Structural health monitoring system and method for urban comprehensive pipe gallery

Abstract

The invention provides a structure health monitoring system and method for an urban comprehensive pipe gallery, and relates to the technical field of pipe gallery monitoring, a three-dimensional laser scanner is used for scanning the urban comprehensive pipe gallery, and pipe gallery point cloud data obtained through scanning are converted into gathered point cloud data; constructing a stress feature point location of the urban comprehensive pipe gallery, and carrying out stress alignment on the gathered point cloud data based on the stress feature point location to obtain aligned point cloud data of the urban comprehensive pipe gallery; performing neighborhood growth segmentation according to the geometric change degree of each aligned point cloud in the aligned point cloud data to obtain point cloud data of each structural region in the urban comprehensive pipe gallery, and determining a structural health feature set of the urban comprehensive pipe gallery according to the point cloud data of each structural region; and generating a structure health monitoring report of the urban comprehensive pipe gallery through the structure health feature set. According to the invention, the structural features of the urban comprehensive pipe gallery can be effectively extracted for detection, so that the monitoring precision of the urban comprehensive pipe gallery is improved.

Description

Technical Field

[0001] The present application relates to the technical field of pipeline corridor monitoring, and more specifically, to a structural health monitoring system and method for urban integrated pipeline corridors. Background Art

[0002] Structural health monitoring of urban utility corridors is a comprehensive management task based on modern engineering technology and intelligent means, which aims to ensure the long-term stability and safety of underground utility corridor structures. With the acceleration of urbanization, utility corridors, as key infrastructure that centrally carries municipal facilities (such as electricity, communications, water supply, drainage, etc.), have a direct impact on the efficiency and safety of urban operations due to their structural health.

[0003] Then, in the structural health monitoring of urban integrated pipeline corridors, due to the structural complexity of the pipeline corridor and human intervention factors, it is impossible to quickly and accurately find the common feature points of multiple measuring stations and achieve high-precision alignment through algorithms. At present, the deformation monitoring of integrated pipeline corridors adopts the method of replacing the whole with the local part, and reflects the overall deformation of the integrated pipeline corridor through the geometric shape and position state of the measuring point area. However, this detection method has problems such as limited detection area, single detection index, and low detection efficiency, which is difficult to meet the detection needs of the current integrated pipeline corridor operation and maintenance process. Therefore, how to effectively extract the structural characteristics of urban integrated pipeline corridors for detection to improve the monitoring accuracy of urban integrated pipeline corridors is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a structural health monitoring system and method for an urban integrated pipeline corridor, which can effectively extract the structural characteristics of the urban integrated pipeline corridor for detection, so as to improve the monitoring accuracy of the urban integrated pipeline corridor.

[0005] In a first aspect, the present application provides a structural health monitoring method for an urban integrated pipe gallery, the monitoring method comprising the following steps: Scanning the urban integrated pipe corridor using a three-dimensional laser scanner, and then converting the scanned pipe corridor point cloud data into aggregated point cloud data of the urban integrated pipe corridor; Constructing stress characteristic points of the urban integrated pipe corridor, and performing stress alignment on the aggregated point cloud data based on the stress characteristic points to obtain aligned point cloud data of the urban integrated pipe corridor; Performing neighborhood growth segmentation according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, thereby obtaining point cloud data of each structural area in the urban integrated pipe corridor, and determining a structural health feature set of the urban integrated pipe corridor according to the point cloud data of each structural area; A structural health monitoring report of the urban integrated pipeline corridor is generated through the structural health feature set.

[0006] In this embodiment, converting the scanned pipe gallery point cloud data into the aggregated point cloud data of the urban integrated pipe gallery specifically includes: For each pipe gallery point cloud in the pipe gallery point cloud data obtained by scanning, determining a division neighborhood corresponding to the pipe gallery point cloud; Determine the point cloud similarity between the pipeline corridor point cloud and the divided neighborhood; Determine a point cloud similarity interval according to the divided neighborhood; When the point cloud similarity is within the point cloud similarity interval, the pipeline corridor point cloud is used as an aggregated point cloud, thereby obtaining aggregated point cloud data of the urban integrated pipeline corridor.

[0007] In this embodiment, determining the point cloud similarity interval according to the divided neighborhood specifically includes: Determine the point cloud level and point cloud fluctuation through all the pipe gallery point clouds in the divided neighborhood; A point cloud similarity interval is constructed using the point cloud level and the point cloud fluctuation.

[0008] In this embodiment, constructing the stress characteristic points of the urban integrated pipe gallery specifically includes: identifying all overlapping regions in the aggregated point cloud data; Extract feature points from each overlapping area to obtain multiple force feature points; All stress characteristic points are optimized and selected to obtain the stress characteristic points of the urban integrated pipeline corridor.

[0009] In this embodiment, the force alignment of the aggregated point cloud data is performed based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery, which specifically includes: Constructing a force rotation matrix using the force characteristic points; Each clustered point cloud in the clustered point cloud data is rotated and aligned according to the force rotation matrix, so as to obtain the aligned point cloud data of the urban integrated pipeline corridor.

[0010] In this embodiment, the geometric change degree is an indicator used to represent the drastic degree of geometric change of the aligned point cloud in the aligned point cloud data.

[0011] In this embodiment, neighborhood growth segmentation is performed according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, and then point cloud data of each structural area in the urban integrated pipe gallery is obtained, which specifically includes: Sorting the aligned point clouds in the aligned point cloud data using the geometric variation degree, and then putting the aligned point cloud with the smallest geometric variation degree into the initial subset as the initial point cloud; Extracting a point cloud neighborhood of the initial point cloud from the aligned point cloud data, and determining a normal angle between the initial point cloud and each neighborhood point in the point cloud neighborhood; The neighborhood points whose normal angle is lower than the set angle threshold are placed in the growth point set, the neighborhood points whose geometric change degree in the point cloud neighborhood is lower than the set change threshold are placed in the initial subset, and the initial point cloud is deleted, and then the neighborhood points in the initial subset are used as the new initial point cloud, and the above steps are repeated until the initial subset is cleared; The final growth point set is used as the point cloud data of the structural area in the urban integrated pipeline corridor, and then the point cloud data of each structural area in the urban integrated pipeline corridor is obtained.

[0012] In this embodiment, determining the structural health feature set of the urban integrated pipe gallery according to the point cloud data of each structural area specifically includes: Feature extraction is performed on the point cloud data of each structural area respectively, thereby obtaining the longitudinal settlement feature, vertical deformation feature and lateral torsion feature of the urban integrated pipeline corridor; The data set consisting of the longitudinal settlement characteristics, the vertical deformation characteristics and the lateral torsion characteristics is used as the structural health feature set of the urban integrated pipeline corridor.

[0013] In this embodiment, generating the structural health monitoring report of the urban integrated pipe gallery by using the structural health feature set specifically includes: The longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics in the structural health characteristic set are analyzed respectively, thereby obtaining the longitudinal settlement analysis results, vertical deformation analysis results and lateral torsion analysis results of the urban integrated pipeline corridor; A structural health monitoring report of the urban integrated pipeline corridor is generated according to the longitudinal settlement analysis results, the vertical deformation analysis results and the lateral torsion analysis results.

[0014] In a second aspect, the present application provides a structural health monitoring system for an urban integrated pipe corridor, which is used to perform a structural health monitoring method for an urban integrated pipe corridor, and the monitoring system includes: A pipe gallery 3D scanning module is used to scan the urban integrated pipe gallery using a 3D laser scanner, and then convert the scanned pipe gallery point cloud data into aggregated point cloud data of the urban integrated pipe gallery; A point cloud force alignment module is used to construct the force characteristic points of the urban integrated pipe gallery, and perform force alignment on the aggregated point cloud data based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery; A health feature extraction module is used to perform neighborhood growth segmentation according to the geometric change degree of each aligned point cloud in the aligned point cloud data, thereby obtaining point cloud data of each structural area in the urban integrated pipe corridor, and determining the structural health feature set of the urban integrated pipe corridor according to the point cloud data of each structural area; A monitoring report generation module is used to generate a structural health monitoring report of the urban integrated pipeline corridor through the structural health feature set.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: The urban utility corridor is scanned by using a three-dimensional laser scanner, and then the point cloud data of the corridor obtained by the scan is converted into the aggregated point cloud data of the urban utility corridor; the stress characteristic points of the urban utility corridor are constructed, and the aggregated point cloud data are force aligned based on the stress characteristic points to obtain the aligned point cloud data of the urban utility corridor; neighborhood growth segmentation is performed according to the geometric change degree of each aligned point cloud in the aligned point cloud data to obtain the point cloud data of each structural area in the urban utility corridor, and the structural health feature set of the urban utility corridor is determined according to the point cloud data of each structural area; and a structural health monitoring report of the urban utility corridor is generated through the structural health feature set.

[0016] It can be seen that in this application, firstly, by converting the point cloud of the corridor, the effective aggregation of the point cloud data of the corridor can be achieved, which helps to improve the accuracy of the point cloud data; then, based on the force feature points, the aggregated point cloud data is force aligned, which can effectively improve the alignment accuracy of the point cloud data, enhance the accuracy of structural feature extraction, and improve the sensitivity and accuracy of the monitoring system; further, through growth segmentation, the various structural areas in the corridor can be accurately divided, and various local geometric deformations and structural differences can be effectively handled. Based on the structural health feature set, the health status of the urban integrated corridor can be fully reflected; finally, by conducting a detailed analysis of the longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics of the urban integrated corridor, a detailed structural health monitoring report can be generated to improve the monitoring accuracy of the urban integrated corridor.

[0017] To sum up, the technical solution adopted in this application can effectively extract the structural characteristics of the urban integrated pipeline corridor for detection, so as to improve the monitoring accuracy of the urban integrated pipeline corridor. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0019] Figure 1 It is a flow chart of the structural health monitoring method for urban integrated pipe corridor provided in this application; Figure 2 It is a schematic diagram of the flow of constructing the stress characteristic points of the urban integrated pipe gallery provided by this application; Figure 3 It is a schematic diagram of a process for determining a structural health feature set of an urban integrated pipe gallery according to the application; Figure 4 It is a module structure diagram of the structural health monitoring system for urban integrated pipeline corridors provided in this application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] The embodiment of the present application provides a structural health monitoring system and method for an urban integrated pipe corridor, the core of which is to use a three-dimensional laser scanner to scan the urban integrated pipe corridor, and then convert the scanned pipe corridor point cloud data into the aggregated point cloud data of the urban integrated pipe corridor; construct the stress characteristic points of the urban integrated pipe corridor, and perform stress alignment on the aggregated point cloud data based on the stress characteristic points to obtain the aligned point cloud data of the urban integrated pipe corridor; perform neighborhood growth segmentation based on the geometric variation of each aligned point cloud in the aligned point cloud data, and then obtain the point cloud data of each structural area in the urban integrated pipe corridor, determine the structural health feature set of the urban integrated pipe corridor based on the point cloud data of each structural area; and generate a structural health monitoring report of the urban integrated pipe corridor through the structural health feature set. The above scheme can effectively extract the structural features of the urban integrated pipe corridor for detection, so as to improve the monitoring accuracy of the urban integrated pipe corridor.

[0022] Embodiment 1: In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1As shown in the figure, this figure is an exemplary flow chart of a structural health monitoring method for an urban integrated pipe gallery according to this embodiment of the present application, and the monitoring method includes the following steps: In step S1, a three-dimensional laser scanner is used to scan the urban integrated pipeline corridor, and then the pipeline corridor point cloud data obtained by the scan is converted into aggregated point cloud data of the urban integrated pipeline corridor.

[0023] In specific implementation, a 3D laser scanner can be used to scan the urban integrated pipeline corridor, so as to obtain a 3D scanning result of the urban integrated pipeline corridor, that is, the point cloud data of the pipeline corridor; in actual implementation, a high-precision 3D laser scanner (with accuracy at the millimeter level and support for multi-angle scanning) can be selected for scanning, and multiple scanning stations can be deployed in the pipeline corridor according to the spatial structure, size and internal obstacles of the urban integrated pipeline corridor to ensure that the scanning covers the entire pipeline corridor. The scanning stations need to overlap with each other to ensure the integrity of the data and the accuracy of subsequent splicing.

[0024] In this embodiment, the scanned pipe gallery point cloud data is converted into the aggregated point cloud data of the urban integrated pipe gallery in the following manner, namely: For each pipe gallery point cloud in the pipe gallery point cloud data obtained by scanning, determining a division neighborhood corresponding to the pipe gallery point cloud; Determine the point cloud similarity between the pipeline corridor point cloud and the divided neighborhood; Determine a point cloud similarity interval according to the divided neighborhood; When the point cloud similarity is within the point cloud similarity interval, the pipeline corridor point cloud is used as an aggregated point cloud, thereby obtaining aggregated point cloud data of the urban integrated pipeline corridor.

[0025] In the specific implementation, first, for each corridor point cloud in the scanned corridor point cloud data, the distance between each corridor point cloud can be calculated by the Euclidean distance method. For a certain corridor point cloud, the K corridor point clouds closest to the corridor point cloud can be selected, and the neighborhood composed of the K corridor point clouds can be used as the corresponding division neighborhood of the corridor point cloud, where the value of K can be preset according to historical experience; then, the point cloud similarity between the corridor point cloud and the division neighborhood can be determined, where the point cloud similarity represents the degree of similarity between point data, and the mean value of the cosine similarity between the corridor point cloud and each corridor point cloud in the corresponding division neighborhood can be calculated. , so that the mean is used as the point cloud similarity between the corridor point cloud and the divided neighborhood; secondly, the point cloud similarity interval can be determined according to the divided neighborhood, and the point cloud similarity interval is an interval used to measure the size of the point cloud similarity; finally, when the point cloud similarity is within the point cloud similarity interval, it can be considered that the corridor point cloud has a high similarity with other corridor point clouds in the divided neighborhood, so the corridor point cloud can be used as a clustered point cloud. By judging each corridor point cloud in the corridor point cloud data as mentioned above, all corridor point clouds that meet the conditions can be marked and extracted, and finally a point cloud data set containing all clustered point clouds is obtained, namely, clustered point cloud data.

[0026] In this embodiment, the following method can be used to determine the point cloud similarity interval according to the neighborhood division, namely: Determine the point cloud level and point cloud fluctuation through all the pipe gallery point clouds in the divided neighborhood; A point cloud similarity interval is constructed using the point cloud level and the point cloud fluctuation.

[0027] In specific implementation, first, the point cloud level and point cloud fluctuation can be determined by dividing all the pipeline corridor point clouds in the neighborhood, wherein the point cloud level represents the average level of all pipeline corridor point clouds in the neighborhood, and the point cloud fluctuation represents the degree of fluctuation of all pipeline corridor point clouds in the neighborhood. The mean of all pipeline corridor point clouds in the neighborhood can be used as the point cloud level, and the standard deviation of all pipeline corridor point clouds in the neighborhood can be used as the point cloud fluctuation; then, the point cloud level and point cloud fluctuation can be used to construct a point cloud similarity interval, that is, the point cloud level minus 3 times the point cloud fluctuation can be used as the lower bound of the point cloud similarity interval, and the point cloud level plus 3 times the point cloud fluctuation can be used as the upper bound of the point cloud similarity interval. The point cloud similarity interval can be obtained in the above manner.

[0028] It should be noted that through the neighborhood division, similarity analysis and construction of point cloud similarity intervals of each corridor point cloud, the effective aggregation of corridor point cloud data can be achieved, which not only improves the accuracy of point cloud data, but also provides accurate basic data for subsequent structural health monitoring and maintenance decisions.

[0029] In step S2, the stress characteristic points of the urban integrated pipeline corridor are constructed, and the aggregated point cloud data are force aligned based on the stress characteristic points to obtain the aligned point cloud data of the urban integrated pipeline corridor.

[0030] Preferably, in this embodiment, the stress characteristic points of the urban integrated pipe gallery are constructed, referring to Figure 2 As shown, this figure is a schematic diagram of the process of constructing the stress characteristic points of the urban integrated pipe gallery in some embodiments of the present application. In this embodiment, the stress characteristic points of the urban integrated pipe gallery can be constructed by the following steps: First, in step S21, all overlapping areas in the aggregated point cloud data are identified; Then, in step S22, feature points are extracted from each overlapping area to obtain a plurality of force feature points; Finally, in step S23, all stress characteristic points are optimized and selected to obtain the stress characteristic points of the urban integrated pipeline corridor.

[0031] In the specific implementation, first, all overlapping areas in the gathered point cloud data can be identified. In the point cloud data obtained by multiple scans, different scans may cover the same area, so these areas need to be identified for subsequent processing. The point cloud registration algorithm (such as the ICP algorithm) can be used to align the multi-source point clouds so that the overlapping parts of the point cloud data at the same position are accurately aligned, and the overlapping areas between adjacent scans are identified by calculating the spatial distance, angle difference and other information of adjacent point cloud data; then, feature points can be extracted from each overlapping area, that is, curvature analysis, normal direction analysis, edge and corner point recognition are used to extract different geometric features (such as curvature, normal direction, edge density, etc.), so as to extract multiple force feature points in each overlapping area, and the position of the force feature points The position, stability and sensitivity of the stress characteristic points to the changes in the structure of the urban integrated pipeline corridor are representative; finally, in order to ensure that the selected stress characteristic points can effectively reflect the stress state of the urban integrated pipeline corridor, all stress characteristic points can be optimized and selected. The goal of the optimization is to minimize redundancy and improve the representativeness of the stress points, while ensuring that the structural state of the pipeline corridor can be accurately reflected. The extracted stress characteristic points can be reduced in dimension by the principal component analysis algorithm to identify the points that best represent the overall stress characteristics of the pipeline corridor. The spatial distribution of these points can evenly cover the key areas of the pipeline corridor, thereby obtaining the stress characteristic points of the urban integrated pipeline corridor. It should be noted that in this application, the stress characteristic points are representative points of the overall stress characteristics of the urban integrated pipeline corridor, and there are three stress characteristic points of the urban integrated pipeline corridor.

[0032] In this embodiment, the force alignment of the aggregated point cloud data is performed based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery in the following manner, namely: Constructing a force rotation matrix using the force characteristic points; Each clustered point cloud in the clustered point cloud data is rotated and aligned according to the force rotation matrix, so as to obtain the aligned point cloud data of the urban integrated pipeline corridor.

[0033] In the specific implementation, first, the force rotation matrix can be constructed using the force feature points, wherein the force rotation matrix is ​​a matrix used to control the rotation of the point cloud data, and the center of gravity position (center point) of all the force feature points can be calculated, that is, the average coordinates of all the force feature points, so that the least square method can be used to optimize the distance error between the force feature points to obtain the force rotation matrix, and the optimal rotation angle and direction can be automatically calculated by minimizing the misalignment of the point cloud in space; then, the various aggregated point clouds in the aggregated point cloud data can be rotated and aligned according to the force rotation matrix, that is, the aggregated point cloud is multiplied by the force rotation matrix, that is, the corresponding aligned point cloud is obtained, and the rotation alignment of each aggregated point cloud in the aggregated point cloud data can be completed in the above manner, so that the aligned point cloud data of the urban integrated pipeline corridor can be obtained. By applying the same force rotation matrix to all the aggregated point clouds, it is ensured that their relative position relationship in three-dimensional space is consistent with the alignment state of the force feature points, thereby realizing the rotation alignment of the point cloud data.

[0034] It should be noted that force alignment of clustered point cloud data based on stress feature points can effectively improve the alignment accuracy of point cloud data, enhance the accuracy of structural feature extraction, and improve the sensitivity and accuracy of the monitoring system. It not only helps to accurately identify potential problems in the tunnel, but also provides more efficient and accurate data support for the structural health monitoring system, thereby optimizing the inspection, maintenance and management strategies of the tunnel.

[0035] In step S3, neighborhood growth segmentation is performed according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, thereby obtaining the point cloud data of each structural area in the urban integrated pipeline corridor, and the structural health feature set of the urban integrated pipeline corridor is determined according to the point cloud data of each structural area.

[0036] It should be noted that, in the present application, the geometric variation degree is an indicator used to represent the severity of the geometric variation of the aligned point cloud in the aligned point cloud data; in specific implementation, for each aligned point cloud in the aligned point cloud data, the Gaussian curvature of the aligned point cloud can be calculated, and the result can be used as the geometric variation degree of the aligned point cloud. The geometric variation degree of each aligned point cloud in the aligned point cloud data can be obtained in the above manner.

[0037] In this embodiment, neighborhood growth segmentation is performed according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, and then point cloud data of each structural area in the urban integrated pipe gallery is obtained in the following manner, namely: Sorting the aligned point clouds in the aligned point cloud data using the geometric variation degree, and then putting the aligned point cloud with the smallest geometric variation degree into the initial subset as the initial point cloud; Extracting a point cloud neighborhood of the initial point cloud from the aligned point cloud data, and determining a normal angle between the initial point cloud and each neighborhood point in the point cloud neighborhood; The neighborhood points whose normal angle is lower than the set angle threshold are placed in the growth point set, the neighborhood points whose geometric change degree in the point cloud neighborhood is lower than the set change threshold are placed in the initial subset, and the initial point cloud is deleted, and then the neighborhood points in the initial subset are used as the new initial point cloud, and the above steps are repeated until the initial subset is cleared; The final growth point set is used as the point cloud data of the structural area in the urban integrated pipeline corridor, and then the point cloud data of each structural area in the urban integrated pipeline corridor is obtained.

[0038] In specific implementation, first, the geometric variation of each aligned point cloud in the aligned point cloud data can be sorted to obtain an aligned point cloud sequence, and the aligned point cloud with the smallest geometric variation in the aligned point cloud sequence can be put into the initial subset as the initial point cloud; then, the point cloud neighborhood of the initial point cloud can be extracted from the aligned point cloud data, a spatial threshold can be set (for example, a distance or a neighborhood radius can be set), and the aligned point cloud can be extracted from the aligned point cloud data with the initial point cloud as the center, and the extracted aligned point cloud can be used as the neighborhood point, so that the point cloud neighborhood of the initial point cloud can be obtained; further, the normal vectors of the initial point cloud and each neighborhood point in the point cloud neighborhood of the initial point cloud can be calculated by the least squares method, and the normal angle between the initial point cloud and each neighborhood point in the point cloud neighborhood can be calculated according to the normal vector.

[0039] In addition, in the specific implementation, first, the neighborhood points whose normal angles are lower than the set angle threshold can be put into the growth point set. The growth point set refers to the points with small morphological changes and consistent normal directions within the current neighborhood range. These points represent local stable areas and meet the characteristics of the same structural area; then, the neighborhood points in the point cloud neighborhood whose geometric changes are lower than the set change threshold can be put into the initial subset, and the initial point cloud can be deleted, so that the neighborhood points in the initial subset are used as the new initial point cloud, and the above steps are repeated until the initial subset is cleared. With the gradual addition of neighborhood points, the point cloud in the initial subset gradually decreases until the initial subset is empty. is cleared, and whenever new neighborhood points are added, they will serve as new initial point clouds and continue the neighborhood growth operation. This process will be repeated until all neighborhood points are classified and added to the corresponding growth point sets. Finally, when the initial subset is completely cleared, the point cloud in the growth point set is all the point cloud data of the structural area. Each growth point set represents a structural area in the corridor (such as the bottom, top, and side of the comprehensive corridor), that is, the final growth point set can be used as the point cloud data of the structural area in the urban comprehensive corridor. The point cloud data of each structural area in the urban comprehensive corridor can be obtained in the above manner.

[0040] It should be noted that through the analysis of geometric variation and normal angle, the various structural areas in the corridor can be accurately divided. For complex corridor structures, neighborhood growth segmentation can effectively handle various local geometric deformations and structural differences, adapt to the division of structural areas of different shapes, scales and complexities, and help to accurately extract point cloud data of each structural area of ​​the corridor, providing more reliable data support for subsequent structural health monitoring, fault detection and maintenance decisions.

[0041] Preferably, in this embodiment, the structural health feature set of the urban integrated pipe gallery is determined according to the point cloud data of each structural area, referring to Figure 3 As shown, this figure is a schematic diagram of the process of determining the structural health feature set of the urban integrated pipe corridor in some embodiments of the present application. In this embodiment, the structural health feature set of the urban integrated pipe corridor can be determined by the following steps: First, in step S31, feature extraction is performed on the point cloud data of each structural area, thereby obtaining the longitudinal settlement feature, vertical deformation feature and lateral torsion feature of the urban integrated pipe gallery; Then, in step S32, the data set consisting of the longitudinal settlement characteristics, the vertical deformation characteristics and the lateral torsion characteristics is used as the structural health feature set of the urban integrated pipeline corridor.

[0042] In specific implementation, feature extraction can be performed on the point cloud data of each structural area respectively. That is, for the point cloud data of the bottom surface of the urban integrated pipeline corridor, the key points of the bottom surface of the urban integrated pipeline corridor can be selected and the height changes of these points can be calculated, so as to use the Z coordinate difference of the point cloud data to obtain the settlement of each point, and the average of the settlement of each point is used as the longitudinal settlement feature of the urban integrated pipeline corridor. The longitudinal settlement feature refers to the displacement of the urban integrated pipeline corridor structure in the vertical direction; the vertical deformation feature refers to the morphological change of the pipeline corridor structure in the vertical direction caused by factors such as pressure and settlement. The vertical deformation characteristics can be extracted through surface analysis of the point cloud data on the top surface of the urban integrated pipeline corridor, for example, calculating the local curvature of the point cloud and analyzing whether there are abnormal deformations on the corridor surface, such as local depressions or protrusions. The lateral torsion feature represents the degree of rotation and distortion of the urban integrated pipeline corridor structure in the horizontal direction. The normal direction of each point in the point cloud data on the side of the urban integrated pipeline corridor can be calculated, and the changes in the normals of adjacent points can be analyzed. The lateral torsion can be estimated through the local rotation transformation model of the point cloud (for example, rotation matrix or local principal component analysis), thereby obtaining the lateral torsion feature.

[0043] It should be noted that by extracting longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics from each structural area and forming them into a structural health feature set, the health status of the urban integrated pipeline corridor can be fully reflected, providing strong data support for subsequent health assessment and fault diagnosis, and helping to accurately monitor the structural changes of the pipeline corridor and realize timely maintenance, thereby improving the safety and reliability of urban infrastructure.

[0044] In step S4, a structural health monitoring report of the urban integrated pipe corridor is generated by using the structural health feature set.

[0045] In this embodiment, the structural health monitoring report of the urban integrated pipe gallery is generated by the structural health feature set in the following manner, namely: The longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics in the structural health characteristic set are analyzed respectively, thereby obtaining the longitudinal settlement analysis results, vertical deformation analysis results and lateral torsion analysis results of the urban integrated pipeline corridor; A structural health monitoring report of the urban integrated pipeline corridor is generated according to the longitudinal settlement analysis results, the vertical deformation analysis results and the lateral torsion analysis results.

[0046] In specific implementation, it can be determined whether the longitudinal settlement feature in the structural health feature set exceeds the set settlement threshold. If it exceeds the set threshold, the longitudinal settlement analysis result should indicate that the urban integrated pipeline corridor has settlement or sinking in the vertical direction, and the abnormal settlement area should be marked and the cause of the settlement should be analyzed, for example, abnormal settlement caused by factors such as soil settlement, uneven foundation settlement or settlement of the pipeline itself; it should be noted that in this application, the vertical deformation characteristics and lateral torsion characteristics can be analyzed in the same way to obtain the vertical deformation analysis results and lateral torsion analysis results of the urban integrated pipeline corridor; finally, the longitudinal settlement analysis results, the vertical deformation analysis results and the lateral torsion analysis results can be integrated to generate a structural health monitoring report.

[0047] It should be noted that by conducting a detailed analysis of the longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics of the urban integrated pipeline corridor, a detailed structural health monitoring report can be generated to improve the monitoring accuracy of the urban integrated pipeline corridor.

[0048] It can be seen that in this application, firstly, by converting the point cloud of the corridor, the effective aggregation of the point cloud data of the corridor can be achieved, which helps to improve the accuracy of the point cloud data; then, based on the force feature points, the aggregated point cloud data is force aligned, which can effectively improve the alignment accuracy of the point cloud data, enhance the accuracy of structural feature extraction, and improve the sensitivity and accuracy of the monitoring system; further, through growth segmentation, the various structural areas in the corridor can be accurately divided, and various local geometric deformations and structural differences can be effectively handled. Based on the structural health feature set, the health status of the urban integrated corridor can be fully reflected; finally, by conducting a detailed analysis of the longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics of the urban integrated corridor, a detailed structural health monitoring report can be generated to improve the monitoring accuracy of the urban integrated corridor.

[0049] To sum up, the technical solution adopted in this application can effectively extract the structural characteristics of the urban integrated pipeline corridor for detection, so as to improve the monitoring accuracy of the urban integrated pipeline corridor.

[0050] Embodiment 2: This application provides a structural health monitoring system for an urban integrated pipe gallery, referring to Figure 4 As shown, this figure is a schematic diagram of a structural health monitoring system for an urban integrated pipe gallery according to this embodiment of the present application, and the monitoring system includes: The pipeline corridor 3D scanning module 100 is used to scan the urban integrated pipeline corridor using a 3D laser scanner, and then convert the pipeline corridor point cloud data obtained by scanning into the aggregated point cloud data of the urban integrated pipeline corridor; The point cloud force alignment module 200 is used to construct the force characteristic points of the urban integrated pipe gallery, and perform force alignment on the aggregated point cloud data based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery; The health feature extraction module 300 is used to perform neighborhood growth segmentation according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, thereby obtaining the point cloud data of each structural area in the urban integrated pipe corridor, and determining the structural health feature set of the urban integrated pipe corridor according to the point cloud data of each structural area; The monitoring report generation module 400 is used to generate a structural health monitoring report of the urban integrated pipe corridor through the structural health feature set.

[0051] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0052] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0053] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A structural health monitoring method for an urban integrated pipe gallery, characterized in that: The monitoring method comprises the following steps: Scanning the urban integrated pipe corridor using a three-dimensional laser scanner, and then converting the scanned pipe corridor point cloud data into aggregated point cloud data of the urban integrated pipe corridor; Constructing stress characteristic points of the urban integrated pipe corridor, and performing stress alignment on the aggregated point cloud data based on the stress characteristic points to obtain aligned point cloud data of the urban integrated pipe corridor; Performing neighborhood growth segmentation according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, thereby obtaining point cloud data of each structural area in the urban integrated pipe corridor, and determining a structural health feature set of the urban integrated pipe corridor according to the point cloud data of each structural area; A structural health monitoring report of the urban integrated pipeline corridor is generated through the structural health feature set.

2. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 1, characterized in that: Converting the scanned pipe gallery point cloud data into the aggregated point cloud data of the urban integrated pipe gallery specifically includes: For each pipe gallery point cloud in the pipe gallery point cloud data obtained by scanning, determining a division neighborhood corresponding to the pipe gallery point cloud; Determine the point cloud similarity between the pipeline corridor point cloud and the divided neighborhood; Determine a point cloud similarity interval according to the divided neighborhood; When the point cloud similarity is within the point cloud similarity interval, the pipeline corridor point cloud is used as an aggregated point cloud, thereby obtaining aggregated point cloud data of the urban integrated pipeline corridor.

3. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 2, characterized in that: Determining the point cloud similarity interval according to the divided neighborhood specifically includes: Determine the point cloud level and point cloud fluctuation through all the pipe gallery point clouds in the divided neighborhood; A point cloud similarity interval is constructed using the point cloud level and the point cloud fluctuation.

4. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 1, characterized in that: The stress characteristic points for constructing the urban integrated pipe gallery specifically include: identifying all overlapping regions in the aggregated point cloud data; Extract feature points from each overlapping area to obtain multiple force feature points; All stress characteristic points are optimized and selected to obtain the stress characteristic points of the urban integrated pipeline corridor.

5. The structural health monitoring method for an urban integrated pipe gallery according to claim 1, characterized in that: The force alignment of the aggregated point cloud data based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery specifically includes: Constructing a force rotation matrix using the force characteristic points; Each clustered point cloud in the clustered point cloud data is rotated and aligned according to the force rotation matrix, so as to obtain the aligned point cloud data of the urban integrated pipeline corridor.

6. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 1, characterized in that: The geometric change degree is an indicator used to indicate the severity of the geometric change of the aligned point cloud in the aligned point cloud data.

7. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 1, characterized in that: Neighborhood growth segmentation is performed according to the geometric variation degree of each aligned point cloud in the aligned point cloud data, thereby obtaining point cloud data of each structural area in the urban integrated pipe gallery, which specifically includes: Sorting the aligned point clouds in the aligned point cloud data using the geometric variation degree, and then putting the aligned point cloud with the smallest geometric variation degree into the initial subset as the initial point cloud; Extracting a point cloud neighborhood of the initial point cloud from the aligned point cloud data, and determining a normal angle between the initial point cloud and each neighborhood point in the point cloud neighborhood; The neighborhood points whose normal angle is lower than the set angle threshold are placed in the growth point set, the neighborhood points whose geometric change degree in the point cloud neighborhood is lower than the set change threshold are placed in the initial subset, and the initial point cloud is deleted, and then the neighborhood points in the initial subset are used as the new initial point cloud, and the above steps are repeated until the initial subset is cleared; The final growth point set is used as the point cloud data of the structural area in the urban integrated pipeline corridor, and then the point cloud data of each structural area in the urban integrated pipeline corridor is obtained.

8. The structural health monitoring method for an urban integrated pipe gallery according to claim 1, characterized in that: The structural health feature set of the urban integrated pipe gallery determined based on the point cloud data of each structural area specifically includes: Feature extraction is performed on the point cloud data of each structural area respectively, thereby obtaining the longitudinal settlement feature, vertical deformation feature and lateral torsion feature of the urban integrated pipeline corridor; The data set consisting of the longitudinal settlement characteristics, the vertical deformation characteristics and the lateral torsion characteristics is used as the structural health feature set of the urban integrated pipeline corridor.

9. A structural health monitoring method for an urban integrated pipe gallery as claimed in claim 1, characterized in that: Generating the structural health monitoring report of the urban integrated pipe gallery through the structural health feature set specifically includes: The longitudinal settlement characteristics, vertical deformation characteristics and lateral torsion characteristics in the structural health characteristic set are analyzed respectively, thereby obtaining the longitudinal settlement analysis results, vertical deformation analysis results and lateral torsion analysis results of the urban integrated pipeline corridor; A structural health monitoring report of the urban integrated pipeline corridor is generated according to the longitudinal settlement analysis results, the vertical deformation analysis results and the lateral torsion analysis results.

10. A structural health monitoring system for an urban integrated utility corridor, used to execute a structural health monitoring method for an urban integrated utility corridor as claimed in any one of claims 1 to 9, characterized in that: The monitoring system comprises: A pipe gallery 3D scanning module is used to scan the urban integrated pipe gallery using a 3D laser scanner, and then convert the scanned pipe gallery point cloud data into aggregated point cloud data of the urban integrated pipe gallery; A point cloud force alignment module is used to construct the force characteristic points of the urban integrated pipe gallery, and perform force alignment on the aggregated point cloud data based on the force characteristic points to obtain the aligned point cloud data of the urban integrated pipe gallery; A health feature extraction module is used to perform neighborhood growth segmentation according to the geometric change degree of each aligned point cloud in the aligned point cloud data, thereby obtaining point cloud data of each structural area in the urban integrated pipe corridor, and determining the structural health feature set of the urban integrated pipe corridor according to the point cloud data of each structural area; A monitoring report generation module is used to generate a structural health monitoring report of the urban integrated pipeline corridor through the structural health feature set.

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