Tunnel section convergence accurate measurement method, system and device and storage medium

Abstract

The invention discloses a tunnel section convergence accurate measurement method, system and device and a storage medium. The method comprises the following steps: receiving input basic information; establishing a tunnel section laser scanning image acquisition model; collecting elevation data of a tunnel section; performing multi-source heterogeneous data fusion based on the input basic information, the collected tunnel section laser scanning image, the point cloud data and the tunnel section elevation data to obtain a fused data result; tunnel section extraction; according to the extracted section result, constructing an independent plane coordinate of the tunnel section after converting the section result, fitting a difference value between a tunnel radius result and a design result, and measuring convergence deformation of the tunnel section; outputting a tunnel section convergence deformation measurement result; according to the invention, multi-source data fusion, data visualization, deformation analysis and risk prediction can be realized, the tunnel measurement precision, the engineering quality and the engineering management efficiency are obviously improved, and the tunnel construction safety is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering, and in particular to a method, system, equipment and storage medium for accurately measuring the convergence of a tunnel section. Background Art

[0002] Statistics show that by the end of 2023, the operating mileage of railway tunnels in my country will be 23,508 km, and the operating mileage of highway tunnels will be 26,784 km.

[0003] In view of the difficulty of tunnel construction and the many risk factors, traditional tunnel monitoring and risk warning methods can no longer meet the current needs of comprehensive management and comprehensive analysis. Therefore, it is necessary to comprehensively monitor and control the safety status of the tunnel structure, realize the automatic detection of the tunnel section, grasp the deformation of the tunnel section, and measure its convergence deformation. Tunnel convergence deformation is the deformation formed by uneven external forces during tunnel construction, which will cause changes in the spatial morphology of the tunnel and cause significant deviations from the design results; convergence deformation is extremely harmful to the tunnel, causing cracks, water seepage, and falling off in the tunnel, posing a major safety hazard to the tunnel structure and normal use.

[0004] In a tunnel construction environment with poor working conditions such as darkness, confinement and humidity, the use of traditional tunnel measurement and monitoring methods such as inverted rulers, convergence meters, and total stations for tunnel construction measurement has disadvantages such as long working time, high cost, poor environmental adaptability, low efficiency, and low accuracy. Traditional single-point monitoring cannot meet the overall deformation monitoring of tunnel projects (especially tunnels with poor geological conditions such as soft rocks and deep soft soils), and cannot meet the requirements of current tunnel engineering construction. In addition, traditional safety risk monitoring methods can no longer meet the current needs of comprehensive management and comprehensive analysis.

[0005] In order to ensure the safe passage and stable operation of traffic in tunnels, the quality of tunnel construction is particularly important. During the construction process, the span of the tunnel is long and it is all constructed underground. The geological environment is very complex. Therefore, it is necessary to comprehensively monitor and control the safety status of the tunnel structure, realize the automatic detection of the subway tunnel section, understand the section distribution, and measure its convergence and deformation. Tunnel section convergence measurement is to measure the dimensions of the tunnel's spatial position, and describe the convergence and deformation of the tunnel section through the changes in the position dimensions. However, when measured with traditional instruments, there is a certain error in its measurement accuracy. Summary of the invention

[0006] The purpose of the present invention is to provide a method, system, equipment and storage medium for accurate measurement of tunnel section convergence, which can realize multi-source data fusion, data visualization, deformation analysis and risk prediction, significantly improve tunnel measurement accuracy, project quality and project management efficiency, and ensure tunnel construction safety.

[0007] To achieve this object, the present invention adopts the following technical solutions: A method for accurately measuring tunnel section convergence is provided, comprising the following steps: Receiving input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, and tunnel section information; Collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; Based on the total station, the coordinates of the measuring points on the inner wall of the tunnel are collected, the information in the coordinates is extracted, and a cross-section drawing is generated to complete the tunnel cross-section elevation data collection; Based on the input basic information and the collected tunnel section data, multi-source heterogeneous data fusion is performed to obtain the fused data results; The tunnel structure centerline method is used to batch slice and process the fused data to quickly extract the subway tunnel section and complete the tunnel section extraction; Based on the extracted cross-section results, the independent plane coordinates of the tunnel cross-section are constructed after transformation, and the difference between the tunnel radius result and the design result is fitted to measure the convergence deformation of the tunnel cross-section; Output the tunnel section convergence deformation measurement results.

[0008] As a preferred solution of the tunnel section convergence accurate measurement method, the step of collecting tunnel section laser scanning images and point cloud data and establishing a tunnel section laser scanning image acquisition model includes: Project the laser rangefinder into the tunnel to obtain the edge contour threshold of the laser scanning image of the subway tunnel section , and its calculation formula is: Where: Represents the grayscale value of the image; Represents the standard deviation of all pixels in the image; The laser vision tracking and recognition method is used to obtain the edge pixel distribution pixel value of the subway belt section laser scanning image, and the calculation formula is: Where: Indicates the laser scanning distance; Indicates the segmentation accuracy; Combining the gradient pixel decomposition and fuzzy identification methods, the texture of the cross-section layer is analyzed to build a visual enhancement model for the laser scanning image of the subway tunnel section. The calculation formula is: Where: represents the correction factor; The frequency domain filtering analysis is used to obtain the cross-section layer topological structure distribution matrix, and its formula is: Where: and Both represent topological distribution vectors, the former corresponds to the X-coordinate direction, and the latter corresponds to the Y-coordinate direction; According to the output results of the three-dimensional laser scanning of the tunnel section, a tunnel section laser scanning image acquisition model is constructed. The acquisition is completed using the spatial complex surface reconstruction method, and its calculation formula is: .

[0009] As a preferred solution for the tunnel section convergence precision measurement method, the steps of collecting the coordinates of the tunnel inner wall measuring points based on the total station, extracting the information in the coordinates, generating a section drawing, and completing the tunnel section elevation data collection include: Set the section acquisition sequence and perform acquisition in sequence; Determine whether the measurement of all sections has been completed; If not, return to the step of “setting the section acquisition sequence and performing acquisition in sequence”; If so, cross-sectional measurement data is generated; Read the elevation data of the measuring point; Generate cross-sectional drawings; Output the collection results.

[0010] As a preferred solution for accurate measurement of tunnel section convergence, a federated learning algorithm is used to fuse multi-source heterogeneous data.

[0011] As a preferred solution for the tunnel section convergence accurate measurement method, the step of batch slicing and processing the fused data using the tunnel structure centerline method to quickly extract the subway tunnel section and complete the tunnel section extraction includes: With the center of the tunnel structure, the cross section where the slice is located is perpendicular to the center line of the tunnel structure, and the tunnel section is extracted; Represents a coordinate point, which is located on the extracted midline, and the tangent vector through this point is Indicates that it is calculated; based on the above two calculation results, the calculation is completed Cross section of a point As a result, the formula is: According to the above formula, the fused data is segmented to form slices with a certain thickness. The distance between any points in the slice is calculated according to the formula. The calculation formula is: The thickness of the slice is Indicates that when , the cross-section point that meets the conditions is , the geometric formula for the corresponding cross-section point is: .

[0012] As a preferred solution of the tunnel section convergence accurate measurement method, the steps of constructing independent plane coordinates of the tunnel section after converting the extracted section results and fitting the difference between the tunnel radius result and the design result to accurately measure the tunnel section convergence deformation include: The converted coordinate points are The expression formula of the circle is: Where: represents the coordinates of the center of the circle; Indicates the radius of a circle; Measuring point The error calculation formula is: Where: Indicate point and the distance from the circumference, the formula can be converted to: Where: , ; Among them, the initial value of the center coordinate is expressed by the average coordinate value of all measured points, and the initial value of the radius is the design result. According to the above formula, the center coordinate result of the tunnel plane is obtained, and the distance result between the measured point and the center of the circle is calculated clockwise from the upper center position. The result is compared with the design result to obtain the difference between the two and measure the cross-section convergence deformation.

[0013] The present invention also provides a tunnel section convergence precision measurement system, comprising: An input module, used to receive input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, tunnel section information; Tunnel section sampling module, used to collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; The tunnel section data acquisition module is used to collect the coordinates of the tunnel inner wall measurement points based on the total station, extract the information in the coordinates, generate a section drawing, and complete the tunnel section elevation data acquisition; The tunnel section multi-source data fusion module is used to fuse multi-source heterogeneous data based on the input basic information and the collected tunnel section data to obtain the fused data results; The tunnel section extraction module is used to batch slice and process the fused data using the tunnel structure centerline method, quickly extract the subway tunnel section, and complete the tunnel section extraction; The tunnel section convergence measurement module is used to transform the extracted section results to construct independent plane coordinates of the tunnel section, fit the difference between the tunnel radius result and the design result, and measure the convergence deformation of the tunnel section; The output module is used to output the tunnel section convergence deformation measurement results.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of any of the above-mentioned methods for accurately measuring tunnel section convergence when executing the computer program. The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the tunnel section convergence accurate measurement method as described in any one of the above items are implemented.

[0015] Beneficial effects of the invention: The invention proposes a method, system, equipment and storage medium for accurate measurement of tunnel section convergence, which can realize multi-source data fusion, data visualization, deformation analysis and risk prediction, significantly improve tunnel measurement accuracy, engineering quality and engineering management efficiency, and ensure tunnel construction safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 This is a flow chart of a tunnel section convergence precision measurement method according to an embodiment of the present invention; Figure 2 It is a schematic block diagram of the structure of a tunnel section convergence precision measurement system according to an embodiment of the present invention; Figure 3 A schematic block diagram of the structure of a computer device according to an embodiment of the present invention; The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0019] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0020] Reference Figure 1 An embodiment of the present invention provides a method for accurately measuring tunnel cross-section convergence, which includes the following steps: S1: receiving input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, tunnel section information; S2: Collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; S3: Based on the total station, the coordinates of the measuring points on the inner wall of the tunnel are collected, the information in the coordinates is extracted, and a cross-section drawing is generated to complete the collection of tunnel cross-section elevation data; S4: Based on the input basic information, the collected tunnel section laser scanning image, point cloud data and tunnel section elevation data, multi-source heterogeneous data fusion is performed to obtain the fused data results; S5: using the tunnel structure centerline method to batch slice and process the fused data, quickly extract the subway tunnel section, and complete the tunnel section extraction; S6: Based on the extracted cross-section results, the cross-section is converted to construct independent plane coordinates of the tunnel cross-section, and the difference between the tunnel radius result and the design result is fitted to measure the convergence deformation of the tunnel cross-section; S7: Output the tunnel section convergence deformation measurement results.

[0021] As described in the above step S1, through the input module, the surveyor inputs basic information such as tunnel monitoring measurement, tunnel engineering information, and tunnel section information, and transmits it to the tunnel section multi-source data fusion module; As described in the above step S2, through the tunnel section sampling module of the three-dimensional laser scanner, the tunnel section laser scanning image, point cloud data and other information are obtained, and a tunnel section laser scanning image acquisition model is established, and transmitted to the tunnel section multi-source data fusion module; The laser rangefinder is projected into the tunnel, and the calculation formula for obtaining the edge contour threshold of the laser scanning image of the subway tunnel section is: Where: Represents the grayscale value of the image; Represents the standard deviation of all pixels in the image.

[0022] The laser vision tracking and recognition method is used to obtain the edge pixel distribution pixel value of the subway belt section laser scanning image, and the calculation formula is: Where: Indicates the laser scanning distance; Indicates the segmentation accuracy.

[0023] Combining the gradient pixel decomposition and fuzzy identification methods, the texture of the cross-section layer is analyzed to build a visual enhancement model for the laser scanning image of the subway tunnel section. The calculation formula is: Where: Indicates the correction factor.

[0024] Obtaining the cross-section topological structure distribution matrix using frequency domain filtering analysis , the formula is: Where: and Both represent topological distribution vectors, the former corresponds to the X-coordinate direction, and the latter corresponds to the Y-coordinate direction.

[0025] According to the output results of the three-dimensional laser scanning of the tunnel section, a tunnel section laser scanning image acquisition model is constructed. The acquisition is completed using the spatial complex surface reconstruction method, and its calculation formula is: The above steps complete the tunnel section data collection and provide support for section convergence measurement.

[0026] As described in step S3 above, the coordinates of the measuring points on the inner wall of the tunnel are obtained through the tunnel section data acquisition module of the total station, and the information in the coordinates is extracted to generate a section drawing, complete the tunnel section elevation data acquisition, and transmit it to the tunnel section multi-source data fusion module; specifically, the following steps are included: Set the section acquisition sequence and perform acquisition in sequence; Determine whether the measurement of all sections has been completed; If not, return to the step of “setting the section acquisition sequence and performing acquisition in sequence”; If so, cross-sectional measurement data is generated; Read the elevation data of the measuring point; Generate cross-sectional drawings; Output the collection results.

[0027] As described in the above step S4, the data collected by each module is fused into multi-source heterogeneous data through the tunnel section multi-source data fusion module to obtain the fused data result, and the result is transmitted to the tunnel section extraction module; The federated learning algorithm is used to complete the fusion of the collected tunnel data. The algorithm contains three modules: feature extraction module, fusion module and feature decision module. During the initialization process of the algorithm, the central node can complete the random initialization of the parameters of the three modules and transmit them to the edge nodes. The edge nodes determine the corresponding feature extraction subnetwork according to the data set structure or category on the node, and complete the training of the three modules according to the local data set. After the training is completed, the value is returned to the central control node to realize the fusion of multi-source heterogeneous data of the tunnel section.

[0028] If the edge node uses It indicates that, Indicates the quantity, the input multi-source heterogeneous tunnel section data category is Indicates that the three modules of the algorithm are used in turn , and Indicates that its data fusion formula is: Where: Represents a concatenation operation.

[0029] The collected multi-source data to be fused is used and Indicates that two types of data are processed through two different nodes, that is, through and The two sub-networks extract features of the two types of data and train them to obtain feature graph results of the two types of data. and Indicates; Combined with the heterogeneous data categories and quantities in the nodes, the feature fusion is completed in two stages. The first stage is based on the first-order unit. and Perform modular multiplication to obtain a new Results, which include The second stage is based on the second-order unit, and the first unit obtains Results and Perform modular multiplication to obtain and The fusion tensor of the two features is The relevant calculation formula is: By completing the multi-source data fusion processing in this way, the spatial dimension feature learning of each multi-source data can be fully completed, and the correlation between the data can be deeply obtained.

[0030] node The training expression formula on is: Where: Node In the Data fusion results after iterations; represents the learning rate; Represents the gradient.

[0031] In the fusion process, each edge node uses the adaptive selection mechanism of the feature extractor to complete the training of the feature extraction module. In this process, each feature extraction sub-network needs to be processed by merging, and the data fusion model is obtained on this basis. It is mainly completed by the average aggregation algorithm. The obtained model contains many multi-source data features. The relevant calculation formula is: Where: represents the updated feature extraction module; and Both represent sample data, the former is located at the edge node The latter is all samples.

[0032] Based on the above formula, we can obtain The global data fusion model results at the iteration , and its calculation formula is: Where: , Both represent the number of samples, the former is located at the edge node The latter is all samples.

[0033] As described in step S5 above, through the tunnel section extraction module, the fused data is batch sliced ​​and processed using the tunnel structure centerline method to quickly extract the subway tunnel section, complete the tunnel section extraction, and transmit it to the tunnel section convergence precision measurement module; The tunnel structure centerline is used to complete the process. During the processing, the cross section where the slice is located is perpendicular to the tunnel structure centerline, so that the subway tunnel section extraction can be completed quickly. Represents a coordinate point, which is located on the extracted midline, and the tangent vector through this point is Indicates that it is calculated; based on the above two calculation results, the calculation is completed Cross section of a point As a result, the formula is: According to the above formula, the fused data is segmented to form slices with a certain thickness. According to this formula, any point in the slice can be calculated. and The distance between , and its calculation formula is: If the slice thickness is Indicates that when , the cross-section point that meets the conditions is , the geometric formula for the corresponding cross-section point is: .

[0034] As described in step S6 above, through the tunnel section convergence measurement module, according to the extracted section results, the extracted section results are converted to construct independent plane coordinates of the tunnel section, and the difference between the tunnel radius result and the design result is fitted to achieve accurate measurement of tunnel section convergence deformation; If the coordinate point after the rotation is The expression formula of the circle is: Where: represents the coordinates of the center of the circle; Indicates the radius of the circle.

[0035] Measuring point The error calculation formula is: Where: Can indicate point and the distance from the circumference, then formula (15) can be converted into: Where: , .

[0036] The initial value of the center coordinate is expressed by the average coordinate value of all measured points, and the initial value of the radius is the design result. According to the above formula, the coordinate result of the center of the tunnel plane is obtained, and the distance between the measured point and the center of the circle is calculated clockwise from the upper center position. The result is compared with the design result to obtain the difference between the two, and the cross-section convergence deformation is accurately measured.

[0037] As described in step S7 above, the output module outputs the results, displays the tunnel section convergence deformation measurement results on a unified platform, and determines whether the tunnel meets the engineering design standards. In this embodiment, a three-dimensional laser scanner and a total station are used to collect point cloud data and elevation data of the tunnel section, a federated learning algorithm is used to fuse the collected multi-source data, and the difference between the tunnel radius result and the design result is fitted to obtain the cross-section convergence deformation; it is able to complete centralized processing of data in different formats and from different data sources, obtain valid data from the data, improve the tunnel measurement accuracy and engineering quality, and can be used for tunnel construction information monitoring and tunnel operation and maintenance monitoring.

[0038] Reference Figure 2 An embodiment of the present invention further provides a tunnel section convergence precision measurement system, comprising: An input module, used to receive input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, tunnel section information; Tunnel section sampling module, used to collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; The tunnel section data acquisition module is used to collect the coordinates of the tunnel inner wall measurement points based on the total station, extract the information in the coordinates, generate a section drawing, and complete the tunnel section elevation data acquisition; The tunnel section multi-source data fusion module is used to fuse multi-source heterogeneous data based on the input basic information and the collected tunnel section data to obtain the fused data results; The tunnel section extraction module is used to batch slice and process the fused data using the tunnel structure centerline method, quickly extract the subway tunnel section, and complete the tunnel section extraction; The tunnel section convergence measurement module is used to transform the extracted section results to construct independent plane coordinates of the tunnel section, fit the difference between the tunnel radius result and the design result, and measure the convergence deformation of the tunnel section; The output module is used to output the tunnel section convergence deformation measurement results.

[0039] Reference Figure 3 In an embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a storage medium and an internal memory. The storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store input basic information, collected tunnel section laser scanning images, point cloud data and tunnel section elevation data, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the tunnel section convergence precision measurement method described in any of the above embodiments can be implemented. Those skilled in the art will understand that Figure 3 The structure shown in is merely a block diagram of a portion of the structure related to the present application solution and does not constitute a limitation on the computer device to which the present application solution is applied.

[0040] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for accurately measuring the convergence of a tunnel section described in any of the above embodiments can be implemented.

[0041] In the description of the present invention, it is necessary to understand that the terms "middle", "length", "up", "down", "front", "back", "vertical", "horizontal", "inside", "outside", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0042] In the present invention, unless otherwise clearly specified and limited, the first feature "on" the second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. "Multiple" means at least two, such as two, three, etc., unless otherwise clearly and specifically limited.

[0043] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection, an electrical connection, or communication with each other; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0044] The above is only for explaining the implementation mode of the present invention and is not intended to limit the present invention. For those skilled in the art, any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention without creative work should be included in the protection scope of the present invention.

Claims

1. A method for accurately measuring tunnel section convergence, characterized in that: The following steps are involved: Receiving input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, and tunnel section information; Collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; Based on the total station, the coordinates of the measuring points on the inner wall of the tunnel are collected, the information in the coordinates is extracted, and a cross-section drawing is generated to complete the tunnel cross-section elevation data collection; Based on the input basic information, the collected tunnel section laser scanning images, point cloud data and tunnel section elevation data, multi-source heterogeneous data fusion is performed to obtain the fused data results; The tunnel structure centerline method is used to batch slice and process the fused data to quickly extract the subway tunnel section and complete the tunnel section extraction; Based on the extracted cross-section results, the independent plane coordinates of the tunnel cross-section are constructed after transformation, and the difference between the tunnel radius result and the design result is fitted to measure the convergence deformation of the tunnel cross-section; Output the tunnel section convergence deformation measurement results.

2. The tunnel section convergence accurate measurement method according to claim 1 is characterized in that: The step of collecting tunnel section laser scanning images and point cloud data and establishing a tunnel section laser scanning image collection model includes: Project the laser rangefinder into the tunnel to obtain the edge contour threshold of the laser scanning image of the subway tunnel section , and its calculation formula is: Where: Represents the grayscale value of the image; Represents the standard deviation of all pixels in the image; The laser vision tracking and recognition method is used to obtain the edge pixel distribution pixel value of the subway belt section laser scanning image, and the calculation formula is: Where: Indicates the laser scanning distance; Indicates the segmentation accuracy; Combining the gradient pixel decomposition and fuzzy identification methods, the texture of the cross-section layer is analyzed to build a visual enhancement model for the laser scanning image of the subway tunnel section. The calculation formula is: Where: represents the correction factor; The frequency domain filtering analysis is used to obtain the cross-section layer topological structure distribution matrix, and its formula is: Where: and Both represent topological distribution vectors, the former corresponds to the X-coordinate direction, and the latter corresponds to the Y-coordinate direction; According to the output results of the three-dimensional laser scanning of the tunnel section, a tunnel section laser scanning image acquisition model is constructed. The acquisition is completed using the spatial complex surface reconstruction method, and its calculation formula is: 。 3. The tunnel section convergence accurate measurement method according to claim 1 is characterized in that: In the step of collecting the coordinates of the measuring points on the inner wall of the tunnel based on the total station, extracting the information in the coordinates, generating a cross-section drawing, and completing the tunnel cross-section elevation data collection, the following steps are included: Set the section acquisition sequence and perform acquisition in sequence; Determine whether the measurement of all sections has been completed; If not, return to the step of "setting the section acquisition sequence and performing acquisition in sequence"; If so, cross-sectional measurement data is generated; Read the elevation data of the measuring point; Generate cross-sectional drawings; Output the collection results.

4. The tunnel section convergence accurate measurement method according to claim 1 is characterized in that: Federated learning algorithm is used to fuse multi-source heterogeneous data.

5. The tunnel section convergence accurate measurement method according to claim 1 is characterized in that: The step of batch slicing and processing the fused data using the tunnel structure centerline method to quickly extract the subway tunnel section and complete the tunnel section extraction includes: With the center of the tunnel structure, the cross section where the slice is located is perpendicular to the center line of the tunnel structure, and the tunnel section is extracted; Represents a coordinate point, which is located on the extracted midline, and the tangent vector through this point is Indicates that it is calculated; based on the above two calculation results, the calculation is completed Cross section of a point As a result, the formula is: According to the above formula, the fused data is segmented to form slices with a certain thickness. The distance between any points in the slice is calculated according to the formula. The calculation formula is: The thickness of the slice is Indicates that when , the cross-section point that meets the conditions is , the geometric formula for the corresponding cross-section point is: 。 6. The tunnel section convergence accurate measurement method according to claim 1 is characterized in that: The step of converting the extracted cross-section results to construct independent plane coordinates of the tunnel cross-section, fitting the difference between the tunnel radius result and the design result, and accurately measuring the convergence deformation of the tunnel cross-section includes: The converted coordinates are The expression formula of the circle is: Where: represents the coordinates of the center of the circle; Indicates the radius of a circle; Measuring point The error calculation formula is: Where: Indicate point and the distance from the circumference, the formula can be converted to: Where: , ; Among them, the initial value of the center coordinate is expressed by the average coordinate value of all measured points, and the initial value of the radius is the design result. According to the above formula, the center coordinate result of the tunnel plane is obtained, and the distance result between the measured point and the center of the circle is calculated clockwise from the upper center position. The result is compared with the design result to obtain the difference between the two and measure the cross-section convergence deformation.

7. A tunnel section convergence precision measurement system, characterized in that: include: An input module, used to receive input basic information, the basic information including: tunnel monitoring measurement, tunnel engineering information, tunnel section information; Tunnel section sampling module, used to collect tunnel section laser scanning images and point cloud data, and establish a tunnel section laser scanning image acquisition model; The tunnel section data acquisition module is used to collect the coordinates of the tunnel inner wall measurement points based on the total station, extract the information in the coordinates, generate a section drawing, and complete the tunnel section elevation data acquisition; The tunnel section multi-source data fusion module is used to fuse multi-source heterogeneous data based on the input basic information, the collected tunnel section laser scanning images, point cloud data and tunnel section elevation data to obtain the fused data results; The tunnel section extraction module is used to batch slice and process the fused data using the tunnel structure centerline method, quickly extract the subway tunnel section, and complete the tunnel section extraction; The tunnel section convergence measurement module is used to transform the extracted section results to construct independent plane coordinates of the tunnel section, fit the difference between the tunnel radius result and the design result, and measure the convergence deformation of the tunnel section; The output module is used to output the tunnel section convergence deformation measurement results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the tunnel section convergence accurate measurement method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the tunnel section convergence accurate measurement method as described in any one of claims 1 to 6 are implemented.

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