Verticality Detection Method and System for Settlement Observation Rod

Abstract

The present invention discloses a method and system for detecting the perpendicularity of a settlement observation rod. The present invention relates to the technical field of settlement observation rods. Based on the positioning target board and the settlement observation rod in the monitoring area, point cloud data of the monitoring area is collected; the target board point cloud and the settlement observation rod point cloud are determined based on the screening of the point cloud data; the thickness of the target board point cloud is determined according to the detection of the target board point cloud; based on the identification of the thickness of the target board point cloud, the inclination of the target board is determined, thereby ensuring the accuracy of the thickness of the target board point cloud. Further, a perpendicularity model of the target board and the settlement observation rod is collected; based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, the perpendicularity of the settlement observation rod is determined, realizing the multi-dimensional control of the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, and ensuring the accuracy of the perpendicularity of the settlement observation rod.

Description

Technical Field

[0001] The present invention relates to the technical field of settlement observation rods, and in particular, to a method and system for detecting the verticality of settlement observation rods. Background Art

[0002] With the rapid development of infrastructure construction, especially in the continuous operation and maintenance stage, deformation monitoring has become a key link in ensuring project safety. Particularly in the fields of large-scale civil engineering, urban construction, and geological disaster prevention and control, settlement observation is an important means to ensure the long-term stable operation of these facilities. As an important tool for monitoring soil settlement, the verticality of the settlement observation rod has an important impact on the accuracy of settlement data. In the prior art, for the verticality of the settlement observation rod, manual detection is carried out on the settlement observation rod and controlled along a single dimension, which cannot ensure the accuracy of the verticality of the settlement observation rod. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a method and system for detecting the verticality of a settlement observation rod, which are based on a positioning target board and a settlement observation rod in a monitoring area, and collect point cloud data of the monitoring area; determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data; determine the thickness of the target board point cloud according to the detection of the target board point cloud; determine the inclination of the target board based on the recognition of the thickness of the target board point cloud, introduce the target board point cloud and the settlement observation rod point cloud, and control the target board point cloud and the settlement observation rod point cloud to ensure the accuracy of the thickness of the target board point cloud.

[0004] Furthermore, collect the verticality model of the target board and the settlement observation rod; determine the verticality of the settlement observation rod based on the verticality model of the target board and the settlement observation rod and the inclination of the target board, which comprehensively considers the verticality model of the target board and the settlement observation rod and the inclination of the target board, realizes multi-dimensional control of the verticality model of the target board and the settlement observation rod and the inclination of the target board, and ensures the accuracy of the verticality of the settlement observation rod.

[0005] An embodiment of the present invention provides a method for detecting the verticality of a settlement observation rod, which is applied to the scenario of detecting the verticality of a settlement observation rod;

[0006] The method for detecting the verticality of the settlement observation rod includes:

[0007] Based on a positioning target board and a settlement observation rod in a monitoring area, and collect point cloud data of the monitoring area;

[0008] Determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data;

[0009] Determine the thickness of the target board point cloud according to the detection of the target board point cloud;

[0010] Determine the inclination of the target board based on the recognition of the thickness of the target board point cloud;

[0011] Collect the perpendicularity model of the target board and the settlement observation rod;

[0012] Determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board.

[0013] Optionally, positioning the target board and the settlement observation rod based on the monitoring area and collecting point cloud data for the monitoring area, including:

[0014] Locate the monitoring area;

[0015] Locate the target board and the settlement observation rod based on the monitoring area;

[0016] Scan the monitoring area;

[0017] Collect point cloud data based on the scan of the monitoring area.

[0018] Optionally, determining the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data, including:

[0019] Freeze the point cloud data;

[0020] Denoise the point cloud data and screen the point cloud data;

[0021] Collect multiple point cloud regions based on the screening of the point cloud data;

[0022] Determine the target board point cloud and the settlement observation rod point cloud based on the recognition of multiple point cloud regions.

[0023] Optionally, determining the thickness of the target board point cloud according to the detection of the target board point cloud, including:

[0024] Freeze the target board point cloud;

[0025] Associate the target board point cloud and the corresponding detection model;

[0026] Determine the distribution of the target board point cloud based on the target board point cloud and the corresponding detection model;

[0027] Determine the thickness of the target board point cloud according to the distribution of the target board point cloud.

[0028] Optionally, determining the inclination of the target board based on the recognition of the thickness of the target board point cloud, including:

[0029] Freeze the thickness of the target board point cloud;

[0030] Compare the thickness of the target board point cloud with a preset thickness threshold;

[0031] The recognition of the thickness of the target board point cloud is triggered based on the comparison between the thickness of the target board point cloud and a preset thickness threshold;

[0032] Associate the thickness of the target board point cloud with the inclination recognition model;

[0033] Determine the inclination of the target board according to the recognition of the thickness of the target board point cloud and the inclination recognition model.

[0034] Optionally, the perpendicularity model for collecting the target board and the settlement observation rod includes:

[0035] Freeze the settlement observation rod;

[0036] Determine the perpendicularity model of the settlement observation rod based on the matching of the settlement observation rod.

[0037] Optionally, the perpendicularity model for collecting the target board and the settlement observation rod further includes:

[0038] Collect the target board;

[0039] Associate the perpendicularity model of the target board and the settlement observation rod.

[0040] Optionally, determining the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board includes:

[0041] Freeze the inclination of the target board;

[0042] Collect the perpendicularity model of the target board and the settlement observation rod;

[0043] Associate the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board.

[0044] Optionally, determining the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board further includes:

[0045] Determine a first parameter based on the perpendicularity model of the target board and the settlement observation rod;

[0046] Determine a second parameter based on the target board and the inclination of the target board;

[0047] Determine the perpendicularity of the settlement observation rod according to the first parameter, the second parameter and the settlement observation rod.

[0048] In addition, an embodiment of the present invention further provides a perpendicularity detection system for a settlement observation rod, and the perpendicularity detection system for the settlement observation rod includes:

[0049] A first acquisition module, configured to locate the target board and the settlement observation rod based on a monitoring area and acquire point cloud data of the monitoring area;

[0050] A screening module, configured to determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data;

[0051] A thickness module, configured to determine the thickness of the target board point cloud according to the detection of the target board point cloud;

[0052] An inclination module, configured to determine the inclination of the target board based on the recognition of the thickness of the target board point cloud;

[0053] A second acquisition module, configured to acquire the perpendicularity model of the target board and the settlement observation rod;

[0054] A perpendicularity module, configured to determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod, the inclination of the target board.

[0055] In an embodiment of the present invention, by the method in the embodiment of the present invention, the target board and the settlement observation rod are located based on the monitoring area, and the point cloud data of the monitoring area is acquired; the target board point cloud and the settlement observation rod point cloud are determined based on the screening of the point cloud data; the thickness of the target board point cloud is determined according to the detection of the target board point cloud; the inclination of the target board is determined based on the recognition of the thickness of the target board point cloud. The target board point cloud and the settlement observation rod point cloud are introduced, and the target board point cloud and the settlement observation rod point cloud are controlled to ensure the accuracy of the thickness of the target board point cloud.

[0056] Furthermore, the perpendicularity model of the target board and the settlement observation rod is acquired; the perpendicularity of the settlement observation rod is determined based on the perpendicularity model of the target board and the settlement observation rod, the inclination of the target board, which comprehensively considers the perpendicularity model of the target board and the settlement observation rod, the inclination of the target board, realizes the multi-dimensional control of the perpendicularity model of the target board and the settlement observation rod, the inclination of the target board, and ensures the accuracy of the perpendicularity of the settlement observation rod. Description of the Drawings

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1 is a schematic flowchart of the method for detecting the perpendicularity of the settlement observation rod in the embodiment of the present invention;

[0059] Figure 2 is a schematic flowchart of S11 in the method for detecting the perpendicularity of the settlement observation rod in the embodiment of the present invention;

[0060] Figure 3 It is a schematic flowchart of S12 in the verticality detection method of the settlement observation rod in the embodiment of the present invention;

[0061] Figure 4 It is a schematic flowchart of S13 in the verticality detection method of the settlement observation rod in the embodiment of the present invention;

[0062] Figure 5 It is a schematic flowchart of S14 in the verticality detection method of the settlement observation rod in the embodiment of the present invention;

[0063] Figure 6 It is a schematic flowchart of S15 in the verticality detection method of the settlement observation rod in the embodiment of the present invention;

[0064] Figure 7 It is a schematic flowchart of S16 in the verticality detection method of the settlement observation rod in the embodiment of the present invention;

[0065] Figure 8 It is a schematic diagram of the structural composition of the verticality detection system of the settlement observation rod in the embodiment of the present invention;

[0066] Figure 9 It is a hardware diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0067] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0068] Please refer to Figures 1 to 9 , a verticality detection method for a settlement observation rod, which is applied to the verticality detection scenario of the settlement observation rod; the verticality detection method for the settlement observation rod includes:

[0069] Step S11: Locate the target board and the settlement observation rod based on the monitoring area, and collect point cloud data for the monitoring area;

[0070] Step S12: Determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data;

[0071] Step S13: Determine the thickness of the target board point cloud based on the detection of the target board point cloud;

[0072] Step S14: Determine the inclination of the target board based on the recognition of the thickness of the target board point cloud;

[0073] Step S15: Collect the perpendicularity model of the target board and the settlement observation rod;

[0074] Step S16: Determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board.

[0075] In the embodiment of the present invention, through the method in the embodiment of the present invention, the target board and the settlement observation rod are positioned based on the monitoring area, and the point cloud data of the monitoring area is collected; the point cloud of the target board and the point cloud of the settlement observation rod are determined based on the screening of the point cloud data; the thickness of the point cloud of the target board is determined according to the detection of the point cloud of the target board; the inclination of the target board is determined based on the recognition of the thickness of the point cloud of the target board. The point cloud of the target board and the point cloud of the settlement observation rod are introduced, and the point cloud of the target board and the point cloud of the settlement observation rod are controlled, ensuring the accuracy of the thickness of the point cloud of the target board.

[0076] Furthermore, collect the perpendicularity model of the target board and the settlement observation rod; determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, which comprehensively considers the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, realizes the multi-dimensional control of the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, and ensures the accuracy of the perpendicularity of the settlement observation rod.

[0077] Reference Figure 2 , in step S11, the target board and the settlement observation rod are positioned based on the monitoring area, and the point cloud data of the monitoring area is collected;

[0078] In the specific implementation process of the present invention, the specific steps may be:

[0079] S111: Locate the monitoring area;

[0080] S112: Locate the target board and the settlement observation rod based on the monitoring area;

[0081] S113: Scan the monitoring area;

[0082] S114: Collect the point cloud data based on the scan of the monitoring area.

[0083] In the embodiment of the present application, the monitoring area is located, the monitoring area is introduced, and the monitoring area is further controlled, so that the target board and the settlement observation rod are located based on the monitoring area, realizing the positioning of the target board and the settlement observation rod.

[0084] Specifically, through on-site investigation, reviewing drawings and materials, etc., detailed information of the monitoring area is collected, including topography, geological conditions, building structures, surrounding environment, etc. According to the monitoring purpose and on-site data, the specific scope of the monitoring area is determined. The specific scope should cover all areas that may be affected by settlement.

[0085] At this time, several fixed points are selected within the monitoring area as the positions for the target plates. These points should be far away from possible interference sources, such as strong light sources, reflective surfaces, etc., to ensure the accuracy of the observation data. At the same time, the points should be easy to identify and measure. Install the target plates at the selected positions. The target plates should be firmly fixed on the ground or the building and maintain a good line-of-sight connection with the observation equipment. The design of the target plates should meet the requirements of the observation equipment so that they can be clearly identified and measured. According to the monitoring plan, determine the positions of the settlement observation rods on the building or other structures. These positions should be able to sensitively reflect the settlement changes of the structures and be convenient for observation and measurement. Install the settlement observation rods at the selected positions. The settlement observation rods should be firmly installed on the structures and maintain good contact with the structures. At the same time, the height and inclination angle of the observation rods should be adjusted according to the on-site conditions to ensure the accuracy of the observation data.

[0086] At the same time, scan the monitoring area to facilitate the scanning of the monitoring area, thereby collecting point cloud data based on the scanning of the monitoring area, introducing the point cloud data, and achieving the control of the point cloud data for subsequent processing of the point cloud data.

[0087] At this time, arrange several scanning stations within the monitoring area. Each station should be able to cover a certain area and ensure that there is sufficient overlapping area between adjacent stations for subsequent point cloud stitching. At each scanning station, use the scanning equipment to scan the monitoring area. Ensure the stability of the equipment during the scanning process to avoid vibration and interference. At the same time, pay attention to recording the scanning data and position information of each station.

[0088] After the scanning is completed, export the scanning data from the scanning equipment. These data usually exist in the form of point clouds and contain the three-dimensional coordinate information of all objects within the monitoring area. Preprocess the exported point cloud data, including steps such as denoising, filtering, and registration. Denoising is to remove the noise points generated during the scanning process; filtering is to smooth the point cloud data and improve the accuracy of the data; registration is to stitch the point cloud data of different stations together to form a complete three-dimensional model. Conduct a quality inspection on the preprocessed point cloud data to ensure the integrity and accuracy of the data. The inspection content includes the density, resolution, accuracy, etc. of the point cloud. Store the point cloud data that has passed the quality inspection in a suitable storage medium and establish a corresponding data management system for subsequent data analysis and application.

[0089] Reference Figure 3 In step S12, the target board point cloud and the settlement observation rod point cloud are determined based on the screening of the point cloud data.

[0090] In the specific implementation process of the present invention, the specific steps may be:

[0091] S121: Freeze the point cloud data;

[0092] S122: Denoise the point cloud data and screen the point cloud data;

[0093] S123: Collect multiple point cloud regions according to the screening of the point cloud data;

[0094] S124: Determine the target board point cloud and the settlement observation rod point cloud based on the recognition of multiple point cloud regions.

[0095] In the embodiment of the present application, the point cloud data is frozen and controlled. At the same time, the point cloud data is denoised and screened to facilitate the abnormal control of the point cloud data, and the abnormal point cloud is removed, thus ensuring the screening of the point cloud data.

[0096] At this time, the scanning device is started to scan the target object. During the scanning process, the device will capture a large amount of three-dimensional point data on the surface of the object, save the scanned point cloud data in a specific file format, such as PCD, PLY or OBJ, etc., and save the point cloud data.

[0097] Furthermore, by analyzing the local neighborhood data of each point in the point cloud, noise removal is performed based on statistical characteristics. For example, the statistical outlier removal (SOR) method calculates the standard deviation of the distances within the neighborhood of each point. If the average distance of a point is much greater than the average distance of other points in the neighborhood, then this point is regarded as a noise point and removed. By dividing the point cloud data into small voxels (similar to a three-dimensional grid) and aggregating the points within each voxel into a representative point, the noise in the data is reduced. This method can reduce excessive detail points and noise points while retaining the overall geometric structure. By performing smoothing processing on each point in the point cloud using a Gaussian function, the local noise is weakened. Gaussian filtering performs weighted averaging on each point according to the Gaussian function. The closer the points in the neighborhood are to the center point, the greater the weight, thus suppressing the noise points far from the center.

[0098] Therefore, multiple point cloud regions are collected according to the screening of the point cloud data; the target board point cloud and the settlement observation rod point cloud are determined based on the recognition of multiple point cloud regions. The recognition of multiple point cloud regions is introduced to ensure the further control of multiple point cloud regions. The target board point cloud and the settlement observation rod point cloud are introduced, thereby further controlling the target board point cloud and the settlement observation rod point cloud.

[0099] At this time, the target board usually has specific geometric shapes and color features, such as circular, square, or cross-shaped, etc., and may have specific color markings. Therefore, the target board point cloud is identified by searching for point cloud regions with these features. The settlement observation rod usually has a slender and upright shape and may be located at specific positions of the building (such as near the corner or column). Therefore, we can identify the settlement observation rod point cloud by searching for point cloud regions with these shape and position features.

[0100] Reference Figure 4 , in step S13, the thickness of the target board point cloud is determined according to the detection of the target board point cloud;

[0101] In the specific implementation process of the present invention, the specific steps may be:

[0102] S131: Freeze the target board point cloud;

[0103] S132: Associate the target board point cloud with the corresponding detection model;

[0104] S133: Determine the distribution of the target board point cloud based on the target board point cloud and the corresponding detection model;

[0105] S134: Determine the thickness of the target board point cloud according to the distribution of the target board point cloud.

[0106] In the embodiment of the present application, by freezing the target board point cloud and further controlling the target board point cloud, the target board point cloud and the corresponding detection model are introduced, so as to associate the target board point cloud with the corresponding detection model, realizing further control of the target board point cloud and the corresponding detection model.

[0107] At this time, load the pre-established detection model, which may be a 3D CAD model, a digital twin model, or other forms of 3D representation. Use point cloud registration technology to align the scanned target board point cloud data with the detection model. The registration process may involve transformation operations such as rotation and translation to ensure the spatial consistency between the point cloud data and the model. After the registration is completed, error analysis is performed to evaluate the accuracy of the registration.

[0108] Therefore, determining the distribution of the target board point cloud based on the target board point cloud and the corresponding detection model takes into account the overall consideration of the target board point cloud and the corresponding detection model, realizes multi-dimensional control of the target board point cloud and the corresponding detection model, ensures the accuracy of the distribution of the target board point cloud, and thus determines the thickness of the target board point cloud according to the distribution of the target board point cloud, ensuring the accuracy of the thickness of the target board point cloud.

[0109] At this time, preprocess the target board point cloud data, including removing noise, filtering out irrelevant points, etc., to ensure the accuracy of the data, and match the preprocessed target board point cloud data with the detection model. This is usually achieved by comparing the feature points or feature planes in the point cloud to ensure that the position and orientation of the point cloud data and the model are consistent in three-dimensional space. After the matching is completed, analyze the distribution characteristics of the target board point cloud data. This includes determining features such as the distribution range, density, and directionality of the point cloud to reveal the specific distribution state of the target board in three-dimensional space.

[0110] Furthermore, extract feature points from the target board point cloud data. These feature points are usually located at specific positions on the edge or surface of the target board. For each feature point, calculate its coordinate value on the Z-axis (or depth axis), and determine the maximum depth value and the minimum depth value. The thickness of the target board can be calculated by the difference between these two depth values. Based on the calculated depth difference value, analyze the thickness of the target board. This can include determining statistical quantities such as the average value and standard deviation of the thickness to reveal the uniformity and consistency of the target board thickness.

[0111] Reference Figure 5 , S14: Determine the inclination of the target board based on the identification of the thickness of the target board point cloud;

[0112] In the specific implementation process of the present invention, the specific steps can be:

[0113] S141: Freeze the thickness of the target board point cloud;

[0114] S142: Compare the thickness of the target board point cloud with a preset thickness threshold;

[0115] S143: Trigger the identification of the thickness of the target board point cloud based on the comparison between the thickness of the target board point cloud and the preset thickness threshold;

[0116] S144: Associate the thickness of the target board point cloud with the inclination identification model;

[0117] S145: Determine the inclination of the target board based on the identification of the thickness of the target board point cloud and the inclination identification model.

[0118] In the embodiments of the present application, locate the target board and the settlement observation rod based on the monitoring area, and collect point cloud data for the monitoring area; determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data; determine the thickness of the target board point cloud based on the detection of the target board point cloud; determine the inclination of the target board based on the identification of the thickness of the target board point cloud. The target board point cloud and the settlement observation rod point cloud are introduced, and the target board point cloud and the settlement observation rod point cloud are controlled to ensure the accuracy of the thickness of the target board point cloud.

[0119] At this time, the thickness of the target board point cloud is fixed, the thickness of the target board point cloud is introduced, and the thickness of the target board point cloud is further controlled, so as to compare the thickness of the target board point cloud with a preset thickness threshold, determine whether it is within the threshold range, and judge whether the thickness of the target board meets the expected specifications or requirements according to the comparison result.

[0120] Therefore, the recognition of the thickness of the target board point cloud is triggered based on the comparison between the thickness of the target board point cloud and the preset thickness threshold; the thickness of the target board point cloud is associated with the inclination recognition model; the inclination of the target board is determined according to the recognition of the thickness of the target board point cloud and the inclination recognition model, realizing the recognition of the thickness of the target board point cloud and the inclination recognition model, and ensuring the accuracy of the inclination of the target board. At the same time, the target board point cloud and the settlement observation rod point cloud are introduced, and the target board point cloud and the settlement observation rod point cloud are controlled to ensure the accuracy of the thickness of the target board point cloud.

[0121] At this time, if the thickness of the target board point cloud falls within the preset threshold range, it is considered that its thickness is compliant, thus triggering the formal recognition of the thickness of the target board point cloud. In addition, the thickness information of the target board point cloud is associated with an inclination recognition model. The inclination recognition model is usually a model trained based on machine learning or deep learning, which can extract features from the point cloud data and predict the inclination of the target board. In this step, we use the thickness of the target board point cloud as one of the input features and input it into the model together with other relevant features (such as the geometric shape and distribution of the point cloud). The model makes predictions based on these features and outputs the inclination of the target board.

[0122] Reference Figure 6 , S15: Collect the perpendicularity model of the target board and the settlement observation rod;

[0123] In the specific implementation process of the present invention, the specific steps can be:

[0124] S151: Fix the settlement observation rod;

[0125] S152: Determine the perpendicularity model of the settlement observation rod based on the matching of the settlement observation rod;

[0126] S153: Collect the target board;

[0127] S154: Associate the perpendicularity model of the target board and the settlement observation rod.

[0128] In the embodiment of the present application, the settlement observation rod is fixed, the settlement observation rod is introduced, and the settlement observation rod is controlled. At the same time, the perpendicularity model of the settlement observation rod is determined based on the matching of the settlement observation rod, realizing the matching of the settlement observation rod and ensuring the accuracy of the perpendicularity model of the settlement observation rod.

[0129] At this time, by regularly observing the settlement observation rod, settlement data is collected. These data include the elevation change and settlement amount of the observation points, etc. The collected settlement data is processed and analyzed to calculate indicators such as the settlement amount and settlement rate of each observation point. At the same time, according to the change trend of the settlement data, it is judged whether the settlement of the building is stable. Based on the matching of the settlement observation rod (i.e., the relative position relationship between each observation point), combined with the change law of the settlement data, a perpendicularity model of the settlement observation rod is established. This model can reflect the change of the perpendicularity of the building during the settlement process.

[0130] Therefore, the target board is collected; the perpendicularity model of the target board and the settlement observation rod is associated, and the perpendicularity model of the target board and the settlement observation rod is controlled, so as to achieve the overall control of the perpendicularity model of the target board and the settlement observation rod.

[0131] Reference Figure 7 , S16: Determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board, the settlement observation rod, and the inclination of the target board;

[0132] In the specific implementation process of the present invention, the specific steps can be:

[0133] S161: Fix the inclination of the target board;

[0134] S162: Collect the perpendicularity models of the target board and the settlement observation rod;

[0135] S163: Associate the perpendicularity models of the target board, the settlement observation rod, and the inclination of the target board;

[0136] S164: Determine the first parameter based on the perpendicularity models of the target board and the settlement observation rod;

[0137] S165: Determine the second parameter based on the target board and the inclination of the target board;

[0138] S166: Determine the perpendicularity of the settlement observation rod according to the first parameter, the second parameter, and the settlement observation rod.

[0139] In the specific implementation process of the present invention, the perpendicularity models of the target board and the settlement observation rod are collected; the perpendicularity of the settlement observation rod is determined based on the perpendicularity models of the target board, the settlement observation rod, and the inclination of the target board, which takes into account the overall consideration of the target board, the perpendicularity models of the settlement observation rod, and the inclination of the target board, realizes the multi-dimensional control of the target board, the perpendicularity models of the settlement observation rod, and the inclination of the target board, and ensures the accuracy of the perpendicularity of the settlement observation rod.

[0140] At this time, freeze the inclination of the target board; collect the perpendicularity models of the target board and the settlement observation rod; correlate the perpendicularity models of the target board and the settlement observation rod and the inclination of the target board, and perform multiple interactions on the perpendicularity models of the target board and the settlement observation rod and the inclination of the target board.

[0141] Therefore, determine the first parameter based on the perpendicularity models of the target board and the settlement observation rod; determine the second parameter based on the target board and the inclination of the target board; determine the perpendicularity of the settlement observation rod according to the first parameter, the second parameter and the settlement observation rod, which is compatible with the first parameter, the second parameter and the settlement observation rod, and controls the first parameter, the second parameter and the settlement observation rod, ensuring the accuracy of the perpendicularity of the settlement observation rod. At the same time, it is compatible with the overall consideration of the perpendicularity models of the target board and the settlement observation rod and the inclination of the target board, realizing the multi-dimensional control of the perpendicularity models of the target board and the settlement observation rod and the inclination of the target board, and ensuring the accuracy of the perpendicularity of the settlement observation rod.

[0142] At this time, use the previously established perpendicularity models of the target board and the settlement observation rod to determine the first parameter directly related to settlement observation. The first parameter is usually used to quantify the spatial position, direction or shape characteristics of the settlement observation rod, which are crucial for subsequent analysis and understanding of the settlement behavior of the building. Optionally, carefully analyze the perpendicularity models of the target board and the settlement observation rod to ensure the accuracy and integrity of the perpendicularity model of the settlement observation rod. This includes checking information such as coordinate data, geometric shape and position relationship in the perpendicularity model of the settlement observation rod, and extracting parameters directly related to settlement observation from the perpendicularity model of the settlement observation rod. These parameters may include the height of the settlement observation rod, the vertical deviation (the offset relative to the ideal vertical line), the inclination angle (if the settlement observation rod is not completely vertical), etc. The selection of these parameters depends on specific settlement observation requirements and objectives.

[0143] Specifically, perpendicularity models of the target board and the settlement observation rod are established. By analyzing the models, we extract the height (H) and vertical deviation (ΔV) of the settlement observation rod as the first parameters. Specifically, the height H of the settlement observation rod is 30 meters, and the vertical deviation ΔV is 5 millimeters (the offset relative to the ideal vertical line).

[0144] At this time, the inclination of the target board is used to determine the second parameters that are indirectly related to the settlement observation. These parameters are usually used to reflect the inclination state or deformation of the target board (and possibly the building structure connected thereto), and they help us to more comprehensively understand the settlement behavior of the building; Optionally, a detailed analysis of the inclination of the target board is carried out to determine key information such as the direction, angle and rate of inclination. Based on the results of the inclination analysis, parameters indirectly related to the settlement observation are defined. These parameters may include the inclination angle (θ), the inclination direction (such as how many degrees east of north), the inclination rate (i.e., the rate of change of the inclination angle with time), etc. The selection of these parameters depends on the specific settlement observation requirements and objectives, and the defined parameters are evaluated to determine whether they accurately reflect the inclination state or deformation of the target board.

[0145] Specifically, by analyzing the inclination of the target board, the inclination angle (θ) and the inclination rate are determined as the second parameters. Specifically, the inclination angle θ of the target board is 0.3 degrees (in the direction of east of north), and the inclination rate increases by 0.01 degrees per year. These parameters indicate that there may be a certain inclination and deformation of the building.

[0146] Furthermore, the first parameters (parameters directly related to the settlement observation rod), the second parameters (parameters related to the inclination of the target board), and the information of the settlement observation rod itself are comprehensively used to determine the verticality of the settlement observation rod. Optionally, the first parameters and the second parameters are integrated to form a complete set of parameters. These parameter sets include information such as the height, vertical deviation, inclination angle, inclination direction, inclination rate of the settlement observation rod, etc.; Based on the integrated parameter set and the information of the settlement observation rod itself (such as material, size, installation location, etc.), an appropriate mathematical model or algorithm is used to calculate the verticality of the settlement observation rod. This may need to consider the influence of various factors, such as temperature, wind force, foundation settlement, etc. Finally, the calculated verticality of the settlement observation rod is verified and interpreted. This can be achieved by comparing with the on-site measured data and analyzing the change trend of the verticality over time. At the same time, it is also necessary to interpret the meaning and influence of the verticality in combination with the specific situation of the building and the objectives of the settlement observation.

[0147] Specifically, the height of the settlement observation rod (H = 30 m), the vertical deviation (ΔV = 5 mm), the inclination angle of the target board (θ = 0.3 degrees) and other parameters are comprehensively used to calculate the verticality of the settlement observation rod. Through appropriate mathematical models and algorithms, it is calculated that the verticality of the settlement observation rod has a slight deviation, but it is still within the acceptable range. Considering the specific situation of the building and the objectives of the settlement observation, this result indicates that the building maintains a relatively stable state during the settlement process.

[0148] Optionally, a specific embodiment of the method for detecting the verticality of the settlement observation rod:

[0149] S1. Embedding and modification of settlement observation board: In the monitoring area, first horizontally embed the settlement observation board inside the soil body to ensure its stability and that its position meets the monitoring requirements. If the settlement observation board has been embedded, it can be directly modified. Above the embedded settlement observation rod, screw in a square or circular target board made of stainless steel by threading. Part of the settlement observation rod is inserted into the soil body and part extends out of the ground surface, and the exposed part is used to support the target board. The target board should theoretically be placed horizontally and be perpendicularly connected to the settlement observation rod. As the key recognition point for drones or laser scanners, through point cloud data collection and processing, using the point cloud thickness of the target board, the horizontal angle change is deduced, and then the verticality of the settlement observation rod is deduced, so as to judge the operation status of the settlement observation system.

[0150] S2. Point cloud data collection: Use point cloud collection devices such as drones or laser scanners to perform high-precision scanning on the area of the modified settlement observation rod, focusing on collecting the point cloud data near the target board to ensure that the key parts of the settlement observation rod are fully covered and the accuracy meets the monitoring requirements.

[0151] S3. Point cloud denoising and classification: Perform denoising processing on the collected point cloud data to remove the interfering point clouds in the environment. Then, use classification algorithms such as K-Means to classify the point cloud, accurately separating the point cloud of the target board and the point cloud of the settlement observation rod to ensure the accuracy of subsequent calculations.

[0152] S4. Calculation of the point cloud thickness of the target board: According to the classification results, extract the point cloud data of the target board and calculate the thickness of the target board through the distribution of the point cloud, providing basic data for the subsequent calculation of the inclination of the target board. The target board is a thin plate. In an ideal situation, its point cloud thickness is close to zero, indicating that the target board is horizontally placed. If the point cloud thickness is large, it means that the target board is tilted.

[0153] S5. Calculation of the inclination of the target board: The inclined plane of the target board forms a triangle with the horizontal plane and the vertical plane. In this triangle, using the point cloud thickness, there are trigonometric functions:

[0154] (1)

[0155] where L is the known side length of the target board, h is the point cloud thickness of the target board obtained in S4, α is the inclination angle of the target board.

[0156] Calculate the inclination angle of the target board using the arcsine function:

[0157] (2)

[0158] S6. Calculation of the verticality of the settlement observation rod: Combining the inclination of the target plate obtained in S5, the verticality of the settlement observation rod is deduced using mathematical principles such as the perpendicular relationship between the target plate and the settlement observation rod. β :

[0159] (3)

[0160] Ideally, the settlement observation rod should be vertically inserted into the soil, and its verticality should be close to 90°. If the calculated verticality β is less than a certain set threshold (e.g., 80°), it indicates that the deviation of the settlement observation rod is relatively serious.

[0161] The beneficial effects of the present invention are as follows:

[0162] 1. Precision improvement: By modifying the traditional settlement observation device, adding a target plate and using point cloud data for detection, the monitoring precision of the verticality of the settlement observation rod can be significantly improved. The combination of the point cloud thickness analysis of the target plate and the deduction of the verticality of the settlement observation rod realizes a more refined assessment of the inclination of the settlement observation rod.

[0163] 2. High degree of automation: The present invention uses devices such as drones or laser scanners to collect point cloud data, and combines data processing algorithms to achieve automatic analysis, avoiding the limitations of traditional manual measurement methods. By introducing classification algorithms such as K-Means, the point cloud data of the target plate and the support rod can be automatically distinguished, improving the efficiency and accuracy of data processing.

[0164] 3. Strong real-time monitoring ability: The present invention uses technical means such as drones to perform large-scale and rapid point cloud scanning, and can obtain the inclination of the settlement observation rod in real time or regularly, ensuring the timeliness of engineering monitoring. Compared with traditional manual measurement, the present invention can more efficiently discover potential settlement deviation problems and take corrective measures in time.

[0165] 4. Adapt to complex geological environments: Traditional settlement monitoring methods are difficult to maintain stable precision under complex geological conditions, while the present invention uses the high spatial resolution of point cloud data and the flexibility of drones to obtain accurate observation results in complex terrains. This makes the technology have better adaptability and application prospects in special geological environments such as soft soil and reclamation areas.

[0166] 5. Reduce human errors: The present invention reduces the errors caused by human operations through automatic data processing. Traditional manual elevation measurement is easily affected by the external environment and the experience of operators, while the present invention significantly reduces the influence of human factors on the results through precise geometric calculations and trigonometric deductions.

[0167] In actual monitoring, if the verticality is found βIf the deviation is too large, manual adjustment or repair measures need to be taken to ensure the stability of the observation rod and the reliability of the data.

[0168] In the embodiment of the present invention, through the method in the embodiment of the present invention, the positioning target board and the settlement observation rod in the monitoring area are based on, and the point cloud data of the monitoring area is collected; the target board point cloud and the settlement observation rod point cloud are determined based on the screening of the point cloud data; the thickness of the target board point cloud is determined according to the detection of the target board point cloud; the inclination of the target board is determined based on the recognition of the thickness of the target board point cloud. The target board point cloud and the settlement observation rod point cloud are introduced, and the target board point cloud and the settlement observation rod point cloud are controlled to ensure the accuracy of the thickness of the target board point cloud.

[0169] Further, the perpendicularity model of the target board and the settlement observation rod is collected; the perpendicularity of the settlement observation rod is determined based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, which is compatible with the overall consideration of the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, realizes the multi-dimensional control of the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board, and ensures the accuracy of the perpendicularity of the settlement observation rod.

[0170] Please refer to Figure 8 , Figure 8 which is a schematic structural composition diagram of the perpendicularity detection system of the settlement observation rod in the embodiment of the present invention.

[0171] As Figure 8 shown, a perpendicularity detection system for a settlement observation rod, the perpendicularity detection system for the settlement observation rod includes:

[0172] The first acquisition module 21 is used to collect point cloud data of the monitoring area based on the positioning target board and the settlement observation rod in the monitoring area;

[0173] The screening module 22 is used to determine the target board point cloud and the settlement observation rod point cloud based on the screening of the point cloud data;

[0174] The thickness module 23 is used to determine the thickness of the target board point cloud according to the detection of the target board point cloud;

[0175] The inclination module 24 is used to determine the inclination of the target board based on the recognition of the thickness of the target board point cloud;

[0176] The second acquisition module 25 is used to collect the perpendicularity model of the target board and the settlement observation rod;

[0177] The perpendicularity module 26 is used to determine the perpendicularity of the settlement observation rod based on the perpendicularity model of the target board and the settlement observation rod and the inclination of the target board.

[0178] Please refer to Figure 9 , the following is with reference toFigure 9 Describe the electronic device 40 according to this embodiment of the present invention. Figure 9 The displayed electronic device 40 is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0179] As Figure 9 shown, the electronic device 40 is presented in the form of a general-purpose computing device. The components of the electronic device 40 may include, but are not limited to: at least one of the above-mentioned processing units 41, at least one of the above-mentioned storage units 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0180] Among them, the storage unit stores program codes, and the program codes can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the "Embodiment Method" section of this specification.

[0181] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 421 and / or a cache storage unit 422, and may further include a read-only storage unit (ROM) 423.

[0182] The storage unit 42 may further include a program / utility 424 having a set (at least one) of program modules 425. Such program modules 425 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include the implementation of a network environment.

[0183] The bus 43 may represent one or more of several types of bus structures, including a storage unit bus or a storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any bus structure in a variety of bus structures.

[0184] The electronic device 40 may also communicate with one or more external devices (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 40, and / or communicate with any device that enables the electronic device 40 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be carried out through an input / output (I / O) interface 44. And, the electronic device 40 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 45. As Figure 9 shown, the network adapter 45 communicates with other modules of the electronic device 40 through the bus 43. It should be understood that although Figure 9Not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems, etc.

[0185] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0186] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. The storage medium can include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), a magnetic disk or an optical disc, etc. And it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the method according to the above.

[0187] In addition, the above has introduced in detail the verticality detection method and system of the settlement observation rod provided by the embodiments of the present invention. Specific examples are used herein to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation on the present invention.

Claims

1. A method for detecting the verticality of a settlement observation rod, characterized in that: Applicable to the verticality detection scenario of settlement observation rod; The verticality detection method of the settlement observation rod comprises: Position the target plate and the settlement observation rod based on the monitoring area, and collect point cloud data for the monitoring area; Determine the target plate point cloud and the settlement observation rod point cloud based on the screening of the point cloud data; Determining the thickness of the target plate point cloud according to the detection of the target plate point cloud; Determine the inclination of the target plate based on the recognition of the thickness of the target plate point cloud: input the target plate point cloud thickness and other features including point cloud geometry and distribution into the inclination recognition model to output the inclination of the target plate; the inclination recognition model is a model based on machine learning or deep learning training; Collect the verticality model of the target plate and the settlement observation rod: collect settlement data by regularly observing the settlement observation rod, process and analyze the settlement data, calculate the indicators of each observation point including settlement amount and settlement rate, and establish the verticality model of the settlement observation rod based on the matching of the settlement observation rod and the change law of settlement data; the settlement data includes the elevation change of the observation point and the settlement amount; The verticality of the settlement observation rod is determined based on the target plate, the verticality model of the settlement observation rod and the inclination of the target plate: the first parameter is determined based on the verticality model of the target plate and the settlement observation rod; the second parameter is determined based on the target plate and the inclination of the target plate; the verticality of the settlement observation rod is determined according to the first parameter, the second parameter and the settlement observation rod; the first parameter includes the height, vertical deviation and inclination angle of the settlement observation rod; the second parameter includes the inclination angle, inclination direction and inclination rate.

2. The verticality detection method of the settlement observation rod according to claim 1 is characterized in that: The method of positioning the target plate and the settlement observation rod based on the monitoring area and collecting point cloud data of the monitoring area includes: Locate monitoring area; Positioning target plates and settlement observation rods based on the monitoring area; Scan the monitoring area; Point cloud data is collected based on scanning of the monitoring area.

3. The verticality detection method of the settlement observation rod according to claim 1 is characterized in that: The method of determining the target plate point cloud and the settlement observation rod point cloud based on the screening of the point cloud data includes: Freeze point cloud data; De-noising and filtering the point cloud data; Collecting multiple point cloud areas according to the screening of point cloud data; The target plate point cloud and the settlement observation rod point cloud are determined based on the recognition of multiple point cloud areas.

4. The verticality detection method of the settlement observation rod according to claim 3 is characterized in that: The step of determining the thickness of the target plate point cloud according to the detection of the target plate point cloud comprises: Freeze the target plate point cloud; Associate the target plate point cloud and the corresponding detection model; Determine the distribution of the target plate point cloud based on the target plate point cloud and the corresponding detection model; The thickness of the target plate point cloud is determined according to the distribution of the target plate point cloud.

5. A verticality detection system for a settlement observation rod, characterized in that: The verticality detection system of the settlement observation rod is applied to the verticality detection method of the settlement observation rod as claimed in any one of claims 1 to 4, and the verticality detection system of the settlement observation rod comprises: The first acquisition module is used to locate the target plate and the settlement observation rod based on the monitoring area, and to collect point cloud data for the monitoring area; A screening module, used to determine the target plate point cloud and the settlement observation rod point cloud based on the screening of the point cloud data; A thickness module, used to determine the thickness of the target plate point cloud according to the detection of the target plate point cloud; The inclination module is used to determine the inclination of the target plate based on the recognition of the thickness of the target plate point cloud: the target plate point cloud thickness and other features including the point cloud geometry and distribution are input into the inclination recognition model to output the inclination of the target plate; the inclination recognition model is a model based on machine learning or deep learning training; The second acquisition module is used to collect the verticality model of the target plate and the settlement observation rod: by regularly observing the settlement observation rod, collecting settlement data, processing and analyzing the settlement data, calculating the indicators of each observation point including settlement amount and settlement rate, and establishing the verticality model of the settlement observation rod based on the matching of the settlement observation rod and the change law of settlement data; the settlement data includes the elevation change of the observation point and the settlement amount; The verticality module is used to determine the verticality of the settlement observation rod based on the target plate, the verticality model of the settlement observation rod, and the inclination of the target plate: determine the first parameter based on the verticality model of the target plate and the settlement observation rod; determine the second parameter based on the target plate and the inclination of the target plate; determine the verticality of the settlement observation rod according to the first parameter, the second parameter and the settlement observation rod; the first parameter includes the height, vertical deviation, and inclination angle of the settlement observation rod; the second parameter includes the inclination angle, inclination direction, and inclination rate.

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