A prism optimization layout method and system of a mobile station type shield guiding system

Abstract

The application belongs to the technical field of tunnel construction, and discloses a prism optimization layout method and system of a mobile station type shield guide system, a total station station conversion precision calculation model is established, the station conversion precision of converting the total station coordinate system to the construction coordinate system is calculated, two prisms fixed on the inner wall of the tunnel and not needing to be moved are defined as 1 and 2, and a third prism needing to be moved is defined as 3, the possible installation position P3 of the third prism 3 on the pipe wall after being moved under the visible space of the total station is generated by using the Monte Carlo method based on the shield DTA axis, the shield diameter and the installation position of the total station, the possible installation position of the prism 3 generated by the Monte Carlo method is taken as a solution space, the minimum total station station conversion error is taken as an optimization target, the total station station conversion precision calculation model established by S1 is combined, and the point with the highest station conversion precision in the solution space is found based on an intelligent optimization algorithm, that is, the optimal installation position of the prism 3.

Description

Technical Field

[0001] This invention belongs to, but is not limited to, the field of tunnel construction technology, and particularly relates to a prism optimization layout method and system for a mobile station-type shield tunneling guidance system. Background Technology

[0002] The history of tunnel boring machine (TBM) construction dates back nearly a century. It first appeared in Europe in the early 1950s, primarily for the construction of urban underground pipelines and subway tunnels. Compared to earlier blasting methods, TBMs significantly improved construction efficiency and safety in excavating long-distance, large-diameter tunnels in urban environments, thus gaining widespread attention and use. After nearly 20 years of technological advancements and experience accumulation, TBM technology matured in the 1960s and 70s and expanded to more countries and regions, including the United States and Japan. Major advancements during this period included improvements in TBM design, control systems, and materials. From the 1970s to the present, TBM technology has continued to develop, attracting increasing numbers of scholars and technicians to participate in research and development. Its application areas have also gradually expanded, covering transportation tunnels, water conservancy projects, and environmental protection projects. With the development of computer technology, the automation level of TBM technology has continuously improved, significantly enhancing the efficiency and safety of tunnel construction. Automated systems can not only monitor the TBM's position and posture in real time but also precisely control the equipment, thereby reducing human error and improving project quality.

[0003] Qualified tunnel construction requires the tunnel boring machine (TBM) to excavate along the pre-designed tunnel axis. Therefore, accurately measuring the TBM's position and attitude is crucial. Existing guidance systems primarily use the laser target method to measure the TBM's position and attitude. A total station is fixed to a bracket on the tunnel wall, measuring the laser target at the tail of the shield to obtain the TBM's position and attitude. This method of measuring with the total station fixed to the bracket on the tunnel wall is also known as the fixed-station mode. As the TBM advances, if the total station becomes too far from the laser target to measure, it needs to be moved and the bracket re-welded. Installing the total station at a new site requires recalibrating its position, a labor-intensive process. Furthermore, the relocation process inevitably increases cumulative measurement errors, affecting construction quality and severely impacting efficiency and wasting materials. Compared to the fixed-station mode, modern guidance systems employ a new mode: the mobile station. In this mode, the total station is not fixed to a bracket on the tunnel wall but is mounted on a trolley and moved simultaneously with it. During segment assembly, three prisms mounted on the tunnel wall are used to determine the precise position of the total station. The total station is then used to measure the laser target at the tail of the shield to obtain the real-time attitude of the tunnel boring machine (TBM). As the TBM advances, if the total station becomes too far from the rear prism mounted on the tunnel wall to continue measuring, or if the total station's positioning accuracy is insufficient, on-site personnel only need to remove the prism furthest from the total station and move it in front of the remaining two prisms, without moving the total station and its welding support. This measurement mode fundamentally solves the problem of frequent station relocations in tunnel construction, improving the adaptability of the automatic measurement system for TBMs. Surveyors are freed from repetitive and tedious station relocation work, significantly reducing the labor costs required for tunnel guidance monitoring and greatly improving construction efficiency. Furthermore, the total station fixed on the trolley has a wider field of view, ensuring continuous measurement even during construction on curves with extremely small radii.

[0004] In rover station mode, the total station needs to repeatedly go through the relocation process, and relocation accuracy is a crucial performance indicator. Repositioning the total station after relocation requires measuring three prisms fixed to the tunnel wall. However, due to measurement errors, the obtained coordinate transformation parameters will have some inaccuracies. The measurement error varies when the total station measures prisms at different locations. Therefore, the arrangement of the three prisms in the rover station system is related to the total station's relocation accuracy. A reasonable arrangement of the prism positions is very important for accurately positioning the total station and achieving accurate guidance.

[0005] Based on the above analysis, the urgent technical problem to be solved in the existing technology is that the prism placement in the existing mobile station system is unreasonable, resulting in low accuracy of the total station when switching stations. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a prism optimization layout method and system for a mobile station-type shield tunneling guidance system.

[0007] This invention is implemented as follows: a prism optimization layout method for a mobile measuring station-type shield tunneling guidance system, comprising:

[0008] S1. Establish a total station relocation accuracy calculation model to calculate the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system.

[0009] S2, define the two fixed prisms on the tunnel wall that do not need to be moved as 1 and 2, and the third prism that needs to be moved as 3. The position coordinates of prisms 1 and 2 in the construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2.

[0010] S3, based on the shield tunnel DTA axis, shield diameter and total station installation position, uses the Monte Carlo method to generate the possible installation position P3 of the third prism 3 on the pipe wall after being moved in the total station's visible space.

[0011] S4 uses the possible installation positions of prism 3 generated by the Monte Carlo method as the solution space. With the goal of minimizing the total station transfer error, and combined with the total station transfer accuracy calculation model established in S1, the point with the highest transfer accuracy in the solution space is found based on the intelligent optimization algorithm, which is the optimal installation position of prism 3.

[0012] Furthermore, in step S1, the total station relocation accuracy calculation model is as follows:

[0013] The total station's relocation accuracy calculation model takes as input the prism coordinates in construction coordinate system 1 and the prism coordinates in total station coordinate system 2, and outputs the total station's relocation accuracy. The steps to establish this model are as follows:

[0014] S11, Calculate the positional variance of the target point (l, α, β) measured by the total station in a spherical coordinate system. The solution is as follows:

[0015]

[0016] In the formula, σ l For the measurement error, σ α ,σ β This represents the angle measurement error.

[0017] S12, a preliminary coordinate system transformation is performed using the quaternion method, converting the 2-coordinate system to a 3-coordinate system, and the rotation matrix R and translation matrix T of the coordinate transformation are solved. At this point, the transformation between station 1 and station 3 is applicable to the seven-parameter small angle transformation; analyzing the station transition accuracy between coordinate systems 1 and 2 is equivalent to analyzing the station transition accuracy between coordinate systems 1 and 3. Finally, the corrected seven-parameter model is obtained:

[0018]

[0019] In the formula, (ε x ,ε y ,ε z Let (Δx, Δy, Δz) be the small rotation angle from station 3 to station 1, (Δx, Δy, Δz) be the coordinate system translation, k be the scale factor (k≈1), and (x, y, z) be the coordinates of the common point at different stations. This can be further written as:

[0020]

[0021] Where [x] n ,y n ,z n ] i Let [x1, y1, z1]1 be the coordinates of the common point at station i, and n be the prism number. For example, [x1, y1, z1]1 is the coordinate P1_1 of prism 1 in construction coordinate system 1 as described in step S1, and [x2, y2, z2]1 is the coordinate P2_1 of prism 2 in construction coordinate system 1 as described in step S1.

[0022] S13, For the equation in step S12, let X = [Δx, Δy, Δz, kε] x ,kε y ,kε z ,k] T These are treated as unknown transfer station parameters. They can be estimated using least squares, and the matrix equation can be written in the form of a least squares error equation:

[0023] V = B - AX

[0024] in:

[0025]

[0026] Let D be the variance matrix of the coordinate measurement error of the common point at two stations. B The least squares estimate of the transfer station parameter X is calculated as follows:

[0027]

[0028] in, The variance value of the location mentioned in step S31.

[0029] The covariance matrix of the transfer station parameters is:

[0030]

[0031] In the above formula, the covariance matrix D of the transfer station parameters x From matrix D B A and A made the decision.

[0032] S14, for the target points in the measurement space, i.e., prisms 1, 2, and 3: P j (x p ,y p ,z p ), j = 1, 2, 3. During the transfer process, the transfer parameters obtained above are applied to P. j The covariance matrix of the corresponding transfer station error is as follows:

[0033]

[0034] Point P j The variances of the transfer stations in the X, Y, and Z directions are respectively

[0035]

[0036] Then P j The accuracy of the transfer station is:

[0037]

[0038] The accuracy of a total station during transit can be evaluated using the transit error at all common points:

[0039]

[0040] Furthermore, in step S3, the possible installation position of the third prism 3 on the tube wall after being moved within the total station's visible space refers to:

[0041] Considering the actual installation conditions, due to the complex structure within the tunnel boring machine (TBM), not all prisms installed on the tunnel can be observed by the total station; only a small portion of the prisms within the space can be observed. The actual visible space on site is a section of arc-shaped cylindrical tube wall space, which is the side region of a cylinder, its boundary defined by an arc. If the tunnel radius is R, the length of the cylindrical tube wall space is L, and the central angle corresponding to the arc is θ0, then in the cylindrical coordinate system, this space can be expressed as: r=R, α≤θ≤α+θ0, 0≤z≤L. R, L, θ0, and α are mainly determined by the relevant tunnel parameters and the position of the total station.

[0042] Furthermore, in step S4, the intelligent optimization algorithm finds the point with the highest accuracy in the solution space. Taking the simulated annealing algorithm as an example, the calculation includes the following steps:

[0043] S41, Set the initial solution. Using the possible installation position P3 of the third prism in the total station's visual space generated by the Monte Carlo method in step S3 as the solution space, randomly select one of the points as the initial solution x0.

[0044] S42 sets the control parameters for simulated annealing. These include: the initial annealing temperature T0, the temperature decay coefficient α, the termination temperature Tend (stopping criterion), and the number of iterations N (Markov chain length) at the current temperature.

[0045] S43, perturb the current solution and randomly generate a new position for prism 3 in the solution space, i.e., a new solution x. new Determine whether to accept the new solution x according to the Metropolis criterion. new Compare the objective function values ​​before and after the perturbation. If the objective function value corresponding to the new solution is smaller, then accept the new solution x. new Overwrite the current solution; if the objective function value of the current solution is small, then accept the current solution with a certain probability.

[0046] According to the Metropolis criterion, the probability p of accepting the new solution is as follows:

[0047]

[0048] Where f(x) is the objective function. The specific calculation steps are the total station relocation accuracy model established in step S1. The inputs are the coordinates of the prism at station 1 in the construction coordinate system (P1_1, P2_1, P3_1) and the coordinates of the prism at station 2 in the total station coordinate system (P1_2, P2_2, P3_2). The output is the relocation accuracy of the total station from station 1 to station 2.

[0049] S44 checks if the number of iterations (i.e., the number of times the perturbation is applied) at the current temperature has reached N. If it has, the temperature is lowered according to T = αT0, and this cycle continues until the current temperature is lower than the termination temperature Tend. Finally, the optimal station accuracy value in the current solution space and the corresponding point coordinates are output.

[0050] Another objective of this invention is to provide a prism optimization layout system for a mobile station-type shield tunneling guidance system, comprising: [The system includes a prism optimization layout method for implementing the aforementioned mobile station-type shield tunneling guidance system, and includes the following components:]

[0051] The calculation model building module establishes a calculation model for the total station's relocation accuracy, and calculates the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system.

[0052] The position coordinate determination module defines two fixed prisms on the tunnel inner wall that do not need to be moved as 1 and 2, and a third prism that needs to be moved as 3. The position coordinates of prisms 1 and 2 in construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2.

[0053] The installation location generation module, based on the shield tunneling DTA axis, shield diameter, and total station installation location, uses the Monte Carlo method to generate the possible installation location P3 on the pipe wall after the third prism 3 is moved in the total station's visible space.

[0054] The optimal installation location determination module uses the possible installation locations of prism 3 generated by the Monte Carlo method as the solution space. With the goal of minimizing the total station transfer error, and combined with the established total station transfer accuracy calculation model, the module uses an intelligent optimization algorithm to find the point with the highest transfer accuracy in the solution space, which is the optimal installation location of prism 3.

[0055] Another object of the present invention is to provide a computer device, the computer device including a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, causing the processor to perform the steps of the prism optimization layout method of the mobile station shield tunneling guidance system.

[0056] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the prism optimization layout method of the mobile station-type shield tunneling guidance system.

[0057] Another objective of this invention is to provide an information data processing terminal, which includes the prism optimization layout system of the mobile station-type shield tunneling guidance system.

[0058] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0059] First, this invention addresses the problem of low total station relocation accuracy caused by unreasonable prism placement in existing rover station systems. It proposes an optimal prism placement method for rover station mode. By constructing a total station relocation accuracy calculation model, the relocation accuracy at different stations during the total station's movement is calculated. Within the total station's visible space, with the highest total station relocation accuracy as the optimization objective, an intelligent optimization algorithm calculates the prism placement scheme with the highest accuracy during the relocation process.

[0060] This invention allows for the rational arrangement of prism positions, reducing the frequency of frequent prism adjustments and simplifying on-site operations, thereby lowering labor costs and operational complexity. Furthermore, it significantly improves the accuracy of the mobile measuring station, thus enabling high-precision guidance of the tunnel boring machine.

[0061] Secondly, the technical bottleneck of traditional shield tunneling guidance systems lies in the static nature of the total station and prism layout and the limitations of measurement accuracy. When the total station is too far from the rear prism or the accuracy is insufficient, real-time measurement of the shield's position and attitude cannot be guaranteed. Currently, the industry lacks scientific methods for dynamically adjusting and optimizing the prism layout, especially lacking quantitative evaluation and optimization models for the accuracy of total station relocation. At the same time, the fixed installation method of the total station increases the complexity of construction adjustments, leading to low construction efficiency and error accumulation. This invention provides a scientific and efficient solution by establishing a total station relocation accuracy calculation model and intelligent optimization algorithm, breaking through the bottlenecks of existing technologies.

[0062] This invention is based on a mathematical model for the accuracy of total station relocation. By inputting the position information of the prism in the construction coordinate system and the total station coordinate system, and combining the length measurement error, angle measurement error, and a seven-parameter transformation model, the relocation accuracy of the total station is calculated. The possible arrangement positions of the prism in a tunnel environment are simulated using the Monte Carlo method to generate a solution space. Simultaneously, using the minimization of relocation error as the objective function, and combining it with an intelligent optimization algorithm, the optimal installation position of the prism is quickly determined. This solves the complex optimization problem in the dynamic adjustment of prism layout and achieves high-precision dynamic measurement of the coordinated arrangement of the total station and prism.

[0063] This invention employs the Monte Carlo method and simulated annealing algorithm to achieve dynamic optimization of prism layout in a shield tunneling guidance system for the first time. The Monte Carlo method combines tunnel diameter, shield centerline, and visible space to generate the prism layout solution space, ensuring its scientific rigor and comprehensiveness. The simulated annealing algorithm, aiming to minimize station transfer errors, achieves rapid optimization of the complex solution space by setting temperature decay parameters and Markov chain lengths, significantly improving the positioning accuracy and station transfer efficiency of the total station. The combination of algorithm and mathematical model avoids the problems of decreased layout accuracy and low efficiency caused by manual adjustments in traditional methods.

[0064] This invention optimizes the dynamic collaboration between the total station and the prism, enabling high-precision station switching for the total station in mobile station mode, significantly improving the continuity and reliability of attitude measurement during tunnel boring machine (TBM) construction. Its algorithm- and mathematical model-based solution not only reduces the frequency of total station and prism adjustments but also significantly reduces the difficulty of manual operation, improving the overall efficiency and safety of tunnel construction. Furthermore, this invention provides a general theoretical and technical framework for optimizing the layout of the total station and prism, possessing broad application value and promoting the intelligent upgrading of underground engineering surveying technology.

[0065] Third, currently, in shield tunnel construction, total stations are used to measure the shield machine's position and attitude in real time. However, traditional methods require the total station to be fixed to a bracket on the tunnel wall. As the shield tunneling progresses, the position of the total station needs to be adjusted frequently. This adjustment not only increases the complexity of the construction but may also lead to a decrease in the positioning accuracy of the total station. In addition, the prisms in traditional methods are usually fixedly installed, lacking dynamic optimization methods. When the total station is too far from the rear prism, the continuity and accuracy of the measurement cannot be guaranteed, thus affecting construction efficiency and guidance accuracy.

[0066] This invention eliminates the need for frequent installation and fixing of traditional total stations by mounting a total station on a trolley, allowing it to move synchronously with the tunnel boring machine (TBM). By optimizing the prism layout, particularly by dynamically adjusting the position of movable prisms, the invention solves the problem of insufficient measurement accuracy when the total station is too far from the rear prism. Based on an intelligent optimization algorithm, this invention can quickly calculate the optimal installation position of the prisms, improving the accuracy of the total station's relocation and ensuring the continuity and reliability of TBM posture measurement. It overcomes the technical bottlenecks of low efficiency and unstable accuracy caused by manual prism layout adjustments in traditional methods.

[0067] The present invention has made significant technological progress in industrial applications: (1) it realizes the collaborative work of the total station and prism dynamic optimization arrangement of the shield tunneling guidance system, which improves the accuracy of station transfer and measurement efficiency; (2) based on the Monte Carlo method and intelligent optimization algorithm, it provides a scientific and accurate prism arrangement scheme, which reduces the workload of manual adjustment; (3) the optimized mobile station mode realizes efficient real-time measurement of shield tunneling posture, ensuring the accuracy of tunnel construction guidance and construction safety, and providing reliable technical support for complex tunnel construction environments.

[0068] This invention significantly improves the automation and intelligence level of tunnel boring machine (TBM) construction through an innovative prism optimization layout method and efficient total station dynamic switching technology. While reducing construction difficulty and improving measurement accuracy and efficiency, it also reduces the risks of manual operation during construction, further promoting the development of the tunnel construction industry towards higher efficiency and intelligence. This invention is not only applicable to TBM tunnel construction but can also be widely used in underground engineering surveying and other fields, possessing broad market prospects and significant industrial value. Attached Figure Description

[0069] Figure 1 This is a flowchart of the prism optimization layout method for the mobile station-type shield tunneling guidance system provided in this embodiment of the invention;

[0070] Figure 2 This is a flowchart of the mobile station mode provided in the embodiments of the present invention and a schematic diagram of the optimal placement of the prism in the mobile station process;

[0071] Figure 3 This is a schematic diagram of the simulation results of the optimized prism layout provided in the embodiment of the present invention;

[0072] Figure 4 This is a schematic diagram of the prism arrangement and distribution during the experiment provided in the embodiment of the present invention;

[0073] Figure 5 This is a schematic diagram of the total station accuracy distribution during the experiment provided in this embodiment of the invention;

[0074] Figure 6 This is a structural diagram of the prism optimization layout system of the mobile station-type shield tunneling guidance system provided in an embodiment of the present invention. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0076] This invention provides a prism optimization layout method for a mobile station-type shield tunneling guidance system. In the mobile station system, the total station does not need to be fixed to a bracket on the tunnel wall, but is mounted on a trolley and moves simultaneously with it. During segment assembly, three prisms mounted on the tunnel wall are used to determine the current precise position of the total station. Then, the total station measures the laser target located at the tail of the shield to obtain the real-time pose of the shield. As the shield advances, when the total station is too far from the rear prism mounted on the tunnel wall to continue measuring, or when the total station's positioning accuracy is insufficient, on-site personnel only need to remove the prism furthest from the total station and move it in front of the remaining two prisms, without moving the total station and welding bracket. Based on this, this invention provides a prism optimization layout method. When the total station is too far from the rear prism mounted on the tunnel wall to continue measuring, or when the total station's positioning accuracy is insufficient, the precise position of the prism furthest from the total station can be quickly calculated, thereby improving the accuracy of the total station relocation and the efficiency of the mobile station mode. The method includes the following steps:

[0077] S1. Establish a total station relocation accuracy calculation model to calculate the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system.

[0078] S2, define the two fixed prisms on the tunnel wall that do not need to be moved as 1 and 2, and the third prism that needs to be moved as 3. The position coordinates of prisms 1 and 2 in the construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2.

[0079] S3, based on the shield tunnel DTA axis, shield diameter and total station installation position, uses the Monte Carlo method to generate the possible installation position P3 of the third prism 3 on the pipe wall after being moved in the total station's visible space.

[0080] S4 uses the possible installation positions of prism 3 generated by the Monte Carlo method as the solution space. With the goal of minimizing the total station transfer error, and combined with the total station transfer accuracy calculation model established in S1, the point with the highest transfer accuracy in the solution space is found based on the intelligent optimization algorithm, which is the optimal installation position of prism 3.

[0081] S1, the total station relocation accuracy calculation model, takes the prism coordinates in construction coordinate system 1 and the prism coordinates in total station coordinate system 2 as inputs, and outputs the total station relocation accuracy. Its setup steps are as follows:

[0082] S11, Calculate the positional variance of the target point measured by the total station in a spherical coordinate system. The solution is as follows:

[0083]

[0084] In the formula, σ l For the measurement error, σ α ,σ β This represents the angle measurement error.

[0085] S12, calculate the centroid coordinates of the common point of the measurement system at stations 1 and 2. Assume the centroid of the common point in the 2-station system is... The centroid of the common point in the 1-station system is The cross-co-occurrence matrix can be obtained:

[0086]

[0087] In the formula, n is the number of common points, and the coordinates of each common point under station 1 and station 2 are respectively.

[0088] S13, let the antisymmetric matrix S = UU T , column vector η=[S 23 ,S 31 ,S 12 ] T We can obtain matrix Q:

[0089]

[0090] Finding the largest eigenvalue of Q yields its corresponding eigenvector, which is the value of the unit quaternion (q0, q1, q2, q3). Using the formula for the rotation matrix, we can obtain the rotation matrix R. Finally, we obtain the translation matrix T by inverse solving. The formula for the rotation matrix is ​​as follows:

[0091]

[0092] S14, using the quaternion method described above, the 1-station model is transformed into the 3-station model. At this point, the transformation between the 3-station and 2-station models is applicable to the seven-parameter small angle transformation, and the accuracy of the station transition between coordinate systems 1 and 2 is equivalent to the accuracy of the station transition between coordinate systems 2 and 3. Finally, the corrected seven-parameter model is obtained:

[0093]

[0094] In the formula, (ε x ,ε y ,ε z Let (Δx, Δy, Δz) be the small rotation angle from 3 stations to 2 stations, (Δx, Δy, Δz) be the coordinate system translation, and k be the scale factor (k≈1). This can be further written as:

[0095]

[0096] Where [x] n ,y n ,z n ] i Let [x1, y1, z1]1 be the coordinates of the common point at station i. For example, [x1, y1, z1]1 is the coordinate P1_1 of prism 1 in construction coordinate system 1 as described in step S1, and [x2, y2, z2]1 is the coordinate P2_1 of prism 2 in construction coordinate system 1 as described in step S1.

[0097] S15, For the equation in step S14, let X = [Δx, Δy, Δz, kε x ,kε y ,kε z ,k] T These are treated as unknown transfer station parameters. They can be estimated using least squares, and the matrix equation can be written in the form of a least squares error equation:

[0098] V = B - AX

[0099] in:

[0100]

[0101] Let D be the variance matrix of the coordinate measurement error of the common point at two stations. B The least squares estimate of the transfer station parameter X is calculated as follows:

[0102]

[0103] in, The variance value of the location mentioned in step S31.

[0104] The covariance matrix of the transfer station parameters is:

[0105]

[0106] In the above formula, the covariance matrix D of the transfer station parameters x From matrix D B A and A made the decision.

[0107] S16, for the target points in the measurement space, i.e., prisms 1, 2, and 3: P j (x p ,y p ,z p ), j = 1, 2, 3. During the transfer process, the transfer parameters obtained above are applied to P. j The covariance matrix of the corresponding transfer station error is as follows:

[0108]

[0109] Point P j The variances of the transfer stations in the X, Y, and Z directions are respectively

[0110]

[0111] The accuracy of the transfer point P is:

[0112]

[0113] Overall transfer accuracy can be evaluated using the transfer errors at all common points:

[0114]

[0115] S3, the Monte Carlo method for generating possible installation locations for the third prism in the total station's visible space includes the following steps:

[0116] S31, randomly generate pipe wall boundary points based on DTA and tunnel diameter.

[0117] S32, predict the total station's trajectory based on its initial position and DTA. Calculate the tangent vector for each pair of adjacent centerline points on the total station's trajectory and standardize it.

[0118] S33. Select a non-tangent vector and perform a cross product with the tangent vector to obtain the normal vector, and then standardize it. Calculate the binormal vector using the cross product of the tangent vector and the normal vector, and then standardize it.

[0119] S34. For each cross-section point, the coordinates of each point are calculated by adding the components of the normal and binormal directions at the centerline point location, generating a circular cross-section point along the centerline.

[0120] S35, divide the circular cross-section points generated in step S34 according to the total station's visible angle range to obtain the possible installation position of the third prism in the total station's visible space.

[0121] S4, the intelligent optimization algorithm finds the point with the highest accuracy in the solution space. Taking simulated annealing as an example, the calculation includes the following steps:

[0122] S41, Set the initial solution. Using the possible installation position P3_1 of the third prism in the total station's visual space generated by the Monte Carlo method in step S3 as the solution space, randomly select a point as the initial solution x0.

[0123] S42 sets the control parameters for simulated annealing. These include: the initial annealing temperature T0, the temperature decay coefficient α, the termination temperature Tend (stopping criterion), and the number of iterations N (Markov chain length) at the current temperature.

[0124] The parameters selected for this invention are shown in the table below.

[0125]

[0126] S43, perturb the current solution and randomly generate a new position for prism 3 in the solution space, i.e., a new solution x. new Determine whether to accept the new solution x according to the Metropolis criterion. new Compare the objective function values ​​before and after the perturbation. If the objective function value corresponding to the new solution is smaller, then accept the new solution x. new Overwrite the current solution; if the objective function value of the current solution is small, then accept the current solution with a certain probability.

[0127] According to the Metropolis criterion, the probability of accepting a new solution is as follows:

[0128]

[0129] Where f(x) is the objective function. The specific calculation steps are the total station relocation accuracy model established in step S1. The inputs are the coordinates of the prism at station 1 in the construction coordinate system (P1_1, P2_1, P3_1) and the coordinates of the prism at station 2 in the total station coordinate system (P1_2, P2_2, P3_2). The output is the relocation accuracy of the total station from station 1 to station 2.

[0130] S44 checks if the number of iterations (i.e., the number of times the perturbation is applied) at the current temperature has reached N. If it has, it cools the temperature according to T = αT0, and continues this cycle until the current temperature is lower than the termination temperature Tend. Finally, it outputs the optimal station accuracy value in the current solution space and the corresponding point coordinates.

[0131] This invention proposes a prism optimization layout method for a mobile station-type shield tunneling guidance system to improve the accuracy and measurement efficiency of total station relocation. By mounting the total station on a trolley and moving it synchronously with the shield, and arranging three prisms (1 and 2 are fixed prisms, and 3 is a movable prism) on the tunnel wall, the total station determines its own coordinates by measuring the positions of the prisms, thereby obtaining the real-time position and orientation of the shield machine. By optimizing the position layout of prism 3, high-precision positioning capability can be maintained during the total station's movement without frequent adjustments to the total station or support structure.

[0132] The system utilizes a seven-parameter transformation model between construction coordinate system 1 and total station coordinate system 2 to calculate the relocation accuracy. A rotation matrix is ​​established based on the quaternion method, and the translation matrix is ​​solved by the coordinate differences of common points. A covariance matrix is ​​constructed by combining length measurement error and angle measurement error, and finally, the covariance and variance distribution of the relocation parameters are calculated. The overall relocation accuracy is comprehensively evaluated using the relocation errors of all common points, providing a mathematical basis for prism optimization layout.

[0133] In the tunnel construction environment, the Monte Carlo method is used to simulate the possible installation positions of prism 3 within the visible space of the total station. By generating boundary points on the tunnel wall, and based on the calculation of the shield centerline and its tangent vector, normal vector, and subnormal, circular cross-section points within the visible space of the total station are generated. These cross-section points are then filtered to determine the set of points that fit within the visible range, forming the solution space of candidate installation positions for prism 3.

[0134] In the candidate solution space, the objective function is to minimize the transfer station error, and the simulated annealing algorithm is used for optimization. The initial solution is a randomly selected prism 3 position. Iterative optimization is performed based on the Metropolis criterion, taking into account parameters such as annealing temperature and Markov chain length. Each time a new solution is generated, the objective function value of the new solution is compared with that of the current solution. If the new solution is better, the solution set is updated; if the current solution is better, the new solution is accepted with a certain probability. Finally, the optimal transfer station accuracy value and the corresponding prism 3 installation position in the current solution space are output.

[0135] When the total station moves too far from the rear prism or the positioning accuracy is insufficient, the system calculates the optimal position of prism 3 based on the optimization algorithm. On-site personnel only need to move the prism furthest from the total station to the optimal position in front, without adjusting the total station or welding the support. Under the new layout, prisms 1, 2, and 3, together with the total station, form a new high-precision measurement network, ensuring real-time measurement and guidance of the tunnel boring machine's posture.

[0136] The prism optimization layout method of this invention significantly improves the station transfer efficiency of total stations in shield tunneling. Dynamic optimization of the prism layout reduces the frequency of total station adjustments, improving guidance accuracy and efficiency during tunnel construction. Simultaneously, the use of intelligent algorithms combined with the Monte Carlo method ensures the scientific rigor and operability of prism relocation operations, providing reliable technical support for shield tunneling guidance in complex tunnel construction environments.

[0137] like Figure 6 As shown, the prism optimization layout system of the mobile station-type shield tunneling guidance system includes:

[0138] The calculation model building module establishes a calculation model for the total station's relocation accuracy, and calculates the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system.

[0139] The position coordinate determination module defines two fixed prisms on the tunnel inner wall that do not need to be moved as 1 and 2, and a third prism that needs to be moved as 3. The position coordinates of prisms 1 and 2 in construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2.

[0140] The installation location generation module, based on the shield tunneling DTA axis, shield diameter, and total station installation location, uses the Monte Carlo method to generate the possible installation location P3 on the pipe wall after the third prism 3 is moved in the total station's visible space.

[0141] The optimal installation location determination module uses the possible installation locations of prism 3 generated by the Monte Carlo method as the solution space. With the goal of minimizing the total station transfer error, and combined with the established total station transfer accuracy calculation model, the module uses an intelligent optimization algorithm to find the point with the highest transfer accuracy in the solution space, which is the optimal installation location of prism 3.

[0142] An application embodiment of the present invention provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the prism optimization layout method for a mobile station-type shield tunneling guidance system.

[0143] An application embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of a prism optimization layout method for a mobile station-type shield tunneling guidance system.

[0144] An application embodiment of the present invention provides an information data processing terminal, which includes a prism optimization layout system for a mobile station-type shield tunneling guidance system.

[0145] This invention uses computer simulation to model the tunnel boring machine (TBM) excavation process in a moving station mode. It analyzes the impact of different prism placement positions within the total station's field of view on the total station's accuracy when the prism furthest from the total station needs to be moved. Simulation results are shown in the figure. Figure 3 As shown in the diagram, the red dots represent the optimal arrangement of prism 3, which provides the highest total station accuracy. The redder the dot, the lower the total station accuracy; conversely, the bluer the dot, the higher the accuracy. This provides a reference for prism arrangement in rover station mode, allowing for reasonable arrangement based on actual site conditions. Furthermore, experiments were conducted in a simulated tunnel environment to investigate the impact of different prism arrangements on the total station's positioning accuracy. The experimental procedure is as follows:

[0146] 1. Set up a total station 1 at a certain location, fix two prisms P_1 and P_2 in a simulated pipe wall environment, and use the total station to measure their coordinates multiple times and regard them as the true values ​​of the prism positions in the construction coordinate system;

[0147] 2. Set up a total station 2 at another location, and randomly place a third prism P_3. Use the total station to measure the coordinates of P_1, P_2, and P_3 multiple times and use them as observation values.

[0148] 3. Based on the total station's relocation accuracy calculation model, the total station's 2-station relocation accuracy was calculated when the third prism was in different positions.

[0149] Figure 4 This is a schematic diagram of the prism distribution. Figure 5 This diagram illustrates the positioning accuracy of the total station under different prism arrangements. The distribution of the total station's accuracy during station transitions in this experiment is similar to the results of computer simulations.

[0150] Application Example 1: Optimized Layout of Prisms in Tunnel Boring Guiding Systems

[0151] In the process of tunneling a subway tunnel in a certain city, a prism optimization layout method for a mobile station-based shield tunneling guidance system was adopted to achieve precise guidance during the tunneling process. First, a total station relocation accuracy calculation model was established. By inputting the fixed coordinates of prisms 1 and 2 in the construction coordinate system and the total station's measured coordinates, the relocation accuracy was calculated. Then, based on the shield tunneling parameters (such as tunnel diameter and shield machine position) and the total station's installation position, the Monte Carlo method was used to generate the possible installation positions of prism 3 on the tunnel wall. Finally, the solution space was optimized using a simulated annealing algorithm to find the installation position of prism 3 with the highest relocation accuracy. The optimization results were used for actual deployment to ensure efficient and accurate guidance of the total station in complex tunneling scenarios.

[0152] Application Example 2: Optimization of Measurement Layout in Underground Utility Tunnel Construction

[0153] In an underground utility tunnel construction project, a mobile station-type shield tunneling guidance system was used for survey layout optimization. A total station was installed in the construction area, and construction accuracy was calibrated using prisms fixed to the inner wall of the tunnel. Due to the complex internal structure of the tunnel, the specific installation position of prism 3, which needed to be moved, significantly affected the accuracy of the relocation. Using this method, possible installation positions of prism 3 were generated through Monte Carlo methods, and the solution space was limited by the geometric parameters of the tunnel (such as radius, length, and structural complexity). Then, an intelligent optimization algorithm (such as simulated annealing) was used to calculate the total station relocation accuracy model to find the optimal installation position. The optimized survey layout improved the efficiency and accuracy of positioning and measurement during tunnel construction.

[0154] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0155] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A prism optimization layout method for a mobile measuring station-type shield tunneling guidance system, characterized in that, include: S1. Establish a total station relocation accuracy calculation model and calculate the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system. S2, define the two fixed prisms on the tunnel wall that do not need to be moved as 1 and 2, and the third prism that needs to be moved as 3; the position coordinates of prisms 1 and 2 in the construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2. S3, based on the shield tunnel DTA axis, shield diameter and total station installation position, the Monte Carlo method is used to generate the possible installation position P3 of the third prism 3 on the pipe wall after being moved in the total station's visible space; S4. The possible installation positions of prism 3 generated by the Monte Carlo method are used as the solution space. With the minimum total station transfer error as the optimization objective, combined with the total station transfer accuracy calculation model established in S1, the point with the highest transfer accuracy in the solution space is found based on the intelligent optimization algorithm, which is the optimal installation position of prism 3. In step S4, the intelligent optimization algorithm finds the point with the highest accuracy in the solution space; this includes the following steps: S41, Set the initial solution; Take the possible installation position P3 of the third prism in the total station's visual space generated by the Monte Carlo method in step S3 as the solution space, and randomly select one of the points as the initial solution x0; S42, set the control parameters for simulated annealing, specifically including: the initial annealing temperature T0, the temperature decay coefficient α, the termination temperature Tend, and the number of iterations N at the current temperature; S43, perturb the current solution and randomly generate a new position for prism 3 in the solution space, i.e., a new solution x. new ; Determine whether to accept the new solution x according to the Metropolis criterion. new Compare the objective function values ​​before and after the perturbation; if the objective function value corresponding to the new solution is smaller, then accept the new solution x. new Overwrite the current solution; if the objective function value of the current solution is small, then accept the current solution with a certain probability. According to the Metropolis criterion, the probability of accepting a new solution is as follows: ； in, The objective function is defined as follows: the total station relocation accuracy model established in step S1 is used; the inputs are the coordinates of the prism at station 1 in the construction coordinate system (P1_1, P2_1, P3_1) and the coordinates of the prism at station 2 in the total station coordinate system (P1_2, P2_2, P3_2); the output is the relocation accuracy of the total station as it moves from station 1 to station 2. S44 determines whether the number of iterations at the current temperature has reached N. If it has, the temperature is reduced according to T=αT0. This process is repeated until the current temperature is lower than the termination temperature Tend. Finally, the optimal value of the transfer station accuracy in the current solution space and the corresponding point coordinates are output.

2. The prism optimization layout method for the mobile station-type shield tunneling guidance system as described in claim 1, characterized in that, In step S1, the total station relocation accuracy calculation model is as follows: The input to the total station's relocation accuracy calculation model is the prism coordinates under construction coordinate system 1 and the prism coordinates under total station coordinate system 2, and the output is the total station's relocation accuracy. The steps to establish it are as follows: S11, Calculate the positional variance of the target point measured by the total station in a spherical coordinate system. The solution is as follows: ； In the formula, To account for measurement error, , This refers to the angle measurement error; S12, a preliminary coordinate system transformation is performed using the quaternion method, converting the 2-coordinate system to a 3-coordinate system, and solving for the rotation matrix R and translation matrix T of the coordinate transformation; at this point, the transformation between station 1 and station 3 is applicable to the seven-parameter small angle transformation, and analyzing the station transition accuracy between coordinate systems 1 and 2 is equivalent to analyzing the station transition accuracy between coordinate systems 1 and 3; finally, the corrected seven-parameter model is obtained: ； In the formula, For the small rotation angle of the transformation from 3 stations to 1 station, The coordinate system translation is k, and the scale factor is k. ), The coordinates of a common point at different stations; further, it can be written as: ； in Let n be the coordinates of the common point at station i, and n be the prism number; for example Let P1_1 be the coordinates of prism 1 in construction coordinate system 1 as described in step S2. The coordinates of the prism 2 in step S2, P2_1, are in construction coordinate system 1. S13, for the equation in step S12, let Treating these as unknown transfer station parameters, they can be estimated using least squares, and the matrix equation can be written in the form of a least squares error equation: ； in: ， ； Let the variance matrix of the coordinate measurement error of the common point at the 2-station location be... The least squares estimate of the transfer station parameter X is calculated as follows: ； in, , , , The variance value of the location mentioned in step S31; The covariance matrix of the transfer station parameters is: ； In the above formula, the covariance matrix of the transfer station parameters From the matrix And A decides; S14, for the target points in the measurement space, i.e., prisms 1, 2, and 3: During the transfer process, the transfer parameters obtained above are applied to... The covariance matrix of the corresponding transfer station error is as follows: ； point The variances of the transfer stations in the X, Y, and Z directions are respectively : ； but The accuracy of the transfer station is: ； The accuracy of a total station during transit can be evaluated using the transit error at all common points: 。 3. The prism optimization layout method for the mobile station-type shield tunneling guidance system as described in claim 1, characterized in that, In step S3, the possible installation position of the third prism 3 on the tube wall after being moved in the total station's visible space refers to: Considering the actual installation conditions, due to the complex structure inside the tunnel boring machine (TBM), not all prisms installed on the tunnel can be observed by the total station; only a small portion of the prisms within the space can be observed. The actual visible space on site is a section of arc-shaped cylindrical wall space, which is the side region of a cylinder, its boundary defined by an arc. If the tunnel radius is R, the length of the cylindrical wall space is L, and the central angle corresponding to the arc is... Then, in cylindrical coordinates, this space can be represented as: R, L, , It is mainly determined by tunnel-related parameters and the position of the total station.

4. A prism optimization layout system for a mobile station-type shield tunneling guidance system, implementing the prism optimization layout method for any one of claims 1 to 3, characterized in that, include: The calculation model building module establishes a calculation model for the total station's relocation accuracy and calculates the relocation accuracy when the total station coordinate system is transformed to the construction coordinate system. The position coordinate determination module defines two fixed prisms on the tunnel inner wall that do not need to be moved as 1 and 2, and the third prism that needs to be moved as 3; the position coordinates of prisms 1 and 2 in construction coordinate system 1 are known as P1_1 and P2_1, and the position coordinates of the two prisms measured by the total station are known as P1_2 and P2_2. The installation location generation module, based on the shield tunnel DTA axis, shield diameter, and total station installation location, uses the Monte Carlo method to generate the possible installation location P3 on the pipe wall after the third prism 3 is moved in the total station's visible space. The optimal installation location determination module uses the possible installation locations of prism 3 generated by the Monte Carlo method as the solution space. With the goal of minimizing the total station transfer error, and combined with the established total station transfer accuracy calculation model, the module uses an intelligent optimization algorithm to find the point with the highest transfer accuracy in the solution space, which is the optimal installation location of prism 3.

5. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the prism optimization layout method for the mobile station-type shield tunneling guidance system as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the prism optimization layout method for a mobile station-type shield tunneling guidance system as described in any one of claims 1 to 3.

7. An information data processing terminal, comprising the prism optimization layout system of the mobile station-type shield tunneling guidance system as described in claim 4.

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