Method and system for measuring arch crown subsidence of multi-arch tunnel

Abstract

The invention relates to the technical field of sinkage measurement, and discloses a multi-arch tunnel vault sinkage measurement method and system, which are used for improving the efficiency and accuracy of multi-arch tunnel vault sinkage measurement. The method comprises the following steps: carrying out benchmark layout on the exterior and interior of a tunnel to obtain a leveling network penetrating through the whole tunnel; a high-precision settlement observation mark is installed at the vault position of the tunnel monitoring section, and a fixed monitoring point group is obtained; performing periodic high-precision leveling on the fixed monitoring point group to obtain absolute deflection data of each monitoring point; performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; the multi-arch section area of the tunnel is automatically monitored by a geometric level gauge at a preset frequency, and continuous deflection data are obtained; and performing fusion analysis on the absolute subsidence data, the spatial position change data and the continuous subsidence data of each monitoring point to obtain an overall subsidence trend evaluation result and a tunnel maintenance strategy suggestion.

Description

Technical Field

[0001] The present invention relates to the technical field of subsidence measurement, and in particular to a method and system for measuring the subsidence of a double-arch tunnel vault. Background Art

[0002] As an important underground engineering structure, multi-arch tunnels are widely used in the construction of transportation infrastructure such as railways and highways. During the operation of tunnels, due to the influence of geological conditions, construction quality, load changes and other factors, arch subsidence is a common and serious safety hazard. Traditional tunnel arch subsidence measurement methods mainly include manual measurement and single sensor monitoring. These methods obtain the deformation data of the tunnel arch by regularly performing leveling, total station measurement or installing displacement sensors, providing a basis for tunnel safety assessment and maintenance.

[0003] However, the existing technology has some shortcomings. First, the manual measurement method is labor-intensive and inefficient, making it difficult to achieve high-frequency, long-term continuous monitoring. Second, although single-sensor monitoring can achieve automation and continuity, its measurement accuracy and reliability are often affected by environmental factors, and it is difficult to fully reflect the overall deformation trend of the tunnel. In addition, the existing methods are relatively simple in data processing and analysis, making it difficult to effectively integrate multi-source data and fully tap the potential value of the data, resulting in low accuracy in the assessment and prediction of tunnel sinking trends. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method and system for measuring the subsidence of a double-arch tunnel vault, which are used to improve the efficiency and accuracy of measuring the subsidence of a double-arch tunnel vault.

[0005] The present invention provides a method for measuring the subsidence of a vault of a multi-arch tunnel, comprising: arranging leveling points outside and inside the tunnel to obtain a leveling network that runs through the entire tunnel; based on the leveling network, installing high-precision settlement observation marks on the vault position of the tunnel monitoring section to obtain a fixed monitoring point group; based on the leveling network, performing periodic high-precision leveling on the fixed monitoring point group to obtain absolute subsidence data of each monitoring point; performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; based on the fixed monitoring point group, performing automatic monitoring of the multi-arch section area of ​​the tunnel with a geometric level at a preset frequency to obtain continuous subsidence data; and fusing and analyzing the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data by the least squares method to obtain an overall subsidence trend assessment result and a tunnel maintenance strategy recommendation.

[0006] The present invention also provides a multi-arch tunnel vault sinking measurement system, comprising: The layout module is used to layout level points outside and inside the tunnel to obtain a leveling network throughout the tunnel; An installation module is used to install high-precision settlement observation marks at the arch position of the tunnel monitoring section based on the leveling network to obtain a fixed monitoring point group; A measurement module, used to perform periodic high-precision leveling measurement on the fixed monitoring point group based on the leveling measurement network to obtain absolute subsidence data of each monitoring point; A calculation module, used for performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; A monitoring module, for automatically monitoring the continuous arch section of the tunnel with a geometric level at a preset frequency based on the fixed monitoring point group to obtain continuous subsidence data; The analysis module is used to perform a fusion analysis on the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data by the least square method to obtain an overall subsidence trend assessment result and a tunnel maintenance strategy recommendation.

[0007] In the technical solution provided by the present invention, by laying out level points outside and inside the tunnel, a leveling network running through the entire tunnel is established, which significantly improves the accuracy and stability of the measurement. Based on the leveling network, high-precision settlement observation marks are installed at the arch position of the tunnel monitoring section to form a fixed monitoring point group, ensuring the consistency and comparability of long-term monitoring. Periodic high-precision leveling measurements are performed on the fixed monitoring point group to obtain the absolute settlement data of each monitoring point, which provides key data for evaluating the overall deformation trend of the tunnel. At the same time, by performing periodic total station three-dimensional coordinate measurements on the fixed monitoring point group, spatial position change data is obtained, which can not only monitor the settlement in the vertical direction, but also capture the displacement in the horizontal direction, and fully reflect the deformation state of the tunnel structure. For the key area of ​​the continuous arch section, a geometric level with a preset frequency is used for automatic monitoring to obtain continuous settlement data, realizing high-frequency and real-time monitoring of key areas and improving the response speed to sudden deformation. Finally, various monitoring data were fused and analyzed through the least squares method to obtain the overall sinking trend assessment results and tunnel maintenance strategy recommendations, which fully utilized the complementarity of multi-source data and improved the accuracy and reliability of the assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0009] Figure 1 It is a flow chart of a method for measuring the arch subsidence of a multi-arch tunnel in an embodiment of the present invention; Figure 2 Schematic diagram of a system for measuring the arch subsidence of a multi-arch tunnel in an embodiment of the present invention. DETAILED DESCRIPTION

[0010] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0011] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying 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 limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0012] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0013] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , Figure 1 Flow chart of a method for measuring the arch subsidence of a multi-arch tunnel according to an embodiment of the present invention. Figure 1 As shown, the following steps are included: S101, arranging level points outside and inside the tunnel to obtain a leveling network running through the entire tunnel; S102. Based on the leveling network, high-precision settlement observation marks are installed at the arch position of the tunnel monitoring section to obtain a fixed monitoring point group; S103, based on the leveling network, periodically perform high-precision leveling on the fixed monitoring point group to obtain absolute subsidence data of each monitoring point; S104, performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; S105, based on the fixed monitoring point group, automatically monitor the arch section area of ​​the tunnel with a geometric level at a preset frequency to obtain continuous subsidence data; S106. The absolute subsidence data, spatial position change data and continuous subsidence data of each monitoring point are integrated and analyzed by the least squares method to obtain the overall subsidence trend assessment results and tunnel maintenance strategy recommendations.

[0014] Specifically, the three-dimensional laser scanning technology is used to scan the surrounding terrain and interior of the tunnel to obtain high-precision point cloud data. For the external terrain point cloud data, the filtering algorithm is used to reduce noise and extract key terrain feature points to provide a basis for the site selection of the leveling benchmark point. For the interior of the tunnel, the point cloud data is segmented and the section is extracted to determine the layout location of the internal leveling points. The least squares adjustment algorithm is used to optimize the network type of the candidate locations of the external and internal leveling points to ensure the geometric strength and accuracy of the leveling network. Through high-precision GPS static measurement and leveling instrument elevation transmission, a leveling network running through the entire tunnel is finally established. Based on the established leveling network, high-precision settlement observation marks are installed at the arch position of the tunnel monitoring section. First, the accuracy of the leveling network is evaluated, and the monitoring section spacing is determined based on the evaluation results. The tunnel is segmented, and geological parameter analysis is performed to evaluate the geological stability of each section. According to the results of the geological stability evaluation, the importance of the monitoring section is graded and the density of observation mark layout is determined. The specific installation location of the high-precision settlement observation mark is determined by force analysis of the arch structure. Drilling operations are carried out at determined locations, high-precision settlement observation marks are installed, and stability tests are conducted to eventually form a group of fixed monitoring points.

[0015] Using the established leveling network, periodic high-precision leveling measurements are performed on the fixed monitoring point group. First, the leveling network is periodically re-measured to evaluate the network stability and select stable leveling benchmarks. The leveling route and instrument layout plan are formulated, and round-trip measurements are performed on the fixed monitoring point group. The original observation data are corrected for temperature and atmospheric pressure, and the accuracy is evaluated by the error propagation law. After data screening and adjustment calculation, the elevation value of each monitoring point is obtained. By comparing with the initial elevation, the absolute subsidence data of each monitoring point is calculated. Periodic total station three-dimensional coordinate measurement is performed on the fixed monitoring point group to obtain spatial position change data. A total station station network is established at locations with good stability around the tunnel. The absolute coordinates of the station points are obtained through high-precision GPS static measurement, and a local coordinate system of the tunnel is established. The total station instrument is placed and leveled, and meteorological parameters are collected. Multi-angle observations are performed on the fixed monitoring point group to obtain the original observation angle and distance data. The data are corrected for atmosphere and instrument errors, and the three-dimensional coordinates of the monitoring points are calculated using the spatial forward intersection method. They are compared and analyzed with previous measurement results to obtain spatial position change data.

[0016] For the arch section of the tunnel, the geometric level is automatically monitored with a preset frequency based on the fixed monitoring point group. The key monitoring points of the arch section are selected from the fixed monitoring point group, and an automatic monitoring plan is formulated. The automated geometric level is installed to detect the stability of the instrument base. The automatic monitoring parameters are set and the automatic measurement program is compiled. The automatic measurement system is started to obtain the continuous observation raw data and transmit it to the remote database in real time. The outliers are identified and eliminated by the data cleaning algorithm, and the relative elevation changes of each monitoring point are calculated to obtain the continuous settlement data. Finally, the absolute settlement data, spatial position change data and continuous settlement data of each monitoring point are fused and analyzed by the least squares method. First, time series alignment and data standardization are performed to establish the observation equation and the initial observation matrix. Weights are assigned to different types of data by the weight distribution algorithm to obtain the weighted observation matrix. The least squares adjustment algorithm is used to estimate the settlement and obtain the comprehensive settlement estimate. The reliability of the fusion result is evaluated by residual analysis. The comprehensive settlement estimate is analyzed by time series, a settlement trend model is established, and the trend extrapolation algorithm is used for prediction calculation. According to the prediction results and the tunnel structure safety threshold, the risk level is divided to obtain the risk assessment results of each section of the tunnel. Based on the risk assessment results, targeted tunnel maintenance strategy recommendations are formulated, and finally the overall sinking trend assessment results and tunnel maintenance strategy recommendations are obtained.

[0017] Taking a certain arch tunnel as an example, more than 1 million point cloud data were obtained through 3D laser scanning. After filtering and feature extraction, 50 external leveling benchmarks and 100 internal leveling points were selected. After least squares adjustment optimization, a measurement network consisting of 150 leveling points was established, and the network accuracy reached ±0.5mm. Based on the network accuracy evaluation results, a monitoring section was set up every 50 meters in the tunnel, and a total of 200 high-precision settlement observation marks were installed. Through periodic high-precision leveling measurements, the absolute settlement data of each monitoring point was obtained, and the maximum settlement was 15mm. The three-dimensional coordinate measurement of the total station showed that the maximum horizontal displacement was 8mm. In the arch section area, the settlement data for 24 hours was obtained through automatic monitoring of the geometric level once an hour. Finally, the three types of data were fused and analyzed by the least squares method to establish a settlement trend model.

[0018] By executing the above steps, a leveling network throughout the tunnel was established by laying out leveling points outside and inside the tunnel, which significantly improved the accuracy and stability of the measurement. Based on the leveling network, high-precision settlement observation marks were installed at the arch position of the tunnel monitoring section to form a fixed monitoring point group, ensuring the consistency and comparability of long-term monitoring. Periodic high-precision leveling measurements were performed on the fixed monitoring point group to obtain the absolute settlement data of each monitoring point, providing key data for evaluating the overall deformation trend of the tunnel. At the same time, by periodically measuring the three-dimensional coordinates of the fixed monitoring point group using a total station, spatial position change data was obtained, which can not only monitor the settlement in the vertical direction, but also capture the displacement in the horizontal direction, and fully reflect the deformation state of the tunnel structure. For the key area of ​​the continuous arch section, a geometric level with a preset frequency was used for automatic monitoring to obtain continuous settlement data, realizing high-frequency and real-time monitoring of key areas and improving the response speed to sudden deformation. Finally, various monitoring data were fused and analyzed through the least squares method to obtain the overall sinking trend assessment results and tunnel maintenance strategy recommendations, which fully utilized the complementarity of multi-source data and improved the accuracy and reliability of the assessment results.

[0019] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) Perform three-dimensional laser scanning on the terrain around the tunnel to obtain point cloud data of the external terrain of the tunnel, and perform noise reduction processing on the external terrain point cloud data of the tunnel to obtain filtered external terrain point cloud data; (2) Extracting terrain features from the filtered external terrain point cloud data to obtain key terrain feature points outside the tunnel, and selecting the location of leveling benchmark points based on the key terrain feature points outside the tunnel to obtain candidate locations of the leveling benchmark points outside the tunnel; (3) Perform three-dimensional laser scanning on the interior of the tunnel to obtain point cloud data of the interior of the tunnel, and perform segmentation processing on the point cloud data of the interior of the tunnel to obtain segmented point cloud data of the interior of the tunnel; (4) Extract the section of the point cloud data of the tunnel segment to obtain the characteristic section of the tunnel, and plan the layout of the internal leveling points based on the characteristic section of the tunnel to obtain the candidate positions of the internal leveling points of the tunnel; (5) The network of candidate locations of the external leveling benchmarks and the internal leveling benchmarks of the tunnel is optimized by the least squares adjustment algorithm to obtain an optimized leveling point layout plan. The leveling points are calibrated on the tunnel entity according to the optimized leveling point layout plan to obtain entity leveling points. (6) Perform high-precision GPS static measurement on the physical leveling points to obtain the absolute coordinate data of the leveling points, and use the leveling instrument to transfer the elevation of the absolute coordinate data of the leveling points to obtain a leveling network throughout the entire tunnel.

[0020] Specifically, a three-dimensional laser scan is performed on the terrain around the tunnel to obtain the point cloud data of the external terrain of the tunnel. The three-dimensional laser scanning technology uses the principle of laser ranging to quickly obtain the three-dimensional coordinate information of the surface of the target object through a high-speed rotating laser transmitter and receiver. For a multi-arch tunnel, the scanning range usually includes the tunnel entrance, exit and the mountains on both sides, forming a high-density point cloud data set. These original point cloud data often contain noise points and need to be denoised. The denoising process uses a statistical outlier filtering algorithm, which calculates the average distance from each point to its neighboring points. If the distance from a point to its neighboring points is greater than the set threshold, it is regarded as a noise point and removed. In this way, the filtered external terrain point cloud data is obtained. The terrain feature extraction is performed on the filtered external terrain point cloud data to obtain the key terrain feature points outside the tunnel. The feature extraction process uses the curvature analysis method to calculate the local curvature of each point and identify areas with significant terrain changes. These areas usually include ridge lines, valley lines, slope change points, etc., which are key manifestations of terrain features. Based on these key terrain feature points, the site selection of leveling benchmarks is carried out. The site selection principle takes into account geological stability, visibility and accessibility, and gives priority to locations near rock outcrops or stable buildings to ensure the long-term stability of the leveling benchmark. Through this process, the candidate locations of the external leveling benchmarks of the tunnel are obtained. Subsequently, the interior of the tunnel is scanned by 3D laser to obtain the point cloud data of the tunnel interior. The internal scanning focuses on the tunnel vault, side walls and ground to form a complete 3D model of the interior of the tunnel. Considering the length and shape complexity of the tunnel, the acquired point cloud data is segmented. The segmentation process uses the equal-interval segmentation method, usually dividing every 50-100 meters into a section to obtain the segmented point cloud data of the tunnel. This segmentation processing method is conducive to subsequent fine analysis and processing. The section extraction of the segmented point cloud data in the tunnel is carried out to obtain the characteristic section of the tunnel interior. The section extraction uses the least squares fitting method to extract multiple sections perpendicular to the axis in the direction of the tunnel axis in each segmented point cloud data. These sections can reflect the changes in the geometric shape of the interior of the tunnel, including key parameters such as the vault height and width. Based on these internal characteristic sections, the internal leveling point layout planning is carried out. The layout planning takes into account the cross-sectional shape, structural stress characteristics and construction convenience, and gives priority to arranging level points at key locations such as the arch crown and arch waist. Through this process, the candidate locations of the level points inside the tunnel are obtained.

[0021] In order to optimize the distribution of leveling points, the least squares adjustment algorithm is used to optimize the network type of the candidate positions of the external leveling benchmark points of the tunnel and the candidate positions of the internal leveling points of the tunnel. The least squares adjustment algorithm obtains the optimal parameter estimation by minimizing the weighted residual sum of squares of the observation values. In the leveling network optimization, the coordinates of the leveling points are taken as unknowns, and the elevation differences between the leveling points are taken as the observation values ​​to establish the observation equation. Through iterative calculation, the optimal leveling point distribution scheme, that is, the leveling point optimization layout scheme, is obtained. According to this scheme, the leveling points are calibrated on the tunnel entity, and the leveling point markers are installed to obtain the physical leveling points. Finally, the physical leveling points are subjected to high-precision GPS static measurement to obtain the absolute coordinate data of the leveling points. GPS static measurement usually uses a dual-frequency GPS receiver, and the observation time is not less than 2 hours to ensure centimeter-level positioning accuracy. After obtaining the GPS measurement results, the absolute coordinate data of the leveling points are transmitted in elevation through the leveling instrument. The elevation transfer process adopts the round-trip closed leveling method, starting from a known elevation point, and gradually measuring the elevation difference between each leveling point, and finally obtaining a leveling network throughout the entire tunnel.

[0022] Taking a 2-kilometer-long multi-arch tunnel as an example, more than 20 million points of raw point cloud data were obtained through 3D laser scanning. After statistical outlier filtering, about 5% of noise points were eliminated, and 19 million points of high-quality point cloud data were obtained after filtering. In the feature extraction process, 500 key terrain feature points were identified, of which 20 locations were selected as candidate locations for external leveling benchmarks. The internal scanning of the tunnel obtained 15 million points of data, which were segmented into sections of 100 meters each to obtain 20 sections of internal point cloud data. Through section extraction, 5 characteristic sections were extracted from each section, a total of 100 characteristic sections, and 80 candidate locations for internal leveling points were selected based on these sections. After least squares adjustment optimization, the layout plan of 15 external leveling points and 60 internal leveling points was finally determined. GPS static measurement observed each point for 3 hours and obtained absolute coordinates with centimeter-level accuracy. The elevation was transferred through the level, and the closure error of the round-trip measurement was controlled within 3mm. Finally, a leveling measurement network with an accuracy of ±0.5mm was established.

[0023] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) Evaluate the accuracy of the leveling network to obtain the network accuracy evaluation results, determine the tunnel monitoring section spacing based on the network accuracy evaluation results, and obtain the monitoring section layout plan; (2) Mark the tunnel in sections according to the monitoring section layout plan to obtain tunnel section data, and perform geological parameter analysis on the tunnel section data to obtain the geological stability assessment results of each section; (3) Based on the geological stability assessment results of each section, the importance of each monitoring section is graded to obtain the monitoring section classification results, and the observation mark density of each section is determined according to the monitoring section classification results to obtain the observation mark layout density plan; (4) Perform stress analysis on the tunnel vault structure to obtain the vault stress distribution data, and determine the specific installation location of the high-precision settlement observation mark based on the vault stress distribution data to obtain the installation coordinates of the observation mark; (5) According to the observed mark installation coordinates, drilling operations are performed on the tunnel vault to obtain the mark installation holes, and the depth and direction of the mark installation holes are detected to obtain hole position verification data; (6) Based on the hole position verification data, a high-precision settlement observation mark is embedded in the mark installation hole to obtain the initial fixed monitoring point. The initial fixed monitoring point is tested for stability to obtain a fixed monitoring point group.

[0024] Specifically, the accuracy of the established leveling network is evaluated. The accuracy evaluation is carried out by the closure error method, which calculates the closure error of each closed loop in the leveling network and compares it with the theoretical closure error. The evaluation indicators include relative mean error and absolute mean error, where the relative mean error reflects the relative level of measurement accuracy, and the absolute mean error indicates the absolute size of the actual measurement deviation. Based on these evaluation results, the spacing of tunnel monitoring sections is determined. The determination of the spacing takes into account factors such as network accuracy, tunnel length and geological conditions. Usually, in areas with higher accuracy, the section spacing can be appropriately increased, while in areas with lower accuracy or complex geological conditions, the section spacing needs to be reduced to increase the monitoring density. Through this process, the monitoring section layout plan is obtained. According to the monitoring section layout plan, the tunnel is marked in sections. The purpose of segment marking is to divide the tunnel into several monitoring units to facilitate subsequent fine monitoring and analysis. The length of each segment usually corresponds to the section spacing, but it will also be adjusted according to actual conditions. For each segment, its geological parameters are collected and analyzed, including lithology, joint development, groundwater conditions, etc. The geological parameter analysis adopts a comprehensive scoring method to quantify the scores of various geological factors, and then obtain the geological stability index of each section through weighted summation. Based on these indices, the geological stability assessment results of each section are obtained.

[0025] Next, based on the geological stability assessment results of each section, the importance of each monitoring section is graded. The grading standard takes into account factors such as the geological stability index, the importance of the section location (such as the tunnel entrance, exit, and arch section), and the sensitivity of the surrounding environment. Sections are usually divided into three importance levels: high, medium, and low. According to the grading results of the monitoring sections, the density of observation marks for each section is determined. The density of observation marks is large for sections with high importance, while the density of observation marks is relatively small for sections with low importance. Through this process, the density plan of observation mark layout is obtained. In order to determine the specific installation position of high-precision settlement observation marks, it is necessary to perform a force analysis on the tunnel vault structure. The force analysis uses the finite element method to establish a mechanical model of the tunnel vault structure, considers factors such as rock and soil pressure, deadweight, and traffic load, and calculates the stress distribution of each point on the vault. Based on the stress distribution data of the vault, stress concentration areas or locations with large stress gradients are selected as the installation points of the observation marks. These locations are often the most sensitive areas of structural deformation. Through this process, the installation coordinates of the observation marks are obtained.

[0026] According to the installation coordinates of the observation mark, drilling operations are carried out on the tunnel vault. The drilling depth and diameter are determined according to the size of the observation mark and the installation requirements, and the depth is usually between 10-20cm. After the drilling is completed, the depth and direction of the mark installation hole are detected using a hole depth gauge and a bore gauge to ensure that the accuracy of the drilling meets the requirements. The test results form hole position verification data, including parameters such as actual hole depth, hole diameter and hole axis direction. Based on the hole position verification data, a high-precision settlement observation mark is embedded in the mark installation hole. Special adhesives are used during the installation process to ensure that the observation mark is tightly integrated with the tunnel structure. After the installation is completed, the initial fixed monitoring point is formed. These initial fixed monitoring points are subjected to stability tests, and the test methods include repeated loading tests and short-term observation comparisons. Through the stability test, unstable or substandard monitoring points are eliminated, and finally a group of fixed monitoring points is obtained.

[0027] Taking a 3-kilometer-long multi-arch tunnel as an example, the accuracy of the leveling network was first evaluated, and the relative mean error was calculated to be 1 / 50000 and the absolute mean error was ±0.8mm. Based on this accuracy level, the monitoring section spacing was determined to be 50 meters, and a total of 60 monitoring sections were set. The tunnel was marked in sections, and 60 sections were obtained, and geological parameters were analyzed for each section. The analysis results showed that 10 sections were weak surrounding rock areas, and the geological stability index was less than 60 points (out of 100 points). According to the results of the geological stability assessment, the 60 monitoring sections were divided into 15 high-importance sections, 25 medium-importance sections, and 20 low-importance sections. Five observation marks were set for high-importance sections, three for medium-importance sections, and two for low-importance sections. Through finite element analysis, the arch stress distribution data was obtained. The maximum stress concentration area appeared in the middle of the multi-arch section, and the stress value reached 15MPa. Based on the stress distribution, the installation coordinates of 240 observation marks were determined. After the drilling operation was completed, the hole position verification showed that the average hole depth was 15.5cm and the hole diameter error was controlled within ±0.5mm. In the stability test after the installation was completed, 5 monitoring points did not meet the requirements and were eliminated, and finally a monitoring point group of 235 fixed monitoring points was formed.

[0028] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Periodically re-measure the leveling network to obtain network stability assessment data, and select stable leveling benchmarks based on the network stability assessment data to obtain the measurement reference benchmark; (2) Based on the measurement reference datum, formulate the leveling measurement route, obtain the measurement route map, and arrange the instrument sites based on the measurement route map to obtain the instrument arrangement plan; (3) According to the instrument layout plan, round-trip measurements are carried out on the fixed monitoring point group to obtain the original observation data, and the original observation data are corrected for temperature and atmospheric pressure to obtain the corrected observation data; (4) The accuracy of the corrected observation data is evaluated by the error propagation law to obtain the measurement accuracy evaluation results, and valid observation data is screened based on the measurement accuracy evaluation results to obtain valid leveling measurement data; (5) Perform adjustment calculation on the effective leveling data to obtain the elevation value of each monitoring point. By comparing it with the initial elevation, calculate the elevation change of each monitoring point and obtain the absolute subsidence data of each monitoring point.

[0029] Specifically, the leveling network is periodically re-measured to evaluate the stability of the network. The re-measurement adopts the closed route method, measuring each closed loop in the network and calculating the closure error. The network stability assessment uses the following formula: ; in, is the network stability indicator, For the The closing error of a closed loop, is the number of closed loops. Stability index The smaller the value, the more stable the network is. Based on this evaluation result, the point with the smallest stability index is selected as the leveling benchmark to form the measurement reference benchmark.

[0030] According to the measurement reference benchmark, the leveling measurement route is formulated. The route design follows the principle of "from known to unknown" and adopts a circular layout method to ensure that each monitoring point is included in at least one closed loop. The minimum spanning tree algorithm in graph theory is used to draw the measurement route map to connect all monitoring points with the shortest total path. Based on the measurement route map, the instrument sites are laid out. The site layout takes into account the unobstructed line of sight and the distance between the measuring stations, which is usually controlled between 50-100 meters to obtain the instrument layout plan. According to the instrument layout plan, round-trip measurements are performed on the fixed monitoring point group. The round-trip measurement is to eliminate system errors and improve measurement accuracy. During the measurement process, the temperature and air pressure data of each measuring station are recorded. The original observation data is corrected for temperature and atmospheric pressure using the following formula: ; in, is the height difference after correction, is the original observed height difference, is the temperature correction coefficient, is the temperature difference, is the pressure correction factor, is the pressure difference. Through this correction, the corrected observation data is obtained. The error propagation law is used to evaluate the accuracy of the corrected observation data. The error propagation law is expressed as: ; in, is the standard deviation of function F, F is the variable The partial derivative of For variables The standard deviation of . Through this calculation, the accuracy evaluation result of each observation value is obtained. Based on the accuracy evaluation result, a threshold is set to filter the valid observation data. Usually, data with an accuracy better than ±0.5mm is selected as the valid leveling measurement data. The valid leveling measurement data is adjusted using the conditional adjustment method. The conditional equation is: ; Among them, B is the coefficient matrix, V is the correction vector, and W is the constant term vector. By solving the equation, the elevation value of each monitoring point after adjustment is obtained. Compare these elevation values ​​with the initial elevation, calculate the elevation change, and obtain the absolute settlement data of each monitoring point. For example, a 2.5-kilometer-long arch tunnel has 50 fixed monitoring points. The results of periodic re-measurement show that the network stability index S is 0.3mm, and the three points with the best stability are selected as leveling reference points. The measurement route design forms 5 closed loops with a total length of 5.2 kilometers. During the round-trip measurement, the temperature variation range was recorded to be 18°C ​​to 25°C, and the air pressure variation range was 98.5kPa to 101.2kPa. Temperature correction coefficient for , pressure correction factor for . After correction, the standard deviation of the observation data was reduced from the original ±0.8mm to ±0.6mm. The accuracy of each observation value was calculated by the error propagation law, of which 45 observation values ​​had an accuracy better than ±0.5mm and were selected as valid data. After adjustment calculation, the final elevation value of each monitoring point was obtained. Compared with the initial elevation, it was found that the maximum subsidence was 12.3mm, which occurred at a monitoring point in the middle of the arch section.

[0031] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Select locations with good stability around the tunnel, establish a total station network, obtain a station network layout plan, and install station markers based on the station network layout plan to obtain physical station locations; (2) Perform high-precision GPS static measurement on the physical measuring station to obtain the absolute coordinate data of the measuring station, and establish the local coordinate system of the tunnel through measuring station coordinate conversion to obtain the local coordinates of the measuring station; (3) According to the local coordinates of the measuring station, the total station is installed and leveled to obtain the instrument positioning data, and the meteorological parameters are collected and input for the instrument positioning data to obtain the measurement environment parameters; (4) Based on the measurement environment parameters, multi-angle observations are performed on the fixed monitoring point group to obtain the original observation angle and distance data, and the original observation angle and distance data are corrected for atmospheric and instrument errors to obtain the corrected observation data; (5) The corrected observation data is calculated through the spatial forward intersection method to obtain the three-dimensional coordinate values ​​of the monitoring points, which are then compared and analyzed with the previous measurement results to obtain the spatial position change data.

[0032] Specifically, locations with good stability are selected around the tunnel to establish a total station network. The principles for site selection include geological stability, wide field of view, and easy long-term preservation. Usually, multiple points are selected at the entrance, exit and both sides of the tunnel to form a network structure to improve measurement accuracy and reliability. The station network layout plan takes into account the inter-visibility and geometric strength between stations to ensure that each monitoring point can be observed by at least two stations. Based on the station network layout plan, station identification is installed. The identification is usually made of concrete piers or stainless steel signs, buried deep underground to ensure long-term stability, so as to obtain a physical station. High-precision GPS static measurement is performed on the physical station to obtain the absolute coordinate data of the station. GPS static measurement uses a dual-frequency GPS receiver, and the observation time is usually not less than 4 hours to ensure centimeter-level positioning accuracy. The measurement adopts the relative positioning method, selects the base station with known coordinates as a reference, and obtains the three-dimensional coordinates of the station in the WGS84 coordinate system through baseline solution. In order to facilitate subsequent operations, the WGS84 coordinate system needs to be converted into the local coordinate system of the tunnel. The coordinate transformation process includes translation, rotation and scale transformation, and the transformation parameters are calculated through known control points. After the transformation, the coordinates of the measuring station in the local coordinate system of the tunnel are obtained. This local coordinate system usually takes the tunnel axis direction as the Y axis, the axis perpendicular to the axis to the right as the X axis, and the vertical upward as the Z axis.

[0033] According to the local coordinates of the station point, the total station is placed and leveled. During the instrument placement process, the total station is firmly installed on the station point using a tripod and a base, and then accurately leveled. The leveling process includes two steps: rough leveling and fine leveling. Rough leveling is achieved by adjusting the foot screws and circular level, and fine leveling is achieved by the electronic level. The leveling accuracy is controlled within 10". After the leveling is completed, the coordinates of the measuring station and the instrument height are input to obtain the instrument positioning data. At the same time, the meteorological parameters of the instrument positioning data are collected and input, including temperature, air pressure and humidity, which will be used for subsequent atmospheric correction to obtain the measurement environment parameters. Based on the measurement environment parameters, multi-angle observations are performed on the fixed monitoring point group. The observation adopts the full-circle observation method, that is, each monitoring point is observed multiple times from different directions to eliminate the influence of the instrument system error. The horizontal angle, vertical angle and slant distance data are recorded during the observation process to obtain the original observation angle and distance data. Atmospheric correction and instrument error correction are performed on these raw data. Atmospheric correction mainly considers the influence of temperature, air pressure and humidity on the optical path, while instrument error correction includes the correction of system errors such as vertical index difference and horizontal axis error. Through these corrections, the corrected observation data is obtained, which improves the accuracy of the data.

[0034] The corrected observation data is calculated using the spatial forward intersection method to obtain the three-dimensional coordinate values ​​of the monitoring points. Spatial forward intersection is a method for calculating the spatial coordinates of unknown points (monitoring points) based on the coordinates of known points (stations) and the angle and distance of observation. The calculation process takes into account the influence of the earth's curvature and projection deformation, and the final result is obtained through iterative calculation. The calculated three-dimensional coordinate values ​​are compared and analyzed with the previous measurement results, and the coordinate difference is calculated to obtain the spatial position change data. Taking a 3-kilometer-long arch tunnel as an example, 8 locations with good stability are selected around the tunnel to establish a total station network. Through GPS static measurement, the WGS84 coordinates of these 8 stations are measured with an accuracy of better than ±5mm. After coordinate conversion, a local coordinate system based on the centerline of the tunnel is established. 150 fixed monitoring points are arranged in the tunnel, and each station observes an average of 30 monitoring points. When the total station was installed, the leveling accuracy was controlled within 5". During the observation process, the temperature range was recorded to be 15°C to 28°C, and the air pressure range was 97.5kPa to 102.3kPa. After atmospheric correction and instrument error correction of the original observation data, the angle observation accuracy was improved to ±2", and the distance observation accuracy was improved to ±1mm+1ppm. Through spatial forward intersection calculation, the three-dimensional coordinates of the monitoring point were obtained. Compared with the previous observation results, it was found that the maximum horizontal displacement was 8mm, which occurred in the middle of the arch section, and the maximum vertical displacement was 15mm, which occurred at the top of the tunnel.

[0035] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) Screen the monitoring points in the arch section area in the fixed monitoring point group to obtain the key monitoring point set of the arch section, and formulate an automatic monitoring plan based on the key monitoring point set of the arch section to obtain the monitoring point layout map; (2) According to the monitoring point layout diagram, an automated geometric level is installed in the arch section area to obtain the fixed installation position of the instrument, and the stability of the fixed installation position of the instrument is tested to obtain the stability data of the instrument base; (3) Based on the stability data of the instrument base, set the automatic monitoring parameters of the geometric level, obtain the monitoring frequency setting value, and compile an automatic measurement program according to the monitoring frequency setting value to obtain the instrument control instructions; (4) According to the instrument control instructions, the geometric level automatic measurement system is started to obtain the continuous observation raw data, and the continuous observation raw data is transmitted in real time to obtain a remote database; (5) The data in the remote database is cleaned by using a data cleaning algorithm to identify and remove outliers, thereby obtaining a valid observation data sequence. Based on the valid observation data sequence, the relative elevation change of each monitoring point is calculated to obtain continuous subsidence data.

[0036] Specifically, the monitoring points in the arch section area of ​​the fixed monitoring point group are screened to obtain the key monitoring point set of the arch section. The screening process takes into account the structural characteristics and stress conditions of the arch section, and focuses on selecting monitoring points at key positions such as the arch top, arch foot and arch waist. The screening criteria include the representativeness, stability and reliability of the points, and usually selects points with large deformation or obvious change trends in the previous monitoring. Based on the key monitoring point set of the arch section obtained by screening, an automatic monitoring plan is formulated. The plan formulation takes into account factors such as monitoring frequency, accuracy requirements and data transmission methods, while taking into account monitoring costs and operational feasibility. By optimizing the layout, a monitoring point layout map is obtained, and the location, number and relative relationship of each monitoring point with the automated geometric level are marked in detail. According to the monitoring point layout map, an automated geometric level is installed in the arch section area. The selection of the installation location needs to comprehensively consider factors such as the measurement line of sight, instrument stability and power supply conditions. It is usually selected to be installed in the middle of the arch section or in the stable area of ​​the side wall to ensure that the instrument can cover all key monitoring points. After the installation is completed, the fixed installation position of the instrument is obtained. The stability test of the fixed installation position of the instrument includes short-term stability test and long-term stability monitoring. The short-term stability test evaluates the repeatability and accuracy of the instrument by repeatedly observing the fixed target, while the long-term stability monitoring is evaluated by regularly checking the horizontal and vertical position changes of the instrument. Through these tests, the stability data of the instrument base is obtained, which reflects the reliability of the instrument installation position and the credibility of the observation data.

[0037] Based on the stability data of the instrument base, the automatic monitoring parameters of the geometric level are set. The parameter settings include observation frequency, accuracy requirements, temperature compensation, etc. The setting of the observation frequency takes into account the deformation rate of the tunnel and the monitoring requirements. It is usually set to once an hour under normal circumstances, and can be increased to once every 10 minutes under special circumstances. The accuracy requirement is usually set to 0.1mm to meet the needs of high-precision monitoring. The temperature compensation parameters are set according to the temperature influencing factors in the stability data of the instrument base to eliminate the influence of temperature changes on the measurement results. Through these parameter settings, the monitoring frequency setting value is obtained. According to the monitoring frequency setting value, the automatic measurement program is compiled. The program compilation takes into account the observation sequence, data storage format and abnormal situation processing, and finally obtains the instrument control instructions. According to the instrument control instructions, the geometric level automatic measurement system is started. After the system is started, the key monitoring points are automatically observed according to the preset frequency and sequence to obtain the continuous observation raw data. These raw data include the reading, observation time, temperature and other information of each monitoring point. Real-time data transmission of the continuous observation raw data is usually carried out by wireless transmission technology, such as 4G network or dedicated wireless network, to transmit the data to the remote server in real time to form a remote database. Real-time transmission ensures the timeliness and security of data, facilitating real-time monitoring and early warning.

[0038] The data in the remote database are identified and removed by using a data cleaning algorithm. The data cleaning process uses a variety of methods, including statistical analysis and time series analysis. Statistical analysis uses the statistical characteristics of data, such as mean and standard deviation, to identify data points that deviate from the normal range. Time series analysis identifies data with sudden or abnormal changes by comparing data changes at adjacent time points. Through these methods, abnormal data caused by instrument failure, external interference and other factors are eliminated to obtain a valid observation data sequence. Based on the valid observation data sequence, the relative elevation changes of each monitoring point are calculated. The calculation process takes into account the stability of the benchmark point and adopts the relative elevation method, that is, taking a certain stable point as the benchmark, the elevation changes of other points relative to this point are calculated. Through this method, continuous settlement data are obtained, which reflect the settlement changes of each monitoring point in the arch section over time.

[0039] Taking a 1.5-kilometer-long multi-arch tunnel as an example, a total of 30 fixed monitoring points were set up in the multi-arch section area, of which 15 key monitoring points were selected through screening for automatic monitoring. The automated geometric level was installed in a stable area on the right side of the middle of the multi-arch section, with an installation height of 1.8 meters. The stability test of the instrument base showed that the maximum deviation within 24 hours did not exceed 0.05mm. Based on this stability result, the monitoring frequency was set to once every 30 minutes, and the temperature compensation parameter was 0.002mm / °C. After the automatic measurement system was started, 720 sets of original observation data were generated every day. Through the data cleaning algorithm, about 1% of abnormal data were eliminated on average every day. The data analysis results show that the maximum settlement of a monitoring point in the middle of the multi-arch section reached 3.2mm in a week, with a change rate of 0.5mm / day.

[0040] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) The absolute subsidence data, spatial position change data and continuous subsidence data of each monitoring point are aligned in time series to obtain a synchronized data set, and the synchronized data set is scaled through data standardization to obtain standardized monitoring data; (2) Establishing the observation equation based on the standardized monitoring data to obtain the initial observation matrix, and assigning weights to different types of data in the initial observation matrix through the weight allocation algorithm to obtain the weighted observation matrix; (3) The weighted observation matrix is ​​estimated by the least squares adjustment algorithm to obtain the estimated value of the comprehensive subsidence after adjustment. The accuracy of the estimated value of the comprehensive subsidence is evaluated by residual analysis to obtain the reliability index of the fusion result. (4) Based on the reliability index of the fusion results, the time series analysis of the estimated comprehensive subsidence after adjustment is carried out to obtain the subsidence trend model. The subsidence trend model is then predicted and calculated using the trend extrapolation algorithm to obtain the future subsidence prediction results. (5) Based on the predicted results of future subsidence and the safety threshold of the tunnel structure, risk levels are divided to obtain risk assessment results for each section of the tunnel. Based on the risk assessment results for each section of the tunnel, targeted tunnel maintenance strategy recommendations are formulated to obtain overall subsidence trend assessment results and tunnel maintenance strategy recommendations.

[0041] Specifically, the absolute subsidence data, spatial position change data and continuous subsidence data of each monitoring point are aligned in time series. This step uses the interpolation method to unify the data of different frequencies and different time points into the same time series to obtain a synchronized data set. Then, the synchronized data set is scaled through data standardization. The observation equation is established based on the standardized monitoring data to obtain the initial observation matrix. The general form of the observation equation is: ; Among them, L is the observation value vector, A is the coefficient matrix, X is the unknown vector, and V is the error vector. In this method, L contains the standardized absolute subsidence, spatial position change and continuous subsidence data. The weight distribution algorithm is used to assign weights to different types of data in the initial observation matrix to obtain a weighted observation matrix. The weight distribution takes into account the accuracy and reliability of various types of data, and usually adopts the inverse variance weight method. The weight calculation formula is: ; in, is the weight of the i-th category data, is the standard deviation of this type of data.

[0042] The least squares adjustment algorithm is applied to the weighted observation matrix for sinking estimation. The core idea of ​​the least squares adjustment is to minimize the sum of squares of the weighted residuals of the observations. The basic equation for the adjustment calculation is: ; Among them, P is the weight matrix, is the transposed matrix of A. By solving this equation, the estimated value of the comprehensive subsidence after adjustment is obtained. Then, the accuracy of the estimated value of the comprehensive subsidence is evaluated through residual analysis. The calculation formula of the residual Q is: ; By analyzing the size and distribution of the residuals, calculating the unit weighted mean error and the accuracy index of each parameter, the reliability index of the fusion result is obtained. Based on the reliability index of the fusion result, the time series analysis of the estimated value of the comprehensive subsidence after adjustment is carried out to obtain the subsidence trend model. The time series analysis adopts the ARIMA (autoregressive integrated moving average) model, and the general form of the model is: ; in, and are the autoregressive and moving average polynomials, B is the lag operator, d is the difference order, is a time series, is a white noise sequence. The subsidence trend model is predicted and calculated by the trend extrapolation algorithm to obtain the future subsidence prediction result. According to the future subsidence prediction result, combined with the tunnel structure safety threshold, the risk level is divided. The risk level division usually adopts the fuzzy comprehensive evaluation method to establish the evaluation matrix: ; in, It represents the membership of the i-th evaluation index to the j-th risk level, m is the number of evaluation indicators, and n is the number of risk levels. The risk assessment results of each section of the tunnel are obtained by calculation, and targeted tunnel maintenance strategy recommendations are formulated based on these results, and finally the overall sinking trend assessment results and tunnel maintenance strategy recommendations are obtained.

[0043] Taking a 2-kilometer-long multi-arch tunnel as an example, a total of 100 monitoring points were set up. Through time series alignment, the continuous subsidence data once an hour, the absolute subsidence data once a day, and the spatial position change data once a week are unified into a daily time series. After standardization, the mean of the absolute subsidence data is 0 and the standard deviation is 1; the mean of the spatial position change data is 0 and the standard deviation is 0.8; the mean of the continuous subsidence data is 0 and the standard deviation is 1.2. The weight distribution results show that the weight of the absolute subsidence data is 0.4, the weight of the spatial position change data is 0.3, and the weight of the continuous subsidence data is 0.3. After the least squares adjustment, the unit weighted mean error of the comprehensive subsidence estimate is ±0.5mm. The time series analysis uses the ARIMA (2,1,1) model, and the prediction results show that the maximum subsidence will reach 22mm in the next three months. According to the prediction results and the safety threshold (25mm), the tunnel is divided into three risk level areas: 1,500 meters for low-risk areas, 400 meters for medium-risk areas, and 100 meters for high-risk areas. For high-risk areas, emergency maintenance measures such as reinforcement grouting are recommended; for medium-risk areas, it is recommended to increase the monitoring frequency and perform preventive maintenance; for low-risk areas, regular monitoring and maintenance are sufficient.

[0044] The embodiment of the present invention also provides a system for measuring the subsidence of a double-arch tunnel vault. Figure 2 As shown, the arch tunnel crown sinking measurement system specifically includes: The layout module 201 is used to layout level points outside and inside the tunnel to obtain a leveling network throughout the tunnel; An installation module 202 is used to install high-precision settlement observation marks at the crown position of the tunnel monitoring section based on the leveling network to obtain a fixed monitoring point group; The measurement module 203 is used to perform periodic high-precision leveling measurement on the fixed monitoring point group based on the leveling measurement network to obtain absolute subsidence data of each monitoring point; A calculation module 204 is used to perform periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; A monitoring module 205 is used to automatically monitor the arch section of the tunnel with a preset frequency using a geometric level based on the fixed monitoring point group to obtain continuous subsidence data; The analysis module 206 is used to perform a fusion analysis on the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data by the least square method to obtain an overall subsidence trend assessment result and a tunnel maintenance strategy recommendation.

[0045] Through the coordinated work of the above modules, by laying out level points outside and inside the tunnel, a leveling network throughout the entire tunnel was established, which significantly improved the accuracy and stability of the measurement. Based on the leveling network, high-precision settlement observation marks were installed at the arch position of the tunnel monitoring section to form a fixed monitoring point group, ensuring the consistency and comparability of long-term monitoring. Periodic high-precision leveling measurements were performed on the fixed monitoring point group to obtain the absolute settlement data of each monitoring point, providing key data for evaluating the overall deformation trend of the tunnel. At the same time, by periodically measuring the three-dimensional coordinates of the fixed monitoring point group with a total station, the spatial position change data was obtained, which can not only monitor the settlement in the vertical direction, but also capture the displacement in the horizontal direction, and fully reflect the deformation state of the tunnel structure. For the key area of ​​the continuous arch section, a geometric level with a preset frequency is used for automatic monitoring to obtain continuous settlement data, realizing high-frequency and real-time monitoring of key areas and improving the response speed to sudden deformation. Finally, various monitoring data were fused and analyzed through the least squares method to obtain the overall sinking trend assessment results and tunnel maintenance strategy recommendations, which fully utilized the complementarity of multi-source data and improved the accuracy and reliability of the assessment results.

[0046] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the embodiments, a person skilled in the art should understand that the specific implementation modes of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for measuring the subsidence of a double-arch tunnel vault, characterized in that: include: Level points are laid out outside and inside the tunnel to obtain a leveling network throughout the tunnel; Based on the leveling network, high-precision settlement observation marks are installed at the arch positions of the tunnel monitoring sections to obtain a fixed monitoring point group; Based on the leveling network, periodic high-precision leveling is performed on the fixed monitoring point group to obtain absolute subsidence data of each monitoring point; Performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; Based on the fixed monitoring point group, the geometric level instrument is automatically monitored at a preset frequency on the continuous arch section area of ​​the tunnel to obtain continuous subsidence data; The absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data are fused and analyzed by the least squares method to obtain an overall subsidence trend assessment result and tunnel maintenance strategy recommendations.

2. The method for measuring the arch subsidence of a multi-arch tunnel according to claim 1, characterized in that: The step of arranging level points outside and inside the tunnel to obtain a leveling network throughout the entire tunnel includes: Performing three-dimensional laser scanning on the terrain around the tunnel to obtain point cloud data of the terrain outside the tunnel, and performing noise reduction processing on the point cloud data of the terrain outside the tunnel to obtain filtered point cloud data of the terrain outside the tunnel; Extracting terrain features from the filtered external terrain point cloud data to obtain key terrain feature points outside the tunnel, and selecting leveling reference points based on the key terrain feature points outside the tunnel to obtain candidate locations of leveling reference points outside the tunnel; Performing three-dimensional laser scanning on the interior of the tunnel to obtain point cloud data of the interior of the tunnel, and performing segmentation processing on the point cloud data of the interior of the tunnel to obtain segmented point cloud data of the interior of the tunnel; Performing section extraction on the segmented point cloud data in the tunnel to obtain a characteristic section inside the tunnel, and performing internal leveling point layout planning based on the characteristic section inside the tunnel to obtain candidate positions of the internal leveling points in the tunnel; The network type of the candidate positions of the external leveling benchmark points of the tunnel and the candidate positions of the internal leveling points of the tunnel are optimized by the least square adjustment algorithm to obtain an optimized leveling point layout scheme, and the leveling points are calibrated on the tunnel entity according to the optimized leveling point layout scheme to obtain entity leveling points; The physical leveling points are subjected to high-precision GPS static measurement to obtain the absolute coordinate data of the leveling points, and the absolute coordinate data of the leveling points are transmitted in elevation through a leveling measuring instrument to obtain a leveling network that runs through the entire tunnel.

3. The method for measuring the arch subsidence of a multi-arch tunnel according to claim 1, characterized in that: The step of installing high-precision settlement observation marks at the crown position of the tunnel monitoring section based on the leveling network to obtain a fixed monitoring point group includes: Performing accuracy assessment on the leveling network to obtain network accuracy assessment results, and determining the tunnel monitoring section spacing based on the network accuracy assessment results to obtain a monitoring section layout plan; Marking the tunnel in sections according to the monitoring section layout plan to obtain tunnel section data, and performing geological parameter analysis on the tunnel section data to obtain geological stability assessment results for each section; Based on the geological stability assessment results of each section, each monitoring section is graded in importance to obtain a monitoring section classification result, and the observation mark density of each section is determined according to the monitoring section classification result to obtain an observation mark layout density plan; Performing a stress analysis on the tunnel vault structure to obtain vault stress distribution data, and determining the specific installation position of a high-precision settlement observation mark based on the vault stress distribution data to obtain the observation mark installation coordinates; According to the observation mark installation coordinates, drilling operations are performed on the tunnel vault to obtain the mark installation hole, and the depth and direction of the mark installation hole are detected to obtain hole position verification data; Based on the hole position verification data, a high-precision settlement observation mark is embedded in the mark installation hole to obtain an initial fixed monitoring point, and a stability test is performed on the initial fixed monitoring point to obtain a fixed monitoring point group.

4. The method for measuring the arch subsidence of a multi-arch tunnel according to claim 1, characterized in that: The step of performing periodic high-precision leveling measurement on the fixed monitoring point group based on the leveling measurement network to obtain absolute subsidence data of each monitoring point includes: Periodically re-measure the leveling network to obtain network stability evaluation data, and select stable leveling benchmark points based on the network stability evaluation data to obtain a measurement reference benchmark; According to the measurement reference datum, a leveling measurement route is formulated to obtain a measurement route map, and instrument sites are arranged based on the measurement route map to obtain an instrument arrangement plan; According to the instrument deployment plan, the fixed monitoring point group is measured back and forth to obtain original observation data, and the original observation data is corrected for temperature and atmospheric pressure to obtain corrected observation data; The corrected observation data is evaluated for accuracy by using the error propagation law to obtain a measurement accuracy evaluation result, and valid observation data is screened based on the measurement accuracy evaluation result to obtain valid leveling measurement data; The effective leveling data are adjusted to obtain the elevation value of each monitoring point, and the elevation change of each monitoring point is calculated by comparing with the initial elevation to obtain the absolute subsidence data of each monitoring point.

5. The method for measuring the arch subsidence of a multi-arch tunnel according to claim 1, characterized in that: The step of performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data includes: Selecting locations with good stability around the tunnel, establishing a total station network, obtaining a station network layout plan, and installing station markers based on the station network layout plan to obtain physical station locations; Perform high-precision GPS static measurement on the physical measuring station to obtain the absolute coordinate data of the measuring station, and establish a local coordinate system of the tunnel through measuring station coordinate conversion to obtain the local coordinates of the measuring station; According to the local coordinates of the measuring station, the total station is placed and leveled to obtain instrument positioning data, and meteorological parameters are collected and input for the instrument positioning data to obtain measurement environment parameters; Based on the measurement environment parameters, the fixed monitoring point group is observed at multiple angles to obtain original observation angle and distance data, and the original observation angle and distance data are corrected for atmospheric and instrument errors to obtain corrected observation data; The corrected observation data are calculated by the spatial forward intersection method to obtain the three-dimensional coordinate values ​​of the monitoring points, and compared and analyzed with the previous measurement results to obtain the spatial position change data.

6. The method for measuring the subsidence of a double-arch tunnel vault according to claim 1, characterized in that: The step of automatically monitoring the continuous arch section of the tunnel with a geometric level at a preset frequency based on the fixed monitoring point group to obtain continuous subsidence data includes: Screening the monitoring points of the arch section area in the fixed monitoring point group to obtain a set of key monitoring points of the arch section, and formulating an automatic monitoring plan based on the set of key monitoring points of the arch section to obtain a monitoring point layout map; According to the monitoring point layout diagram, an automated geometric level is installed in the arch section area to obtain a fixed installation position of the instrument, and stability detection is performed on the fixed installation position of the instrument to obtain stability data of the instrument base; Based on the instrument base stability data, automatic monitoring parameters of the geometric level are set to obtain a monitoring frequency setting value, and an automatic measurement program is compiled according to the monitoring frequency setting value to obtain an instrument control instruction; According to the instrument control instruction, the geometric level automatic measurement system is started to obtain the continuous observation raw data, and the continuous observation raw data is transmitted in real time to obtain a remote database; The data in the remote database is identified and eliminated for outliers through a data cleaning algorithm to obtain a valid observation data sequence, and the relative elevation change of each monitoring point is calculated based on the valid observation data sequence to obtain continuous subsidence data.

7. The method for measuring the subsidence of a double-arch tunnel vault according to claim 6, characterized in that: The step of fusing and analyzing the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data by the least square method to obtain an overall subsidence trend assessment result and a tunnel maintenance strategy recommendation step includes: Performing time series alignment on the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data to obtain a synchronized data set, and performing scale unification on the synchronized data set through data standardization processing to obtain standardized monitoring data; An observation equation is established based on the standardized monitoring data to obtain an initial observation matrix, and weights are assigned to different types of data in the initial observation matrix through a weight distribution algorithm to obtain a weighted observation matrix; The weighted observation matrix is ​​subjected to subsidence estimation by a least squares adjustment algorithm to obtain an estimated value of the comprehensive subsidence after adjustment, and the accuracy of the estimated value of the comprehensive subsidence is evaluated by residual analysis to obtain a reliability index of the fusion result; Based on the reliability index of the fusion result, a time series analysis is performed on the estimated value of the comprehensive subsidence after adjustment to obtain a subsidence trend model, and a prediction calculation is performed on the subsidence trend model through a trend extrapolation algorithm to obtain a future subsidence prediction result; According to the future subsidence prediction results, combined with the tunnel structure safety threshold, risk level classification is carried out to obtain risk assessment results of each section of the tunnel, and targeted tunnel maintenance strategy recommendations are formulated based on the risk assessment results of each section of the tunnel to obtain overall subsidence trend assessment results and tunnel maintenance strategy recommendations.

8. A system for measuring the subsidence of a double-arch tunnel vault, used for executing the method for measuring the subsidence of a double-arch tunnel vault as claimed in any one of claims 1 to 7, characterized in that: include: The layout module is used to layout level points outside and inside the tunnel to obtain a leveling network throughout the tunnel; An installation module is used to install high-precision settlement observation marks at the arch position of the tunnel monitoring section based on the leveling network to obtain a fixed monitoring point group; A measurement module, used to perform periodic high-precision leveling measurement on the fixed monitoring point group based on the leveling measurement network to obtain absolute subsidence data of each monitoring point; A calculation module, used for performing periodic total station three-dimensional coordinate measurement on the fixed monitoring point group to obtain spatial position change data; A monitoring module, for automatically monitoring the continuous arch section of the tunnel with a geometric level at a preset frequency based on the fixed monitoring point group to obtain continuous subsidence data; The analysis module is used to perform a fusion analysis on the absolute subsidence data of each monitoring point, the spatial position change data and the continuous subsidence data by the least square method to obtain an overall subsidence trend assessment result and a tunnel maintenance strategy recommendation.

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