Shield tunnel segment loading test platform data monitoring and analysis method

Abstract

The invention relates to the technical field of tunnel segment data monitoring and analysis, and relates to a shield tunnel segment loading test platform data monitoring and analysis method. According to the method, the position coordinates of the identification points in the segment seam area are captured and decomposed into normal, tangential and rotary displacement components, real-time synchronous quantification of the seam opening amount, the dislocation amount and the torsion angle is achieved, and meanwhile historical test data and a real-time sequence are fused based on the timestamp alignment technology; a segment joint deformation evolution trend chart is predicted through multi-parameter coupling, and a real-time sequence is combined to carry out collaborative judgment to generate a segment joint area deformation danger degree index, so that deformation trend dynamic accurate prediction and danger degree accurate evaluation are realized. And performing correlation analysis on the identified maximum curvature position, the curvature change rate and the deformation danger degree index of the segment joint area, outputting the safety margin of the segment structure, and triggering a multi-stage early warning mechanism, thereby comprehensively evaluating the overall structure safety state of the shield tunnel segment.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel segment data monitoring and analysis, and relates to a method for monitoring and analyzing data of a shield tunnel segment loading test platform. Background Art

[0002] During the construction and operation of shield tunnels, the safety of the segment structure is directly related to the overall stability and service life of the tunnel. With the increasing complexity of urban underground space development, the load environment faced by shield tunnels is becoming increasingly variable, and multi-dimensional structural responses such as segment joint deformation and outer surface curvature change have become key indicators for evaluating the safety performance of segments.

[0003] For example, a method for monitoring and predicting shield segment cracking with the Chinese patent publication number CN117951651A. This method measures the deformation data of shield segments through inclination sensors, considers the geological conditions and construction conditions of shield tunnels, realizes effective prediction of segment deformation and cracking, and uses the XGBoost algorithm to establish and train a segment deformation evaluation model to realize real-time evaluation of shield segment cracking, more accurately reflecting information such as geological conditions and shield machine operation parameters, thereby improving the accuracy and effect of segment cracking prediction.

[0004] For example, a shield-formed tunnel shape data processing system and method with the Chinese patent publication number CN119577922A. The present invention includes the following steps: S1 Collecting and preprocessing data of several cross-sections in a shield-formed tunnel; S2 Calculating the offset of the center of each segment; S3 Continuously measuring and analyzing the deformation trend; S4 Using a linear regression model to predict the change of the offset; S5 Using the trained model to predict the final offset of the segment.

[0005] However, the prior art has the following problems: 1. When monitoring and analyzing segment deformation data, most of the prior art focuses on single-dimensional data processing, such as only analyzing deformation data or geological data separately, lacking comprehensive consideration of the correlation between segment joint area deformation and segment outer surface deformation, and unable to comprehensively evaluate the overall structural safety state of shield tunnel segments.

[0006] 2. The prior art analyzes the deformation trend by collecting cross-section data and measuring the offset of the segment center, focusing on the change of the segment center position, and the monitoring of the detailed deformation information in the segment joint area is not precise enough, making it difficult to accurately evaluate the structural safety risk at the joint and unable to comprehensively reflect the complex deformation situation in the segment joint area. Summary of the Invention

[0007] The present invention aims to provide a method for monitoring and analyzing data of a shield tunnel segment loading test platform to solve the problems in the prior art such as incomplete monitoring information, inaccurate monitoring of segment joint area deformation, and lack of correlation analysis between segment joints and outer surface deformation.

[0008] The technical solution adopted by the present invention to solve its technical problems is as follows: A method for monitoring and analyzing data of a shield tunnel segment loading test platform, including:

[0009] S1. Operate the loading device of the test platform to apply physical loads to the outer surface of the shield tunnel segment to be tested according to a preset loading scheme, and simultaneously construct a three-dimensional point cloud model of the segment through three-dimensional laser scanning.

[0010] S2. Based on the three-dimensional point cloud model of the segment, real-time capture the position coordinates of the pre-laid marking points in the segment joint area, and obtain the real-time sequences of the joint opening amount, misalignment amount, and torsion angle in the segment joint area through spatial coordinate transformation.

[0011] S3. Correlate the historical test data of the shield tunnel segment joints with the real-time sequences, predict the deformation evolution trend diagram of the segment joints through multi-parameter coupling, and perform collaborative determination in combination with the real-time sequences to generate the deformation risk degree index of the segment joint area.

[0012] S4. Extract the curvature values of each sampling point on the outer surface of the segment, identify the position of the maximum curvature and the curvature change rate, and perform correlation analysis with the deformation risk degree index of the segment joint area to output the structural safety margin of the segment.

[0013] S5. When the structural safety margin of the segment is less than the preset structural safety threshold, trigger a multi-level warning mechanism.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] (1) While applying physical loads through the loading device of the test platform, the present invention uses three-dimensional laser scanning to construct a three-dimensional point cloud model of the segment, symmetrically arranges marking points in the joint area, real-time captures the coordinates of the marking points and decomposes them into normal, tangential, and rotational displacement components, realizing real-time synchronous quantification of the joint opening amount, misalignment amount, and torsion angle, and comprehensively capturing the three-dimensional deformation characteristics under the action of loads.

[0016] (2) The present invention uses the timestamp alignment technology to fuse historical test data with real-time sequences, screens the most similar historical sequences based on the morphological similarity calculated by the Euclidean distance, constructs the deformation evolution trend diagram and outputs the current predicted value, and generates the deformation risk degree index of the segment joint area by fusing multi-parameter deviation values in combination with the preset weight coefficient, thereby realizing the quantitative assessment of the structural safety risk of the segment joints, and realizing the dynamic and accurate prediction of the deformation trend and the accurate assessment of the risk degree.

[0017] (3) By extracting the curvature values of each sampling point on the outer surface of the segment, identifying the position of the maximum curvature and the curvature change rate, and performing a correlation analysis between them and the deformation risk degree index of the segment joint area, the structural safety margin of the segment is output, realizing the collaborative analysis of the deformation on the outer surface of the segment and the risk in the joint area, so as to comprehensively evaluate the overall structural safety state of the shield tunnel segment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic flow chart of the method steps of the present invention.

[0020] Figure 2 It is a schematic flow chart of the step content of S2 in the present invention.

[0021] Figure 3 It is a schematic flow chart of the step content of S3 in the present invention.

[0022] Figure 4 It is a schematic diagram for determining the analysis steps of the structural safety margin of the segment in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] Now, various exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps set forth in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0024] The following description of at least one exemplary embodiment is merely illustrative in nature and in no way serves as a limitation on the present invention, its application, or its use. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and devices should be regarded as part of the specification.

[0025] In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0026] The present invention relates to the technical field of tunnel segment data monitoring and analysis, and relates to a method for monitoring and analyzing data of a shield tunnel segment loading test platform. The present invention realizes real-time synchronous quantification of the joint opening amount, misalignment amount and torsion angle by capturing the position coordinates of the identification points in the segment joint area and decomposing them into normal, tangential and rotational displacement components. At the same time, based on the timestamp alignment technology, historical test data and real-time sequences are fused, and the deformation evolution trend diagram of the segment joint is predicted by multi-parameter coupling. Combining with the real-time sequence, a collaborative judgment is made to generate the deformation danger degree index of the segment joint area, so as to realize dynamic and accurate prediction of the deformation trend and accurate assessment of the danger degree. The maximum curvature position and curvature change rate identified are correlated with the deformation danger degree index of the segment joint area, and the structural safety margin of the segment is output, triggering a multi-level early warning mechanism, so as to comprehensively evaluate the overall structural safety state of the shield tunnel segment.

[0027] Please refer to Figure 1 As shown, the present invention provides a method for monitoring and analyzing data of a shield tunnel segment loading test platform, including: S1. Operate the loading device of the test platform to apply physical loads to the outer surface of the shield tunnel segment to be tested according to a preset loading scheme, and simultaneously construct a three-dimensional point cloud model of the segment through three-dimensional laser scanning.

[0028] It should be noted that the preset loading scheme is carefully formulated by professionals according to the design parameters of the shield tunnel segment, actual working condition simulation and relevant mechanical property test requirements. It details key elements such as the loading sequence, loading rate, loading magnitude and loading duration of the load. For example, the load is applied in a gradually increasing manner from low to high, and each load level lasts for a certain time to ensure that the segment has sufficient response. At the same time, the maximum loading limit is determined according to the design bearing capacity of the segment, aiming to truly simulate various physical load conditions that the shield tunnel segment may encounter during actual use, providing a scientific and rigorous loading basis for subsequent construction of the three-dimensional point cloud model of the segment through three-dimensional laser scanning and in-depth analysis based on this, so as to accurately evaluate the mechanical properties and structural stability of the segment.

[0029] The three-dimensional laser scanning consists of multiple groups of three-dimensional laser scanners. Each three-dimensional laser scanner is distributed in a layered and staggered manner along the axial and circumferential directions of the segment, and the coverage range of each three-dimensional laser scanner forms a monitoring overlap area with its adjacent scanner. The three-dimensional laser scanners are synchronously started to scan the segment with extremely high precision, quickly capturing the fine features and changes of the segment surface and its structure, and then constructing an accurate and detailed three-dimensional point cloud model of the segment, providing a rich and accurate data basis for subsequent in-depth analysis of the deformation, stress distribution, etc. of the segment under the action of the load, and helping to comprehensively evaluate the performance and quality of the shield tunnel segment.

[0030] S2. Based on the 3D point cloud model of the segment, the position coordinates of the pre - arranged identification points in the segment joint area are captured in real - time, and the real - time sequences of the joint opening amount, misalignment amount and torsion angle in the segment joint area are obtained through spatial coordinate transformation.

[0031] As Figure 2 shown, the steps of S2 are as follows: S21. Uniformly arrange identification points on both sides of the joint corresponding to the segment joint area, and capture the position coordinates of each identification point in real - time.

[0032] S22. Compare the position coordinates of each captured identification point with the initial 3D coordinates to obtain the 3D displacement vector of each identification point. The initial 3D coordinates of the identification point are the 3D coordinates when the loading device of the test platform is not loaded.

[0033] S23. Decompose the 3D displacement vector of each identification point into normal displacement, tangential displacement and rotational displacement components through spatial coordinate transformation, and obtain the real - time joint opening amount, misalignment amount and torsion angle in the segment joint area based on the normal displacement, tangential displacement and rotational displacement components.

[0034] S24. According to the real - time joint opening amount, misalignment amount and torsion angle in the segment joint area,

[0035] construct real - time sequences of the joint opening amount, misalignment amount and torsion angle. The real - time sequence is composed of the joint opening amount, misalignment amount and torsion angle at all captured timestamps during the loading process of the test platform.

[0036] It should be noted that when capturing the position coordinates of each identification point, a local coordinate system needs to be established with the joint surface as the reference. The Z - axis is the direction of the normal vector of the joint surface, the X - axis is the tangential direction of the segment ring, and the Y - axis is the longitudinal tangential direction of the segment, satisfying the orthogonal relationship of X×Y = Z.

[0037] The normal displacement refers to the displacement component of the identification point in the direction perpendicular to the joint plane. When the loading device applies physical loads to the shield tunnel segments, the segment joint area will deform, resulting in a displacement difference of the identification point in the normal direction, which in turn reflects the relative change of the joint in the normal direction, that is, the joint opening amount. For example, the 3D displacement vector of a certain identification point is , and the normal displacement component is obtained through spatial coordinate transformation. is the unit normal vector of the joint surface, then the joint opening amount is the absolute value of the normal displacement component, , and the maximum joint opening amount is selected from the joint opening amounts of each identification point as the real - time joint opening amount in the segment joint area.

[0038] The tangential displacement is the displacement component of the marked point in the joint plane and perpendicular to the joint direction. Under the action of the load, the marked points on both sides of the segment joint will have relative displacement along the tangential direction, and this relative displacement is the dislocation amount. The dislocation amount includes two orthogonal components: the circumferential dislocation amount and the longitudinal dislocation amount. If the dislocation amount is , where is the circumferential dislocation amount, , is the circumferential tangential unit vector, is the longitudinal dislocation amount, , is the longitudinal tangential unit vector, and the maximum dislocation amount is selected from the dislocation amounts of each marked point as the real-time dislocation amount in the segment joint area.

[0039] The rotational displacement is the rotation of the marked point around a certain axis. During the loading process, torsional deformation may occur in the segment joint area, resulting in the rotation of the marked point around a certain axis, usually the axis of the joint or other key axes. By analyzing the rotational displacement of the marked point, the torsional angle at the joint can be calculated. If the torsional angle is , and the maximum torsional angle is selected from the torsional angles of each marked point as the real-time torsional angle in the segment joint area.

[0040] In the present invention, while applying physical loads through the operation test platform loading device, a three-dimensional point cloud model of the segment is constructed by using three-dimensional laser scanning, and marked points are symmetrically arranged in the joint area. The coordinates of the marked points are captured in real time and decomposed into normal, tangential, and rotational displacement components, so as to realize the real-time synchronous quantification of the joint opening amount, dislocation amount, and torsional angle, comprehensively capture the three-dimensional deformation characteristics under the action of the load, improve the accuracy of the structural safety risk assessment at the segment joint, and provide detailed and accurate data support for the subsequent prediction of the deformation evolution trend and the assessment of the danger level.

[0041] S3. Correlate the historical test data of the segment joint of the shield tunnel with the real-time sequence, predict the deformation evolution trend diagram of the segment joint through multi-parameter coupling, and perform collaborative determination in combination with the real-time sequence to generate the deformation danger level index of the segment joint area.

[0042] As Figure 3 shown, the specific steps of the S3 are as follows: S31. Obtain the historical sequences of the joint opening amount, dislocation amount, and torsional angle of each test in the historical test data of the segment joint of the shield tunnel, align the time stamps of the historical sequence and the real-time sequence, predict the deformation evolution trend diagram of the segment joint through coupling analysis, and output the current predicted values of the joint opening amount, dislocation amount, and torsional angle.

[0043] S32. Co-judge the current predicted value with the real-time joint opening amount, dislocation amount, and torsion angle, and generate the deformation risk degree index of the segment joint area by fusing the opening amount deviation, dislocation amount deviation, and torsion angle deviation based on the preset weight coefficients.

[0044] Further, the output method of the current predicted values of the joint opening amount, dislocation amount, and torsion angle is as follows: S311. Obtain the current loading duration according to the real-time sequence, intercept the historical sequence corresponding to the current loading duration from the historical sequences of each test, align its time stamps with the real-time sequence, and obtain the historical synchronous time sequence and the real-time synchronous time sequence respectively.

[0045] S312. Perform normalization processing on the historical synchronous time sequences and the real-time synchronous time sequences of each test, calculate the difference degree between the real-time synchronous time sequence and the historical synchronous time sequences of each test at each time point by using the Euclidean distance for the normalization processing results, and judge the morphological similarity between the real-time synchronous time sequence and the historical synchronous time sequences of each test according to the difference degree.

[0046] S313. Screen the historical sequences of the joint opening amount, dislocation amount, and torsion angle corresponding to the test with the highest morphological similarity, construct the deformation evolution trend diagram of the segment joint according to the screened historical sequences, and select the current predicted values of the joint opening amount, dislocation amount, and torsion angle corresponding to the real-time.

[0047] In a specific embodiment, the normalization processing can be the minimum-maximum normalization processing method, which is a prior art and will not be elaborated here.

[0048] The difference degree between the real-time synchronous time sequence and the historical synchronous time sequences of each test at each time point is , are respectively the joint opening amount, dislocation amount, and torsion angle at the time point in the real-time synchronous time sequence, are respectively the joint opening amount, dislocation amount, and torsion angle at the time point in the historical synchronous time sequence, .

[0049] The morphological similarity between the real-time synchronous time sequence and the historical synchronous time sequences of each test is , where m is the total number of time points.

[0050] It should be noted that the method for generating the deformation risk degree index of the segment joint area is as follows: Compare and analyze the real-time joint opening amount, dislocation amount, and torsion angle with the current predicted values of the joint opening amount, dislocation amount, and torsion angle respectively, calculate the deviation value between the real-time value and the current predicted value of the joint opening amount, the deviation value between the real-time value and the current predicted value of the dislocation amount, and the deviation value between the real-time value and the current predicted value of the torsion angle. After normalizing the joint opening amount deviation value, dislocation amount deviation value, and torsion angle deviation value, perform weighted summation based on the preset weight coefficients to obtain the deformation risk degree index of the segment joint area.

[0051] The preset weight coefficients are set according to the hazard levels of each deformation parameter in the shield tunnel engineering specifications. For example, the weight of the joint opening amount is greater than the weight of the dislocation amount, and the weight of the dislocation amount is greater than the weight of the torsion angle. Since the joint opening amount directly affects the waterproof performance and overall stability of the tunnel, it has the largest weight; the dislocation amount has a greater impact on driving safety and local structural stress, with the second largest weight; the impact of the torsion angle is relatively small, with the lowest weight. For example, the weight of the joint opening amount can be , the weight of the dislocation amount can be , and the weight of the torsion angle can be .

[0052] The method for normalizing the joint opening amount deviation value, dislocation amount deviation value, and torsion angle deviation value can all be the ratio of the deviation value to the current predicted value.

[0053] The present invention fuses historical test data and real-time sequences through timestamp alignment technology, screens the most similar historical sequences based on the calculation of morphological similarity using the Euclidean distance, constructs a deformation evolution trend graph and outputs the current predicted value, and combines preset weight coefficients to fuse multi-parameter deviation values to generate the deformation risk degree index of the segment joint area, thereby realizing the quantitative assessment of the structural safety risk of the segment joint, and realizing the dynamic and accurate prediction of the deformation trend and the accurate assessment of the risk degree.

[0054] S4. Extract the curvature values of each sampling point on the outer surface of the segment, identify the position of the maximum curvature and the curvature change rate, perform a correlation analysis with the deformation risk degree index of the segment joint area, and output the structural safety margin of the segment.

[0055] It should be noted that the specific steps of S4 are as follows: Uniformly sample the outer surface of the segment three-dimensional point cloud model to select each sampling point, search for all the nearest neighbor points in the corresponding neighborhood of each sampling point, construct the covariance matrix of each sampling point, perform eigenvalue analysis on the covariance matrix to obtain the curvature value of each sampling point, screen the sampling point corresponding to the maximum curvature value from the curvature values of each sampling point as the maximum curvature position, calculate the curvature change rate of adjacent time points at the maximum curvature position, perform correlation analysis on the maximum curvature value, the curvature change rate and the deformation risk degree index of the segment joint area, and output the structural safety margin of the segment.

[0056] In a specific embodiment, the curvature change rate of adjacent time points at the maximum curvature position is the ratio of the curvature difference between adjacent time points at the maximum curvature position to the time interval between adjacent time points.

[0057] Further, the analysis method of the curvature value of each sampling point is as follows: Construct a neighborhood point coordinate set according to all the nearest neighbor points in the corresponding neighborhood of each sampling point, perform average coordinate analysis on the neighborhood point coordinate set to obtain the mean coordinate of the neighborhood points, calculate the covariance matrix according to the coordinates of all the neighborhood points in the neighborhood point coordinate set and the corresponding mean coordinate of the neighborhood points, perform eigenvalue decomposition on the calculated covariance matrix to obtain the first principal curvature and the second principal curvature, and take the mean of the first principal curvature and the second principal curvature as the curvature value.

[0058] The first principal curvature and the second principal curvature are respectively the eigenvalue ranked first and the eigenvalue ranked second in the eigenvalues of the covariance matrix. The covariance matrix and the eigenvalue decomposition process of the covariance matrix are both prior arts.

[0059] As Figure 4 shown, the specific method of the structural safety margin of the segment is as follows: Perform deviation degree analysis on the maximum curvature value and the curvature change rate respectively with the design limit curvature of the segment structure and the set curvature change rate threshold to obtain the maximum curvature value deviation degree and the curvature change rate deviation degree, and perform linear fusion analysis on the maximum curvature value deviation degree and the curvature change rate deviation degree to obtain the deformation risk degree index of the outer surface of the segment.

[0060] In a specific embodiment, the analysis process of the maximum curvature value deviation degree is as follows: Obtain the absolute difference between the maximum curvature value and the design limit curvature of the segment structure, and take the ratio of the absolute difference to the design limit curvature as the maximum curvature value deviation degree. Similarly, the curvature change rate deviation degree is obtained through the analysis method of the maximum curvature value deviation degree.

[0061] The linear fusion analysis method of the deformation risk degree index on the outer surface of the segment is to retrieve the historical data of the maximum curvature value deviation and the curvature change rate deviation at different positions on the outer surface of the segment from the historical tunnel segment detection records, construct a linear regression equation with the maximum curvature value deviation and the curvature change rate deviation as independent variables and the deformation risk degree index on the outer surface of the segment as the dependent variable, solve the constructed linear regression equation by the least square method according to the retrieved historical data, obtain the regression coefficients and the intercept term of the maximum curvature value deviation and the curvature change rate deviation, thereby construct a new linear regression equation, and substitute the maximum curvature value deviation and the curvature change rate deviation into the new linear regression equation to obtain the deformation risk degree index on the outer surface of the segment.

[0062] The Pearson correlation coefficient is used to determine the correlation between the deformation risk degree index on the outer surface of the segment and the deformation risk degree index in the segment joint area. When the determined correlation is relevant, the comprehensive deformation risk degree index is analyzed collaboratively according to the deformation risk degree index on the outer surface of the segment and the deformation risk degree index in the segment joint area. When the determined correlation is irrelevant, the maximum value of the deformation risk degree index on the outer surface of the segment and the deformation risk degree index in the segment joint area is used as the comprehensive deformation risk degree index, and the comprehensive deformation risk degree index is compared and analyzed with the set comprehensive critical index to generate the segment structure safety margin. Among them, when the Pearson correlation coefficient is less than 0.3 and greater than 0, the correlation is irrelevant. When the Pearson correlation coefficient is greater than 0.3 and less than 1, the correlation is relevant.

[0063] In a specific embodiment, the formula for generating the segment structure safety margin can be , where is the segment structure safety margin, is the comprehensive deformation risk degree index, is the set comprehensive critical index, which is set based on the failure cases of similar tunnels or the warning thresholds in the health monitoring historical database.

[0064] The collaborative analysis process of the comprehensive deformation risk degree index is as follows: Multiply and accumulate the deformation risk degree index on the outer surface of the segment and the deformation risk degree index in the segment joint area with the corresponding weight coefficients to obtain the comprehensive deformation risk degree index. Among them, the weights of the segment joint area such as bolt connections or circumferential joints are usually higher because their deformation is likely to cause chain failures; the weight of the concrete body on the outer surface of the segment is relatively lower. In a specific embodiment, the weight of the deformation risk degree index in the segment joint area can be set to 0.6, and the weight of the deformation risk degree index on the outer surface of the segment can be set to 0.4.

[0065] The present invention extracts the curvature values of each sampling point on the outer surface of the segment, identifies the position of the maximum curvature and the curvature change rate, performs a correlation analysis with the deformation risk degree index of the segment joint area, outputs the structural safety margin of the segment, realizes the collaborative analysis of the deformation on the outer surface of the segment and the risk in the joint area, and thus comprehensively evaluates the overall structural safety state of the shield tunnel segment.

[0066] S5. When the structural safety margin of the segment is less than the preset structural safety threshold, a multi-level warning mechanism is triggered.

[0067] It should be noted that the specific steps of triggering the multi-level warning mechanism are as follows: when the structural safety margin of the segment is less than the preset structural safety margin threshold, obtain the deviation value of the structural safety margin of the segment, divide the warning levels according to the deviation value of the structural safety margin of the segment, and trigger the control instruction of the alarm signal set corresponding to the warning level to control the loading device of the test platform to adjust the preset loading scheme. The deviation value of the structural safety margin of the segment is the difference between the preset structural safety margin threshold and the structural safety margin of the segment.

[0068] The multi-level warning mechanism established by the present invention can trigger corresponding-level warnings according to different degrees of safety margins, can more accurately reflect the safety risk degree of the segment structure, timely remind the operator to take corresponding measures, improve the safety and reliability of the shield tunnel segment loading test, and provide more powerful safety guarantees for the construction and operation of tunnel projects.

[0069] The above formulas are all dimensionless and take their numerical values for calculation. The formula is a formula obtained by collecting a large amount of data for software simulation to get the closest to the real situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0070] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0071] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0072] In addition, in each embodiment of the present application, the functional modules can be integrated in a processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0073] As described above, it is only the specific implementation manner of the present application. However, the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claimed rights.

[0074] Finally, the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for monitoring and analyzing data of a segment loading test platform for shield tunnels, characterized in that, Including: S1. The loading device of the operation test platform applies physical loads to the outer surface of the shield tunnel segment to be tested according to a preset loading scheme, and simultaneously constructs a three-dimensional point cloud model of the segment through three-dimensional laser scanning; S2. Based on the three-dimensional point cloud model of the segment, the position coordinates of the pre-arranged identification points in the segment joint area are captured in real time, and the real-time sequences of the joint opening amount, dislocation amount, and torsion angle in the segment joint area are obtained through spatial coordinate transformation; S3. Correlate the historical test data of the shield tunnel segment joints with the real-time sequences, predict the deformation evolution trend diagram of the segment joints through multi-parameter coupling, and conduct collaborative judgment in combination with the real-time sequences to generate the deformation risk degree index of the segment joint area; S4. Extract the curvature values of each sampling point on the outer surface of the segment, identify the position of the maximum curvature and the curvature change rate, and conduct correlation analysis with the deformation risk degree index of the segment joint area to output the structural safety margin of the segment; S5. When the structural safety margin of the segment is less than the preset structural safety threshold, trigger a multi-level warning mechanism.

2. The data monitoring and analysis method of a shield tunnel segment loading test platform according to claim 1, wherein: The steps of S2 are as follows: S21. Uniformly arrange identification points on both sides of the corresponding joint in the segment joint area, and capture the position coordinates of each identification point in real time; S22. Compare the position coordinates of each identification point captured in real time with the initial three-dimensional coordinates to obtain the three-dimensional displacement vector of each identification point; S23. Decompose the three-dimensional displacement vector of each identification point into normal displacement, tangential displacement, and rotational displacement components through spatial coordinate transformation, and obtain the real-time joint opening amount, dislocation amount, and torsion angle in the segment joint area based on the normal displacement, tangential displacement, and rotational displacement components; S24. According to the real-time joint opening amount, dislocation amount, and torsion angle in the segment joint area, Construct a real-time sequence of the joint opening amount, dislocation amount, and torsion angle.

3. A data monitoring and analysis method for a shield tunnel segment loading test platform according to claim 1, characterized in that: The specific steps of S3 are as follows: Obtain the historical sequences of the joint opening amount, dislocation amount, and torsion angle of each test in the historical test data of the shield tunnel segment joints, align the time stamps of the historical sequences with the real-time sequences, predict the deformation evolution trend diagram of the segment joints through coupling analysis, and output the current predicted values of the joint opening amount, dislocation amount, and torsion angle; Conduct collaborative judgment on the current predicted values and the real-time joint opening amount, dislocation amount, and torsion angle, and generate the deformation risk degree index of the segment joint area based on the preset weight coefficients to fuse the opening amount deviation, dislocation amount deviation, and torsion angle deviation.

4. A method for monitoring and analyzing data of a shield tunnel segment loading test platform according to claim 3, characterized in that: The output method of the current predicted values of the joint opening amount, dislocation amount, and torsion angle is: Obtain the current loading duration according to the real-time sequence, intercept the historical sequence corresponding to the current loading duration from the historical sequences of each test, align its time stamp with the real-time sequence, and respectively obtain the historical synchronous time sequence and the real-time synchronous time sequence; Normalize the historical synchronous time sequences and real-time synchronous time sequences of each test, calculate the difference degree between the real-time synchronous time sequence and the historical synchronous time sequences of each test at each time point by using the Euclidean distance for the normalized processing results, and judge the morphological similarity between the real-time synchronous time sequence and the historical synchronous time sequences of each test according to the difference degree; Screen the historical sequences of the joint opening amount, misalignment amount, and torsion angle corresponding to the test with the highest morphological similarity. Based on the screened historical sequences, construct a diagram showing the evolution trend of the segment joint deformation, and select the current predicted values of the joint opening amount, misalignment amount, and torsion angle corresponding to the real-time time from it.

5. A method for monitoring and analyzing data of a segment loading test platform for shield tunnels according to claim 3, characterized in that: The generation method of the deformation danger degree index of the segment joint area is as follows: Compare and analyze the real-time joint opening amount, misalignment amount, and torsion angle with their current predicted values respectively, calculate the deviation value between the real-time value and the current predicted value of the joint opening amount, the deviation value between the real-time value and the current predicted value of the misalignment amount, and the deviation value between the real-time value and the current predicted value of the torsion angle. After normalizing the joint opening amount deviation value, misalignment amount deviation value, and torsion angle deviation value, perform weighted summation based on the preset weight coefficient to obtain the deformation danger degree index of the segment joint area.

6. A method for monitoring and analyzing data of a segment loading test platform for shield tunnels according to claim 1, characterized in that: The specific steps of S4 are as follows: Uniformly sample the outer surface of the segment in the 3D point cloud model of the segment to select each sampling point; Search for all the nearest neighbor points in the corresponding neighborhood of each sampling point and construct the covariance matrix of each sampling point; Perform eigenanalysis on the covariance matrix to obtain the curvature value of each sampling point; Select the sampling point corresponding to the maximum curvature value from the curvature values of each sampling point as the maximum curvature position, and calculate the curvature change rate of the adjacent time points of the maximum curvature position; Perform correlation analysis on the maximum curvature value, curvature change rate, and the deformation danger degree index of the segment joint area, and output the structural safety margin of the segment.

7. A method for monitoring and analyzing data of a shield tunnel segment loading test platform according to claim 6, characterized in that: The analysis method of the curvature value of each sampling point is as follows: Construct a neighborhood point coordinate set according to all the nearest neighbor points in the corresponding neighborhood of each sampling point; Perform average coordinate analysis on the neighborhood point coordinate set to obtain the average coordinate of the neighborhood points; Calculate the covariance matrix according to the coordinates of all the neighborhood points in the neighborhood point coordinate set and the average coordinate of the corresponding neighborhood points; Perform eigenvalue decomposition on the calculated covariance matrix to obtain the first principal curvature and the second principal curvature, and take the average of the first principal curvature and the second principal curvature as the curvature value.

8. A method for monitoring and analyzing data of a segment loading test platform for shield tunnels according to claim 6, characterized in that: The specific method of the structural safety margin of the segment is as follows: Analyze the deviation degree of the maximum curvature value and the curvature change rate from the design limit curvature of the segment structure and the set curvature change rate threshold respectively to obtain the maximum curvature value deviation degree and the curvature change rate deviation degree. Perform linear fusion analysis on the maximum curvature value deviation degree and the curvature change rate deviation degree to obtain the deformation danger degree index of the outer surface of the segment; Use the Pearson correlation coefficient to determine the correlation between the deformation danger degree index of the outer surface of the segment and the deformation danger degree index of the segment joint area. When the determined correlation is relevant, perform collaborative analysis on the deformation danger degree index of the outer surface of the segment and the deformation danger degree index of the segment joint area to obtain the comprehensive deformation danger degree index. When the determined correlation is non-relevant, take the maximum value of the deformation danger degree index of the outer surface of the segment and the deformation danger degree index of the segment joint area as the comprehensive deformation danger degree index, and compare and analyze the comprehensive deformation danger degree index with the set comprehensive critical index to generate the structural safety margin of the segment.

9. A method for monitoring and analyzing data of a segment loading test platform for shield tunnels according to claim 8, characterized in that: The collaborative analysis process of the comprehensive deformation danger degree index is as follows: Multiply and accumulate the deformation danger degree index of the outer surface of the segment and the deformation danger degree index of the segment joint area with the corresponding weight coefficients to obtain the comprehensive deformation danger degree index.

10. A method for monitoring and analyzing data of a shield tunnel segment loading test platform according to claim 1, characterized in that: The specific steps of triggering the multi-level early warning mechanism are as follows: When the structural safety margin of the segment is less than the preset structural safety margin threshold, obtain the deviation value of the structural safety margin of the segment, divide the early warning level according to the deviation value of the structural safety margin of the segment, and trigger the control instruction of the alarm signal set corresponding to the early warning level to control the loading device of the test platform to adjust the preset loading scheme.

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