] The deformation analysis module 106 is used to analyze the relative deformation of the joint in three-dimensional space by comparing and analyzing the spatial vector relationship of the three-dimensional spatial displacement field. The relative deformation includes at least the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface.

[0117] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0118] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0119] In addition, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0120] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application.

[0121] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for measuring the three-dimensional deformation of joints in prefabricated concrete components, characterized in that, The method includes: S1. On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple visual markers with non-repeating coded patterns are arranged. S2. Using at least two image acquisition devices arranged in a spatial angle, the optical axes of the image acquisition devices are set to be at an inclination angle that is not orthogonal to the estimated deformation direction of the seam, and the seam area image containing all the visual marker points is acquired simultaneously. S3. Based on the seam area image, identify the non-repeating coding pattern of each visual marker point, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection. S4. After the prefabricated concrete component is subjected to load, repeat steps S2 to S3 to obtain the second three-dimensional coordinates of each visual marker point; S5. Based on the first three-dimensional coordinates and the second three-dimensional coordinates, calculate the three-dimensional spatial displacement field of the visual marker point groups located on both sides of the joint, specifically including: for each visual marker point, calculate the vector difference between its second three-dimensional coordinates and the first three-dimensional coordinates to obtain the three-dimensional displacement vector of that point; according to the arrangement position of each visual marker point on both sides of the joint, assign the calculated three-dimensional displacement vector to the first side displacement vector set and the second side displacement vector set respectively; based on the first side displacement vector set and the second side displacement vector set, generate the three-dimensional spatial displacement field that respectively characterizes the motion state of the concrete surface on both sides of the joint; S6. By comparing and analyzing the spatial vector relationships of the three-dimensional displacement field, the relative deformation of the joint in three-dimensional space is analyzed. The relative deformation includes at least the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface. Specifically, it includes: establishing a local three-dimensional coordinate system based on the joint surface according to the preset geometric features of the joint; projecting all three-dimensional displacement vectors in the first side displacement vector set and the second side displacement vector set onto the three coordinate axes of the local three-dimensional coordinate system to obtain the displacement component sets of each side group in each coordinate axis direction; performing vector synthesis calculation on the displacement component sets of both sides of the joint in each coordinate axis direction to obtain the overall relative displacement of both sides of the joint along the coordinate axis direction; and defining the calculated overall relative displacement of each axial direction as the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface according to the geometric relationship between each coordinate axis of the local three-dimensional coordinate system and the joint surface.

2. The method for measuring the three-dimensional deformation of joints in prefabricated concrete components as described in claim 1, characterized in that, On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple visual markers with non-repeating coded patterns are arranged, specifically including: On the concrete surface on both sides of the joint of the prefabricated concrete component, multiple physical code markers with unique ID codes are pre-set. On the concrete surface area where the pre-set physical coding markers are located, auxiliary speckles are then sprayed to form a random distribution. The overall pattern formed by the physical coding marker and the auxiliary speckle is defined as the visual marker.

3. The method for measuring the three-dimensional deformation of joints in prefabricated concrete components as described in claim 2, characterized in that, Multiple physical coding markers with unique ID codes are pre-set, specifically including: multiple markers with a high-contrast solid circle at the center, wherein at least some of the markers are surrounded by a ring coding band with specific black and white intervals, to form the physical coding markers with unique ID codes.

4. The method for measuring the three-dimensional deformation of joints in prefabricated concrete components as described in claim 1, characterized in that, Based on the seam area image, the non-repeating coding pattern of each visual marker is identified, and according to the principle of multi-view forward intersection, the first three-dimensional coordinates of each visual marker in a predetermined three-dimensional coordinate system are calculated, specifically including: Based on the seam area image, the sub-pixel precision image coordinates of each visual marker point are extracted using the gray-scale centroid method. Based on the non-repeating coding pattern of the visual markers, feature matching is performed on the sub-pixel precision image coordinates from different image acquisition devices to determine the corresponding coordinates of the same physical point in all images; Based on the sub-pixel precision image coordinate set with matched features, spatial triangulation calculation is performed according to the multi-view forward intersection principle to generate the first three-dimensional coordinates of each visual marker point in the predetermined three-dimensional coordinate system.

5. The method for measuring the three-dimensional deformation of joints in prefabricated concrete components as described in claim 1, characterized in that, After the prefabricated concrete component is subjected to load, steps S2 to S3 are repeated to obtain the second three-dimensional coordinates of each visual marker point, specifically including: When the prefabricated concrete component begins to bear the load, all the image acquisition devices simultaneously acquire images of the joint area containing all the visual markers, as synchronous image frames after the load is applied. Based on the synchronized image frame after the load is applied, repeat step S3 to calculate the second three-dimensional coordinates of each visual marker point in the predetermined three-dimensional coordinate system.

6. The method for measuring the three-dimensional deformation of joints in prefabricated concrete components as described in claim 1, characterized in that, The displacement component sets on both sides of the joint in each coordinate axis direction are vector synthesized. Specifically, the displacement component sets on both sides of the joint are respectively fitted to a plane, and the relative displacement of the two fitted planes in the corresponding coordinate axis direction is calculated as the overall relative displacement in that coordinate axis direction.

7. A three-dimensional deformation measurement system for joints of prefabricated concrete components, used to implement the three-dimensional deformation measurement method for joints of prefabricated concrete components as described in any one of claims 1-6, characterized in that, The system includes: The visual marker placement module is used to place multiple visual markers with non-repeating coded patterns on the concrete surface on both sides of the joint of prefabricated concrete components. A synchronous image acquisition module is used to synchronously acquire images of the seam area containing all the visual markers using at least two image acquisition devices arranged at a spatial angle. The three-dimensional coordinate calculation module is communicatively connected to the synchronous image acquisition module. It is used to identify the non-repeating coding pattern of each visual marker point based on the seam area image, and calculate the first three-dimensional coordinates of each visual marker point in a predetermined three-dimensional coordinate system according to the principle of multi-view forward intersection. The deformation trigger acquisition module works in conjunction with the synchronous image acquisition module and the three-dimensional coordinate calculation module to trigger the synchronous image acquisition module to acquire images again when the prefabricated concrete component is subjected to load, and the three-dimensional coordinate calculation module calculates the second three-dimensional coordinates of each visual marker point based on the newly acquired images. The seam deformation analysis module is used to calculate the three-dimensional spatial displacement field of the visual marker point group located on both sides of the seam based on the first three-dimensional coordinates and the second three-dimensional coordinates. The deformation analysis module is used to analyze the spatial vector relationship of the three-dimensional displacement field to determine the relative deformation of the joint in three-dimensional space. The relative deformation includes at least the opening perpendicular to the joint surface, the slip parallel to the joint surface, and the displacement perpendicular to the joint surface.

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