A data monitoring and analysis method for shield tunnel segment loading test platform

Abstract

The present invention relates to the technical field of tunnel segment data monitoring and analysis, and relates to a data monitoring and analysis method for a shield tunnel segment loading test platform. The present invention captures the position coordinates of the identification points in the segment joint area and decomposes them into normal, tangential and rotational displacement components, thereby achieving real-time synchronous quantification of the joint opening, dislocation and torsion angle. At the same time, based on the timestamp alignment technology, the historical test data and the real-time sequence are integrated, and the segment joint deformation evolution trend diagram is predicted through multi-parameter coupling. Combined with the real-time sequence, a collaborative judgment is made to generate a segment joint area deformation hazard index, thereby achieving dynamic and accurate prediction of the deformation trend and accurate assessment of the hazard level. The identified maximum curvature position and curvature change rate are correlated with the segment joint area deformation hazard index for analysis, and the segment structure safety margin is output, triggering a multi-level early warning mechanism, thereby comprehensively evaluating the overall structural safety status 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 in particular to a data monitoring and analysis method for a shield tunnel segment loading test platform. Background Art

[0002] During shield tunnel construction and operation, the safety of the segment structure is directly related to the tunnel's overall stability and service life. With the increasing complexity of urban underground space development, shield tunnels face increasingly variable load environments. Multidimensional structural responses, such as segment joint deformation and changes in external surface curvature, have become key indicators for evaluating segment safety performance.

[0003] For example, Chinese patent publication number CN117951651A discloses a shield segment cracking monitoring and prediction method. This method measures the deformation data of the shield segment through an inclination sensor, takes into account the geological conditions and construction conditions of the shield tunnel, and effectively predicts the deformation and cracking of the segment. The XGBoost algorithm is used to establish and train a segment deformation assessment model to achieve real-time assessment of shield segment cracking, more accurately reflecting information such as geological conditions and shield machine operating parameters, thereby improving the accuracy and effectiveness of segment cracking prediction.

[0004] For example, a shield-type tunnel morphology data processing system and method disclosed in Chinese patent publication number CN119577922A includes the following steps: S1 collects and pre-processes data from a number of sections in a shield-type tunnel; S2 calculates the offset of the center of each segment; S3 continuously measures and analyzes deformation trends; S4 uses a linear regression model to predict offset changes; and S5 uses the trained model to predict the final offset of the segment.

[0005] However, the existing technology has the following problems: 1. When monitoring and analyzing segment deformation data, most of the existing technologies focus on single-dimensional data processing, such as only analyzing deformation data or geological data separately. There is a lack of comprehensive consideration of the correlation between the deformation of the segment joint area and the deformation of the segment outer surface, and it is impossible to comprehensively evaluate the overall structural safety status of the shield tunnel segment.

[0006] 2. Existing technologies analyze deformation trends by collecting cross-sectional data and measuring segment center offsets, focusing on changes in segment center positions. However, they are not accurate enough in monitoring detailed deformation information in segment joint areas, making it difficult to accurately assess the structural safety risks at the joints and unable to fully reflect the complex deformation conditions in the segment joint areas. Summary of the Invention

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

[0008] The present invention solves the technical problem by adopting a technical solution: a data monitoring and analysis method for a shield tunnel segment loading test platform, comprising:

[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 the preset loading scheme, and simultaneously construct a 3D point cloud model of the segment through 3D laser scanning.

[0010] S2. Based on the three-dimensional point cloud model of the pipe segment, the position coordinates of the pre-arranged marking points in the pipe segment joint area are captured in real time, and the real-time sequence of the joint opening amount, displacement amount and torsion angle in the pipe segment joint area is obtained through spatial coordinate conversion.

[0011] S3. Correlate historical test data of shield tunnel segment joints with real-time sequences, predict segment joint deformation evolution trend diagrams through multi-parameter coupling, and make collaborative judgments based on real-time sequences to generate a segment joint area deformation hazard index.

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

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

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

[0015] (1) The present invention applies physical loads by operating the loading device of the test platform, and constructs a three-dimensional point cloud model of the pipe segment using three-dimensional laser scanning. The marking points are symmetrically arranged in the joint area, and the coordinates of the marking points are captured in real time and decomposed into normal, tangential and rotational displacement components, thereby achieving real-time synchronous quantification of the joint opening, dislocation and torsion angle, and comprehensively capturing the three-dimensional deformation characteristics under the action of load.

[0016] (2) The present invention integrates historical test data and real-time sequences through timestamp alignment technology, selects the most similar historical sequences based on morphological similarity calculation based on Euclidean distance, constructs a deformation evolution trend graph and outputs the current prediction value, combines the multi-parameter deviation value with the preset weight coefficient to generate the deformation hazard index of the segment joint area, thereby realizing quantitative assessment of the safety risk of the segment joint structure, and realizing dynamic and accurate prediction of deformation trend and accurate assessment of hazard level.

[0017] (3) The present invention extracts the curvature value of each sampling point on the outer surface of the segment, identifies the maximum curvature position and curvature change rate, and performs correlation analysis with the deformation risk index of the segment joint area. It outputs the segment structure safety margin and realizes the coordinated analysis of the deformation of the segment outer surface and the risk of the joint area, thereby comprehensively evaluating the overall structural safety status 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 following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 Schematic diagram of the method steps of the present invention.

[0020] Figure 2 This is a flow chart of the step contents of S2 in the present invention.

[0021] Figure 3 This is a flow chart of the step contents of S3 in the present invention.

[0022] Figure 4 Schematic diagram of the analysis steps and determination of the safety margin of the segment structure in the present invention. DETAILED DESCRIPTION

[0023] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions, and numerical values ​​described in these embodiments do not limit the scope of the present invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn to scale.

[0024] The following description of at least one exemplary embodiment is merely illustrative in nature and is not intended to limit the invention, its application, or uses. Technologies, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the specification.

[0025] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. 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 data monitoring and analysis method for a shield tunnel segment loading test platform. The present invention captures the position coordinates of the identification points in the segment joint area and decomposes them into normal, tangential and rotational displacement components, thereby achieving real-time synchronous quantification of the joint opening, dislocation and torsion angle. At the same time, based on the timestamp alignment technology, the historical test data and the real-time sequence are integrated, and the segment joint deformation evolution trend diagram is predicted through multi-parameter coupling. Combined with the real-time sequence, a collaborative judgment is made to generate a segment joint area deformation hazard index, thereby achieving dynamic and accurate prediction of the deformation trend and accurate assessment of the hazard level. The identified maximum curvature position and curvature change rate are correlated with the segment joint area deformation hazard index for analysis, and the segment structure safety margin is output, triggering a multi-level early warning mechanism, thereby comprehensively evaluating the overall structural safety status of the shield tunnel segment.

[0027] See also Figure 1 As shown, the present invention provides a data monitoring and analysis method for a shield tunnel segment loading test platform, including: S1, operating the loading device of the test platform to apply a physical load to the outer surface of the shield tunnel segment to be tested according to a preset loading scheme, and simultaneously constructing 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 based on the design parameters of the shield tunnel segments, actual working condition simulation and relevant mechanical performance test requirements. It details the key factors such as the loading sequence, loading rate, loading magnitude and loading duration of the load. For example, the load is applied in a step-by-step manner from low to high, and each load level lasts for a certain time to ensure that the segments have sufficient response. At the same time, the maximum loading limit is determined based on the design bearing capacity of the segments. It aims to truly simulate the various physical load conditions that the shield tunnel segments may suffer during actual use, and provide a scientific and rigorous loading basis for the subsequent construction of a three-dimensional point cloud model of the segments through three-dimensional laser scanning and in-depth analysis, so as to accurately evaluate the mechanical properties and structural stability of the segments.

[0029] The 3D laser scanning is composed of multiple groups of 3D laser scanners, each of which is distributed in a layered and staggered manner along the axial and circumferential directions of the pipe segment, and the coverage area of ​​each 3D laser scanner forms a monitoring overlap area with its adjacent scanner. The 3D laser scanners are started synchronously to perform a full-scale scan of the pipe segment with extremely high precision, quickly capturing the subtle features and changes of the pipe segment surface and its structure, and then constructing an accurate and detailed 3D point cloud model of the pipe segment, providing a rich and accurate data basis for subsequent in-depth analysis of the deformation, stress distribution, etc. of the pipe segment under load, and helping to comprehensively evaluate the performance and quality of the shield tunnel pipe segment.

[0030] S2. Based on the three-dimensional point cloud model of the pipe segment, the position coordinates of the pre-arranged marking points in the pipe segment joint area are captured in real time, and the real-time sequence of the joint opening amount, displacement amount and torsion angle in the pipe segment joint area is obtained through spatial coordinate conversion.

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

[0032] S22, comparing the position coordinates of each marker point captured in real time with the initial three-dimensional coordinates to obtain a three-dimensional displacement vector of each marker point, wherein the initial three-dimensional coordinates of the marker point are the three-dimensional coordinates when the loading device of the test platform is not loaded.

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

[0034] S24, according to the real-time joint opening, displacement and torsion angle of the segment joint area,

[0035] Construct a real-time sequence of joint opening, displacement and torsion angle. The real-time sequence consists of all joint opening, displacement and torsion angles with 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 based on the joint surface, with the Z axis being the normal vector direction of the joint surface, the X axis being the circumferential tangent direction of the segment, and the Y axis being the longitudinal tangent direction of the segment, satisfying the orthogonal relationship X×Y=Z.

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

[0038] Tangential displacement refers to the displacement component of the marking point in the joint plane and perpendicular to the joint direction. Under the action of load, the marking points on both sides of the segment joint will undergo relative displacement along the tangential direction. The relative displacement is the slip. The slip consists of two orthogonal components: circumferential slip and longitudinal slip. If the slip is , where is the circumferential discrepancy momentum, , is the annular tangential unit vector, is the longitudinal displacement, , is the longitudinal tangential unit vector, and the maximum displacement is selected from the displacement of each identification point as the real-time displacement of the segment joint area.

[0039] Rotational displacement refers to the rotation of the marking point around a certain axis. During the loading process, the segment joint area may undergo torsional deformation, causing the marking point to rotate around a certain axis, usually the axis of the joint or other key axis. By analyzing the rotational displacement of the marking point, the torsion angle at the joint can be calculated. For example, if the torsion angle is The maximum torsion angle is selected from the torsion angles of each identification point as the real-time torsion angle of the segment joint area.

[0040] The present invention applies physical loads by operating the loading device of the test platform while constructing a three-dimensional point cloud model of the pipe segment using three-dimensional laser scanning, and symmetrically arranges identification points in the joint area. The coordinates of the identification points are captured in real time and decomposed into normal, tangential and rotational displacement components, thereby achieving real-time synchronous quantification of the joint opening, misalignment and torsion angle, comprehensively capturing the three-dimensional deformation characteristics under the action of load, improving the accuracy of the structural safety risk assessment at the pipe segment joint, and providing detailed and accurate data support for subsequent deformation evolution trend prediction and hazard level assessment.

[0041] S3. Correlate historical test data of shield tunnel segment joints with real-time sequences, predict segment joint deformation evolution trend diagrams through multi-parameter coupling, and make collaborative judgments based on real-time sequences to generate a segment joint area deformation hazard index.

[0042] like Figure 3 As shown, the specific steps of S3 are as follows: S31. Obtain the historical sequence of joint opening, dislocation and torsion angle of each test in the historical test data of shield tunnel segment joints, align the historical sequence with the real-time sequence by time stamp, predict the segment joint deformation evolution trend chart through coupling analysis, and output the current predicted values ​​of joint opening, dislocation and torsion angle.

[0043] S32. Coordinate the current predicted value with the real-time joint opening, displacement and torsion angle, fuse the opening deviation, displacement deviation and torsion angle deviation based on the preset weight coefficient, and generate a deformation risk index for the segment joint area.

[0044] Furthermore, the current predicted values ​​of the joint opening, misalignment and torsion angle are output as follows: S311, the current loading duration is obtained according to the real-time sequence, the historical sequence corresponding to the current loading duration is intercepted from the historical sequence of each test, and the historical sequence is aligned with the real-time sequence for timestamps to obtain the historical synchronization time series and the real-time synchronization time series respectively.

[0045] S312. Normalize the historical synchronization time series and real-time synchronization time series of each test, and use the Euclidean distance to calculate the difference between the real-time synchronization time series and the historical synchronization time series of each test at each time point. Based on the difference, determine the morphological similarity between the real-time synchronization time series and the historical synchronization time series of each test.

[0046] S313. Filter the historical sequences of joint opening, displacement, and torsion angle corresponding to the test with the highest morphological similarity, construct a segment joint deformation evolution trend graph based on the filtered historical sequences, and select the current predicted values ​​of the joint opening, displacement, and torsion angle corresponding to the real time.

[0047] In a specific embodiment, the normalization process may be a minimum-maximum normalization process, which is a prior art and will not be described in detail here.

[0048] The difference between the real-time synchronous time series and the historical synchronous time series of each test at each time point is , They are the first The joint opening, displacement and torsion angle at a given time point, They are the first The joint opening, displacement and torsion angle at a given time point, .

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

[0050] It should be noted that the deformation hazard index of the segment joint area is generated as follows: the real-time joint opening, dislocation and torsion angle are compared and analyzed with the current predicted values ​​of the joint opening, dislocation and torsion angle respectively, and the deviation between the real-time value of the joint opening and the current predicted value, the deviation between the real-time value of the dislocation and the current predicted value, and the deviation between the real-time value of the torsion angle and the current predicted value are calculated. After normalizing the joint opening deviation value, the dislocation deviation value and the torsion angle deviation value, they are weightedly summed based on the preset weight coefficient to obtain the deformation hazard index of the segment joint area.

[0051] The setting of the preset weight coefficient is determined according to the hazard level of each deformation parameter in the shield tunnel engineering specification, such as the weight of the joint opening is greater than the weight of the displacement, and the weight of the displacement is greater than the weight of the torsion angle. The joint opening has the largest weight because it directly affects the waterproof performance and overall stability of the tunnel; the displacement has a greater impact on driving safety and local stress of the structure, and its weight is second; the influence of the torsion angle is relatively small, and its weight is the lowest. For example, the weight of the joint opening can be , the weight of the dislocation can be , the torsion angle weight can be .

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

[0053] The present invention integrates historical test data and real-time sequences through timestamp alignment technology, selects the most similar historical sequences based on morphological similarity calculation based on Euclidean distance, constructs a deformation evolution trend graph and outputs the current prediction value, and combines multi-parameter deviation values ​​with preset weight coefficients to generate a deformation hazard index for the segment joint area, thereby achieving a quantitative assessment of the safety risk of the segment joint structure, and realizing dynamic and accurate prediction of deformation trends and accurate assessment of the hazard level.

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

[0055] It should be noted that the specific steps of S4 are as follows: uniformly sample the outer surface of the segment of the segment three-dimensional point cloud model to select each sampling point, search for all nearest neighboring points in the neighborhood corresponding to each sampling point, construct a covariance matrix of each sampling point, perform feature analysis 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, calculate the curvature change rate of the adjacent time points of the maximum curvature position, correlate the maximum curvature value, the curvature change rate and the deformation hazard index of the segment joint area, and output the safety margin of the segment structure.

[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] Furthermore, the curvature value analysis method of each sampling point is as follows: a neighborhood point coordinate set is constructed according to all the nearest neighboring points in the neighborhood corresponding to each sampling point, an average coordinate analysis is performed on the neighborhood point coordinate set to obtain the neighborhood point mean coordinates, a covariance matrix is ​​calculated according to the coordinates of all neighborhood points in the neighborhood point coordinate set and the corresponding neighborhood point mean coordinates, an eigenvalue decomposition is performed on the calculated covariance matrix to obtain the first principal curvature and the second principal curvature, and the average of the first principal curvature and the second principal curvature is used as the curvature value.

[0058] The first principal curvature and the second principal curvature are respectively the first eigenvalue and the second eigenvalue of the eigenvalues ​​of the covariance matrix. The covariance matrix and the eigenvalue decomposition process of the covariance matrix are both existing technologies.

[0059] like Figure 4 As shown, the specific method of the safety margin of the segment structure is: the maximum curvature value and the curvature change rate are analyzed with the design limit curvature of the segment structure and the set curvature change rate threshold respectively to obtain the maximum curvature value deviation and the curvature change rate deviation, and the maximum curvature value deviation and the curvature change rate deviation are linearly fused and analyzed to obtain the deformation hazard index of the outer surface of the segment.

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

[0061] The linear fusion analysis method of the segment outer surface deformation hazard index is to retrieve historical data of the maximum curvature value deviation and the curvature change rate deviation at different positions on the segment outer surface from historical tunnel segment inspection records, construct a linear regression equation with the maximum curvature value deviation and the curvature change rate deviation as independent variables and the dependent variable as the segment outer surface deformation hazard index, solve the constructed linear regression equation using the least squares method based on the retrieved historical data, obtain the regression coefficients and intercept term of the maximum curvature value deviation and the curvature change rate deviation, thereby constructing 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 segment outer surface deformation hazard index.

[0062] The Pearson correlation coefficient is used to determine the correlation between the segment outer surface deformation hazard index and the segment joint area deformation hazard index. If the correlation is determined to be positive, a comprehensive deformation hazard index is generated based on the combined analysis of the two. If the correlation is negative, the maximum of the two values ​​is used as the comprehensive deformation hazard index. This comprehensive deformation hazard index is then compared with the set comprehensive critical index to generate the segment structural safety margin. When the Pearson correlation coefficient is less than 0.3 and greater than 0, the correlation is negative; when the Pearson correlation coefficient is greater than 0.3 and less than 1, the correlation is positive.

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

[0064] The collaborative analysis process for the comprehensive deformation hazard index is as follows: the deformation hazard index of the segment outer surface and the deformation hazard index of the segment joint area are multiplied and added with corresponding weight coefficients to obtain the comprehensive deformation hazard index. Segment joint areas, such as bolted joints or girth seams, are generally given a higher weight because their deformation is prone to cascading failures. The concrete mass on the segment outer surface is relatively less heavily weighted. In one specific embodiment, the weight of the deformation hazard index of the segment joint area can be set to 0.6, and the weight of the deformation hazard index of the segment outer surface can be set to 0.4.

[0065] The present invention extracts the curvature value of each sampling point on the outer surface of the segment, identifies the maximum curvature position and curvature change rate, performs correlation analysis with the deformation hazard index of the segment joint area, outputs the segment structure safety margin, and realizes the coordinated analysis of the deformation of the segment outer surface and the risk of the joint area, thereby comprehensively evaluating the overall structural safety status of the shield tunnel segment.

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

[0067] It should be noted that the specific steps for triggering the multi-level warning mechanism are as follows: when the segmental structural safety margin is less than a preset structural safety margin threshold, a segmental structural safety margin deviation value is obtained, a warning level is determined based on the segmental structural safety margin deviation value, and an alarm signal set control instruction corresponding to the warning level is triggered to control the loading device of the test platform to adjust the preset loading scheme. The segmental structural safety margin deviation value is the difference between the preset structural safety margin threshold and the segmental structural safety margin.

[0068] The multi-level early warning mechanism established by the present invention can trigger early warnings of corresponding levels according to different degrees of safety margin, can more accurately reflect the safety risk level of the segment structure, and promptly remind operators to take corresponding measures, thereby improving the safety and reliability of shield tunnel segment loading tests and providing stronger safety guarantees for the construction and operation of tunnel projects.

[0069] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

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

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

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

[0073] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0074] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A data monitoring and analysis method for a shield tunnel segment loading test platform, characterized in that: include: 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 the preset loading scheme, and simultaneously construct a 3D point cloud model of the segment through 3D laser scanning; S2. Based on the segment 3D point cloud model, the position coordinates of the pre-placed marker points in the segment joint area are captured in real time. Through spatial coordinate conversion, a real-time sequence of the joint opening, displacement, and torsion angle in the segment joint area is obtained. The steps of S2 are as follows: S21. Evenly distribute marking points on both sides of the corresponding joints in the segment joint area, and capture the position coordinates of each marking point in real time; S22, comparing the position coordinates of each marker point captured in real time with the initial three-dimensional coordinates to obtain a three-dimensional displacement vector of each marker point; S23. Decomposing the three-dimensional displacement vector of each marked point into normal displacement, tangential displacement, and rotational displacement components through spatial coordinate transformation, and obtaining the real-time joint opening, displacement, and torsion angle of the segment joint area based on the normal displacement, tangential displacement, and rotational displacement components; S24, according to the real-time joint opening, displacement and torsion angle of the segment joint area, Construct a real-time sequence of joint opening, displacement and torsion angle; S3. Correlate historical test data of shield tunnel segment joints with real-time sequences, predict segment joint deformation evolution trends through multi-parameter coupling, and make collaborative judgments based on real-time sequences to generate a segment joint area deformation hazard index. The specific steps of S3 are as follows: Obtain the historical sequence of joint opening, displacement, and torsion angle for each test in the historical test data of shield tunnel segment joints, align the historical sequence with the real-time sequence by time stamp, predict the segment joint deformation evolution trend through coupling analysis, and output the current predicted values ​​of joint opening, displacement, and torsion angle; The current predicted value is coordinated with the real-time joint opening, displacement and torsion angle, and the opening deviation, displacement deviation and torsion angle deviation are integrated based on the preset weight coefficient to generate the deformation risk index of the segment joint area; S4. Extract the curvature value of each sampling point on the outer surface of the segment, identify the maximum curvature position and curvature change rate, perform correlation analysis with the deformation risk index of the segment joint area, and output the safety margin of the segment structure; The specific steps of S4 are as follows: Uniformly sample the outer surface of the segment of the segment 3D point cloud model and select sampling points; Search for all nearest neighboring points in the neighborhood corresponding to each sampling point and construct the covariance matrix of each sampling point; Perform characteristic analysis on the covariance matrix to obtain the curvature value of each sampling point; The sampling point corresponding to the maximum curvature value is selected from the curvature values ​​of each sampling point as the maximum curvature position, and the curvature change rate of the adjacent time points of the maximum curvature position is calculated; Correlation analysis is performed on the maximum curvature value, curvature change rate and deformation risk index of the segment joint area to output the segment structure safety margin; The specific method of outputting the safety margin of the segment structure is: The maximum curvature value and curvature change rate are analyzed for deviation from the design limit curvature of the segment structure and the set curvature change rate threshold, respectively, to obtain the maximum curvature value deviation and curvature change rate deviation. The maximum curvature value deviation and curvature change rate deviation are linearly fused to obtain the segment outer surface deformation hazard index. The Pearson correlation coefficient is used to determine the correlation between the segment outer surface deformation hazard index and the segment joint area deformation hazard index. When the correlation is determined to be correlated, a comprehensive deformation hazard index is generated based on a collaborative analysis of the segment outer surface deformation hazard index and the segment joint area deformation hazard index. When the correlation is determined to be uncorrelated, the maximum value of the segment outer surface deformation hazard index and the segment joint area deformation hazard index is used as the comprehensive deformation hazard index. The comprehensive deformation hazard index is then compared with the set comprehensive critical index to generate the segment structure safety margin. S5. When the safety margin of the segment structure is less than the preset structural safety threshold, a multi-level early warning mechanism is triggered.

2. The data monitoring and analysis method for a shield tunnel segment loading test platform according to claim 1 is characterized by: The current predicted values ​​of the joint opening, displacement and torsion angle are output as follows: The current loading duration is obtained based on the real-time sequence. The historical sequence corresponding to the current loading duration is intercepted from the historical sequence of each test. The historical sequence is timestamped with the real-time sequence to obtain the historical synchronization time series and the real-time synchronization time series respectively. The historical synchronization time series and real-time synchronization time series of each test were normalized. The normalization results were used to calculate the difference between the real-time synchronization time series and the historical synchronization time series of each test at each time point using the Euclidean distance. The morphological similarity between the real-time synchronization time series and the historical synchronization time series of each test was determined based on the difference. The historical sequences of joint opening, displacement and torsion angle corresponding to the test with the highest morphological similarity are screened, and a segment joint deformation evolution trend diagram is constructed based on the screened historical sequences, from which the current predicted values ​​of joint opening, displacement and torsion angle corresponding to the real time are selected.

3. The data monitoring and analysis method for a shield tunnel segment loading test platform according to claim 1 is characterized by: The segment joint area deformation risk index is generated as follows: The real-time joint opening, dislocation and torsion angle are compared and analyzed with the current predicted values ​​of the joint opening, dislocation and torsion angle respectively, and the deviation between the real-time value of the joint opening and the current predicted value, the deviation between the real-time value of the dislocation and the current predicted value, and the deviation between the real-time value of the torsion angle and the current predicted value are calculated. After the joint opening deviation value, the dislocation deviation value and the torsion angle deviation value are normalized, they are weightedly summed based on the preset weight coefficient to obtain the deformation hazard index of the pipe segment joint area.

4. The data monitoring and analysis method for a shield tunnel segment loading test platform according to claim 1 is characterized by: The curvature value analysis method of each sampling point is: Construct a neighborhood point coordinate set based on all the nearest neighboring points in the neighborhood corresponding to each sampling point; Perform average coordinate analysis on the neighborhood point coordinate set to obtain the neighborhood point mean coordinates; Calculate the covariance matrix based on the coordinates of all neighborhood points in the neighborhood point coordinate set and the mean coordinates of the corresponding neighborhood points; The calculated covariance matrix is ​​subjected to eigenvalue decomposition to obtain the first principal curvature and the second principal curvature, and the mean of the first principal curvature and the second principal curvature is taken as the curvature value.

5. The method for monitoring and analyzing data of a shield tunnel segment loading test platform according to claim 1, characterized in that: The collaborative analysis process of the comprehensive deformation hazard index is as follows: the deformation hazard index of the outer surface of the segment and the deformation hazard index of the segment joint area are multiplied and added with the corresponding weight coefficients to obtain the comprehensive deformation hazard index.

6. The 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 segment structure safety margin is less than the preset structural safety margin threshold, the segment structure safety margin deviation value is obtained, the warning level is divided according to the segment structure safety margin deviation value, and the alarm signal set control instruction corresponding to the warning level is triggered to control the loading device of the test platform to adjust the preset loading plan.

Images