Shield tunnel electromechanical numerical control and test integrated model test platform and method

Abstract

The invention discloses a shield tunnel electromechanical numerical control and testing integrated model test platform and method, and relates to the technical field of shield construction testing. Comprising the following steps: S1, collecting water-soil machine three-dimensional coupling test data in real time, and performing data preprocessing; s2, reconstructing a pore pressure, water content, stress and average effective stress multi-distribution field; multiple types of residual parameters are calculated, the three-dimensional water-soil coupling balance is evaluated, the hydraulic stress state is judged, and balance control over flow and pressure is executed; s3, when the hydraulic stress state is imbalanced, evaluating and correcting the flux adjusting quantity, and realizing water inlet and outlet flow adjustment; and S4, based on the three-dimensional water-soil coupling balance change rate and the correction flux regulation variable change rate, evaluating dynamic response consistency, updating parameters and correcting a threshold value. The problem that the test precision and the subsequent construction safety are affected due to the fact that an existing shield test device cannot accurately reflect the stress seepage collaborative change rule in the shield construction process under the complex water-rich stratum is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of shield construction testing, in particular to a shield tunnel electromechanical numerical control and testing integrated model test platform and method. BACKGROUND

[0002] With the continuous advancement of urbanization and the continuous deepening of the development and utilization of underground space resources, tunnel excavation and underground engineering construction occupies an increasingly important position in the city infrastructure system. As the main way of modern tunnel construction, shield method is widely used in subway transportation, urban pipe network, underground passage and large water conservancy projects and other fields. At the same time, the expansion of engineering scale and the complication of construction conditions put forward higher requirements for tunnel construction safety control, environmental protection and operation and maintenance.

[0003] For example, the patent with the announcement number CN112031782B announces a detection device of a shield machine, which comprises a cutter holder, a cutter head, a signal sending module and a signal receiving module. One end of the cutter holder is provided with a mounting groove. A weighing sensor is fixedly connected to the inner wall of the mounting groove. The outer wall of the weighing sensor is fixedly connected with a conductive test plate. The outer wall of the conductive test plate is provided with a plurality of conductive test mechanisms. The inner wall of the mounting groove is fixedly connected with a limiting ring. The inner wall of the mounting groove is fixedly connected with a mounting plate on one side of the limiting ring. A plurality of top rods are uniformly arranged on the outer wall of the mounting plate. The present application is provided with a plurality of blind holes and inflation strips. When the cutter head reaches a certain degree of wear, the corresponding detection blind hole will be worn out, and the inflation strip in the detection blind hole will be worn out in the subsequent operation process, which will randomly trigger the weighing sensor and the conductive test mechanism in the cutter holder, so as to report the wear condition of the cutter by means of the cooperation of the signal sending module and the signal receiving module.

[0004] For example, the patent with the announcement number CN111255471B announces a multi-working-condition earth pressure balance shield muck working property test simulation test system, which comprises a water supply system, a pressure source, a test cylinder, a shear rod arranged in the test cylinder, an axial loading device, a radial extrusion ring capsule and a test bin pressure sensor. The test cylinder can simulate the soil bin working state of the earth pressure balance shield machine. The axial loading device is used to simulate different shield machine thrust forces. The radial extrusion ring capsule is used to simulate the change of the earth pressure balance shield machine. The water supply system is used to simulate the water pressure of different underground water environments. The modifier adding system is used for muck sample improvement test. The present application can comprehensively test the working property of the soil sample under the condition that the water pressure and the earth pressure change synchronously, which is also beneficial to the research on the coupling effect of the water pressure and the earth pressure on the working property of the soil sample. The working property parameters of the soil sample measured by the test system of the present application are more scientific and objective, and are more in line with the actual working conditions of the shield engineering in special water-rich strata such as river and sea.

[0005] However, in the construction simulation of complex water-rich strata, the existing shield test devices are mostly concentrated on single working condition or partial structural performance test, lacking the ability of systematic simulation and quantitative evaluation of dynamic interaction among water, soil and structure. Although the traditional test box can adjust the underground water level and has water inlet and outlet control structure, under the condition of water-soil interaction, the coupling change of pore water pressure and soil effective stress is significant, and it is difficult to realize the accurate control of the shield "earth pressure balance" state, resulting in insufficient test reproducibility and comparability. At the same time, the single soil pressure or seepage monitoring method cannot reflect the spatial distribution characteristics of three-dimensional water-soil coupling effect, which limits the real reproduction and verification of complex stress seepage behavior in shield construction.

[0006] Therefore, in view of the above problems, a shield tunnel electromechanical numerical control and test integrated model test platform and method are urgently needed. SUMMARY

[0007] Technical problems to be solved

[0008] In view of the deficiencies of the prior art, the present application provides a shield tunnel electromechanical numerical control and test integrated model test platform and method, which solves the problem that the existing shield test device cannot accurately reflect the stress seepage collaborative variation law in the shield construction process under complex water-rich strata, thereby affecting the test precision and subsequent construction safety.

[0009] Technical scheme

[0010] To achieve the above purpose, the present application realizes the following technical scheme: a shield tunnel electromechanical numerical control and test integrated model test method, comprising the following steps: S1, real-time acquisition of water-soil machine three-dimensional coupling test data, data preprocessing of water-soil machine three-dimensional coupling test data; S2, mapping the preprocessed water-soil machine three-dimensional coupling test data to a unified three-dimensional grid, reconstructing the pore pressure, water content, stress and average effective stress multi-distribution field; calculating multiple residual parameters through spatial difference and time derivative of the multi-distribution field and evaluating the three-dimensional water-soil coupling balance, determining the hydraulic stress state and executing the balance control of flow and pressure; S3, when the hydraulic stress state is unbalanced, combining the three-dimensional water-soil coupling balance and the multiple residual parameter evaluation correction flux adjustment amount, and driving the hydraulic pump and valve execution unit to realize the water inlet and outlet flow adjustment; S4, based on the three-dimensional water-soil coupling balance change rate and the correction flux adjustment amount change rate, evaluating the dynamic response consistency, updating the parameters and correcting the threshold value according to the dynamic response consistency.

[0011] Further, the three-dimensional coupling test data of the water and soil machine is collected in real time, and the specific process of data preprocessing of the three-dimensional coupling test data of the water and soil machine is as follows: the three-dimensional coupling test data of the water and soil machine is collected in real time, and the three-dimensional coupling test data of the water and soil machine includes: sample volume, measuring point elevation, porosity, coefficient of Biot, groundwater level, pore water pressure, volumetric water content, vertical total stress, lateral total stress, water inflow, water outflow, valve opening, soil temperature, and spatial coordinates and unified time stamp of each sensing point; the time error of all sensing nodes is controlled through precise timing; the main sampling frequency is set, linear interpolation resampling is performed on the pore water pressure, vertical total stress, lateral total stress, water inflow and water outflow, zero-order hold is adopted for the groundwater level, volumetric water content, water temperature and valve opening; temperature compensation and calibration conversion are performed, the pore water pressure, volumetric water content, water inflow and water outflow are corrected by using the same point temperature data, and the baseline correction is performed according to the static water state to eliminate zero drift; the three-dimensional coupling test data of the water and soil machine is filtered and abnormal data is removed, smooth filtering is adopted to remove high-frequency noise, and mutation and distortion points are identified through abnormal limit value and spatial consistency detection; the three-dimensional coupling test data of the water and soil machine is standardized and dimensionless normalized; a coupling test database is established, and the original and preprocessed three-dimensional coupling test data of the water and soil machine is stored in the coupling test database.

[0012] Further, the three-dimensional coupling test data of the water and soil machine is mapped to a unified three-dimensional grid, and the specific process of reconstructing the pore pressure, water content, stress and average effective stress multi-distribution field is as follows: the preprocessed three-dimensional coupling test data of the water and soil machine is mapped to a unified three-dimensional grid according to the spatial coordinates, and all data channels are synchronized based on the time stamp; the pore water pressure, volumetric water content, vertical total stress and lateral total stress are respectively interpolated in three dimensions to construct the pore pressure field, water content field and stress field components; the saturation value of each spatial point is obtained by calculating the ratio of volumetric water content to porosity, and the saturation field is generated by using the spatial interpolation method; the total water head is obtained by converting the pore water pressure of each measuring point by water density and gravitational acceleration and superimposing the measuring point elevation, and the difference between the total water heads of the water inlet and outlet measuring points is taken as the water head difference; according to the water inflow, water outflow and water head difference, the equivalent permeability coefficient of each region is calculated according to Darcy's law, and the viscosity correction of the equivalent permeability coefficient is performed by using the water temperature data to form the equivalent permeability coefficient field; according to the vertical total stress, lateral total stress and pore water pressure data, the effective stress in the vertical and lateral directions is calculated, that is, the total stress is subtracted from the pore water pressure at each measuring point to obtain the vertical and lateral effective stress distributions; the average effective stress value of each spatial point is obtained by averaging the vertical effective stress and twice the lateral effective stress, and the average effective stress field is constructed by using the spatial interpolation method.

[0013] Further, the specific process of calculating multi-class residual parameters and evaluating the three-dimensional water-soil coupling balance through the spatial difference and time derivative of the multi-distribution field is as follows: based on the pore pressure field, the saturation field, the equivalent permeability coefficient field and the average effective stress field, the derivative operation is performed on the continuous time sequence and the spatial grid by using the difference method to calculate the volume water content rate, the pore water pressure rate and the average effective stress rate; in the spatial dimension, the water head gradient, the saturation gradient and the average effective stress gradient of each point are calculated by using the neighborhood difference, and the flux vector field is obtained by multiplying the equivalent permeability coefficient and the total water head gradient point by point, and the divergence of the three-dimensional grid is performed to obtain the seepage flux divergence; the mass conservation residual is obtained by dividing the difference between the water inflow and the water outflow by the sample volume and subtracting the volume water content rate; the seepage equation residual is obtained by adding the seepage flux divergence and the volume water content rate; the stress-pore pressure consistency residual is obtained by adding the average effective stress rate and the product of the Biot coefficient and the pore water pressure rate; the saturation gradient modulus and the average effective stress gradient modulus are calculated, and the saturation gradient modulus is divided by the sum of the constant one and the average effective stress gradient modulus to obtain the spatial coupling gradient ratio; based on the same time, the spatial median of the mass conservation residual distribution is taken as the mass conservation reference value; the spatial median of the seepage equation residual distribution is taken as the seepage residual reference value; the spatial median of the stress-pore pressure consistency residual distribution is taken as the stress-pore pressure consistency reference value; the spatial median of the spatial coupling gradient ratio distribution is taken as the spatial coupling gradient ratio reference value; the mass conservation residual is divided by the mass conservation reference value, the seepage equation residual is divided by the seepage residual reference value, the stress-pore pressure consistency residual is divided by the stress-pore pressure consistency reference value, and the spatial coupling gradient ratio is divided by the spatial coupling gradient ratio reference value to obtain four ratios; the square sum of the four ratios is calculated, and the square root is obtained to obtain the three-dimensional water-soil coupling imbalance index term; the reciprocal of the three-dimensional water-soil coupling imbalance index term is subjected to natural exponential operation with the exponential power, and the three-dimensional water-soil coupling imbalance comprehensive value is obtained by subtracting the constant one from the natural exponential operation result.

[0014] Further, the specific process of determining the hydraulic stress state and performing the balance control of flow and pressure is as follows: based on the three-dimensional water-soil coupling imbalance comprehensive value, a three-dimensional water-soil coupling imbalance comprehensive value distribution field is constructed; when it is monitored that the three-dimensional water-soil coupling imbalance comprehensive value of any region is higher than the balance threshold value, it is determined that the local hydraulic stress is unbalanced, and the boundary control loop is triggered: if the three-dimensional water-soil coupling imbalance comprehensive value of the inflow side is higher than that of the outflow side, the water inlet pressure reduction control is performed to reduce the water inlet valve opening; if the three-dimensional water-soil coupling imbalance comprehensive value of the outflow side is higher than that of the inflow side, the water outlet discharge increase control is performed to increase the water outlet valve opening, and the pressure balance is restored by short-time drainage; if the three-dimensional water-soil coupling imbalance comprehensive value is higher than the balance threshold value for a duration exceeding the time tolerance threshold value, the staged water injection and drainage operation is performed by the precision water pump; when the three-dimensional water-soil coupling imbalance comprehensive value of the whole field is less than or equal to the balance threshold value, it is determined that the hydraulic stress is coordinated and stable, and the current valve opening and flow output are maintained; at the same time, the three-dimensional water-soil coupling imbalance comprehensive value of each monitoring point, as well as the valve opening, water inflow and water outflow change data are written into the coupling test database.

[0015] Further, when the hydraulic stress state is unbalanced, the specific process of combining three-dimensional water-soil coupling balance and multiple residual parameters to evaluate and correct the specific process of the flux adjustment amount is as follows: receiving the three-dimensional water-soil coupling unbalance comprehensive value distribution field, averaging the global three-dimensional water-soil coupling unbalance comprehensive value to obtain the three-dimensional water-soil coupling unbalance comprehensive average value, and calculating the average values of the three-dimensional water-soil coupling unbalance comprehensive values in the inlet and outlet water ends and the adjacent range to obtain the average unbalance comprehensive values of the inlet and outlet water ends; obtaining the mass conservation residual, the seepage equation residual, the stress-pore pressure consistency residual, and the spatial coupling gradient ratio of all measuring points, and calculating the average values to obtain the mass conservation residual average value, the seepage equation residual average value, the stress-pore pressure consistency residual average value, and the spatial coupling gradient ratio average value; calculating the product of the equivalent permeability coefficient field and the total water head along the normal component on the inlet and outlet water end boundaries to obtain the inlet and outlet water end boundary fluxes; based on the sliding time window, screening the median of the average values of the inlet and outlet water end boundary fluxes to obtain the flux reference value, calculating the three-dimensional water-soil coupling unbalance comprehensive average value change rate by the difference method, and screening the median of the three-dimensional water-soil coupling unbalance comprehensive average value to obtain the coupling unbalance comprehensive reference value, and taking the arithmetic average of the average values of the inlet and outlet water flow in the sliding time window to obtain the reference flux value; calculating the difference between the average unbalance comprehensive values of the inlet and outlet water ends to obtain the unbalance difference term; calculating the difference between the inlet and outlet water end fluxes and dividing the flux reference value to obtain the boundary flux deviation term; dividing the three-dimensional water-soil coupling unbalance comprehensive average value change rate by the coupling unbalance comprehensive reference value to obtain the unbalance change rate term; calculating the ratio of the mass conservation residual average value to the mass conservation reference value, the ratio of the seepage equation residual average value to the seepage residual reference value, the ratio of the stress-pore pressure consistency residual average value to the stress-pore pressure consistency reference value, and the ratio of the spatial coupling gradient ratio average value to the spatial coupling gradient ratio reference value, and taking the square root of the sum of the squares of the four ratios to obtain the coupling weight term; multiplying the sum of the unbalance difference term, the boundary flux deviation term, and the unbalance change rate term by the coupling weight term, substituting it into the hyperbolic tangent function for operation, and multiplying it by the current reference flux value to obtain the corrected flux adjustment value.

[0016] Further, the specific process of driving the hydraulic pump and valve execution unit to realize the water inflow and outflow adjustment is as follows: when it is determined that the local hydraulic stress is unbalanced, the corrected flux adjustment value is calculated and written into the coupling test database, and the corrected flux adjustment value is transmitted to the hydraulic pump and valve execution unit in real time; when the corrected flux adjustment value is greater than 0, the water inlet end execution mechanism is controlled to increase the flow output, and the water outlet end valve opening degree is adjusted synchronously; when the corrected flux adjustment value is less than 0, the execution unit performs the opposite action to reduce the water inlet pressure and reduce the water outlet end discharge rate; at the same time, the change rate of the three-dimensional water-soil coupling imbalance comprehensive average value is monitored, and when the change rate of the three-dimensional water-soil coupling imbalance comprehensive average value decreases to below the change threshold, the current flow output is locked; when the corrected flux adjustment value appears continuous reverse change or the amplitude of the corrected flux adjustment value exceeds the proportional threshold and does not converge, it is determined that the state is oscillation or over-regulation, and the adjustment step is limited and shrunk to enter the amplitude limiting self-stabilizing mode.

[0017] Further, the specific process of evaluating the dynamic response consistency based on the three-dimensional water-soil coupling balance change rate and the corrected flux adjustment value change rate is as follows: the corrected flux adjustment value and the three-dimensional water-soil coupling imbalance comprehensive average value are received, the three-dimensional water-soil coupling imbalance comprehensive average value change rate sequence is calculated based on the sliding time window, the standard deviation and average change rate of the three-dimensional water-soil coupling imbalance comprehensive average value change rate are calculated, and the corrected flux adjustment value change rate is calculated; the current three-dimensional water-soil coupling imbalance comprehensive average value change rate is subtracted from the average change rate to obtain the coupling change deviation value; the product of the current corrected flux adjustment value change rate and the proportional adjustment weight factor is calculated to obtain the flux response value; the absolute difference between the coupling change deviation value and the flux response value is calculated, and divided by the sum of the standard deviation of the three-dimensional water-soil coupling imbalance comprehensive average value change rate and the stability constant value to obtain the normalized dynamic difference value; the negative of the normalized dynamic difference value is taken as the exponential power to perform natural exponential operation to obtain the dynamic response consistency value.

[0018] Further, the specific process of updating the parameters and correcting the threshold value according to the dynamic response consistency is as follows: the dynamic response consistency value is calculated and written into the coupling test database, and compared with the consistency threshold value; when the dynamic response consistency is greater than or equal to the consistency threshold value, it is determined that the consistency regulation is stable, and the current algorithm and the corresponding reference value of each parameter are maintained; when the dynamic response consistency is less than the consistency threshold value, the reference value of each parameter is updated to the median value of the parameter distribution in the sliding time window as the update target, and is adaptively adjusted according to the weighted smoothing method; at the same time, based on the historical data in the coupling test database, the change rate sequence of the dynamic response consistency value and the three-dimensional water-soil coupling imbalance comprehensive value is used to optimize and update the balance threshold value and the consistency threshold value by using the Bayesian optimization algorithm.

[0019] The second aspect of the present application provides a shield tunnel electromechanical numerical control and test integrated model test platform, comprising: a data acquisition and preprocessing module, used for real-time acquisition of water and soil machine three-dimensional coupling test data, and data preprocessing of the water and soil machine three-dimensional coupling test data; a coupling analysis and balance evaluation module, used for mapping the preprocessed water and soil machine three-dimensional coupling test data to a unified three-dimensional grid, reconstructing pore pressure, water content, stress and average effective stress multi-distribution field; calculating multiple residual parameters through spatial difference and time derivative of the multi-distribution field and evaluating three-dimensional water and soil coupling balance, determining the hydraulic stress state, and performing balance control of flow and pressure; a flow regulation and closed-loop control module, used for when the hydraulic stress state is unbalanced, combining three-dimensional water and soil coupling balance and multiple residual parameter evaluation correction flux adjustment, and driving a hydraulic pump and valve execution unit to realize water inflow and outflow regulation; a self-learning and threshold optimization module, used for evaluating dynamic response consistency based on three-dimensional water and soil coupling balance rate and correction flux adjustment rate change rate, updating parameters and correcting thresholds according to dynamic response consistency.

[0020] Advantages

[0021] The present application has the following advantages:

[0022] (1) The present application, by multi-channel synchronous timing, temperature compensation, zero drift correction and dimensionless normalization processing of pore water pressure, water content, stress, flow and other multi-source physical quantities, establishes a reproducible coupling test database, realizes the spatial and temporal integration of water, soil, mechanical multi-parameter acquisition and high-precision fusion. Effectively eliminates the data deviation caused by multi-sensor asynchronous sampling and measurement point drift in traditional shield test.

[0023] (2) The present application, by unified spatial mapping and dynamic reconstruction of pore pressure field, water content field, stress field, saturation field and equivalent permeability coefficient field, based on the calculation of mass conservation residual, seepage equation residual, stress-pore pressure consistency residual and spatial coupling gradient ratio, forms a quantitative index of three-dimensional water and soil coupling imbalance comprehensive value, realizes the spatialization, continuity and numerical evaluation of the hydraulic stress coordination state. Breaks through the limitation of traditional test that can only observe the change of single stress or pore pressure, and can truly reflect the cooperative evolution law of water and soil stress in complex water-rich stratum.

[0024] (3) The present application, based on three-dimensional water and soil coupling imbalance comprehensive value and multiple residual parameter correction flux adjustment value, realizes intelligent adjustment of water inflow and outflow through hydraulic pump and valve execution unit. Using hyperbolic tangent function to constrain the adjustment signal nonlinearly, combining imbalance rate and flux deviation for amplitude limiting and self-stabilizing control, realizes the dynamic recovery and stable maintenance of the hydraulic stress balance state in the experiment. In the experiment, the water inflow and outflow pressure and flow are self-adaptively adjusted, effectively improving the authenticity and stability of the shield "earth pressure balance" simulation.

[0025] (4) The application calculates the coupling relationship of the three-dimensional water-soil coupling imbalance comprehensive mean change rate and the modified flux adjustment amount change rate, defines a dynamic response consistency value, and realizes the self-learning update and Bayesian optimization of the balance threshold and the consistency threshold based on the dynamic response consistency value. The control parameters and the threshold can be automatically corrected in long-term operation, the deviation accumulation caused by experience setting is avoided, the intelligentization, stabilization and long-term self-adaptive evolution of the test system are realized. Therefore, the experimental platform has the intelligent characteristics of "continuous learning, automatic optimization and dynamic convergence".

[0026] Of course, any product implementing the present application does not necessarily need to achieve all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 It is a shield tunnel mechanical and electrical numerical control and test integrated model test method flow chart;

[0028] Figure 2 It is a shield tunnel mechanical and electrical numerical control and test integrated model test platform structure diagram;

[0029] Figure 3 It is a shield tunnel mechanical and electrical numerical control and test integrated model test platform configuration schematic diagram;

[0030] Figure 4 It is a three-dimensional water-soil coupling residual error and comprehensive imbalance value collaborative evolution diagram. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. As understood by those skilled in the art, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0032] Please refer to Figures 1-4 The embodiments of the present application provide a technical solution: a shield tunnel mechanical and electrical numerical control and test integrated model test platform and method, such as Figure 1As shown, the method comprises the following steps: S1, real-time acquisition of water and soil machine three-dimensional coupling test data, data preprocessing of water and soil machine three-dimensional coupling test data; S2, mapping the preprocessed water and soil machine three-dimensional coupling test data to a unified three-dimensional grid, reconstructing the pore pressure, moisture content, stress and average effective stress multi-distribution field; calculating multiple residual parameters through the spatial difference and time derivative of the multi-distribution field and evaluating the three-dimensional water and soil coupling balance, determining the hydraulic stress state, and executing the balance control of flow and pressure; S3, when the hydraulic stress state is unbalanced, the three-dimensional water and soil coupling balance and the multiple residual parameter evaluation correction flux adjustment amount are combined, and the hydraulic pump and valve execution unit are driven to realize the water inflow and outflow flow regulation; S4, based on the three-dimensional water and soil coupling balance rate and the correction flux adjustment amount change rate, the dynamic response consistency is evaluated, the parameters are updated according to the dynamic response consistency, and the threshold value is corrected.

[0033] Specifically, the three-dimensional coupling test data of the water and soil machine is collected in real time, and the specific process of data preprocessing of the three-dimensional coupling test data of the water and soil machine is as follows: the three-dimensional coupling test data of the water and soil machine is collected in real time, and the three-dimensional coupling test data of the water and soil machine includes: sample volume, measuring point elevation, porosity, coefficient of Biot, groundwater level, pore water pressure, volumetric water content, vertical total stress, lateral total stress, water inflow, water outflow, valve opening, soil temperature, and spatial coordinates and unified time stamp of each sensing point; wherein, the sample volume and the measuring point elevation are determined by the design parameters and the spatial calibration system in the test loading and sensor layout stage, which are static input parameters; the porosity is obtained by calculating the volume change from the initial density of the sample and the local deformation measured by the multi-point displacement sensor arranged in the model box; the coefficient of Biot is calculated according to the known soil sample parameters through the ratio of the pore water pressure change and the total stress change; the groundwater level is collected in real time by the water level sensor arranged at the bottom of the sample; the pore water pressure is directly measured by the multi-point pore pressure sensor array; the volumetric water content is collected in real time by the soil moisture sensor using the TDR method; the vertical total stress and the lateral total stress are measured by the stress sensors buried in different directions respectively; the water inflow and the water outflow are collected by the high-precision electromagnetic flowmeter; the valve opening is collected by the valve angle sensor; the soil temperature is measured in real time by the thermosensitive temperature sensor; the spatial coordinates are obtained by the calibrated position before installation and the three-dimensional positioning system, and all sensing nodes are connected to the central collection control module through the bus, and the data are transmitted by the bus type integrated collection module, so as to ensure the synchronism and continuity of the collection process. A network time service and hardware clock joint calibration mechanism is adopted, and the precise time service of the PTP network time service system with sub-millisecond level synchronization accuracy is used to control the time error of all sensing nodes; the main sampling frequency is set, which can be adjusted within the range of 1 Hz to 100 Hz according to the dynamic response characteristics of the test system and the equipment bandwidth, and linear interpolation resampling is performed on the pore water pressure, vertical total stress, lateral total stress, water inflow and water outflow, and zero-order hold is adopted for the groundwater level, volumetric water content, water temperature and valve opening; temperature compensation and calibration conversion are performed, the pore water pressure, volumetric water content, water inflow and water outflow are corrected by using the same point temperature data, and the baseline correction is performed according to the static water state to eliminate the zero drift; filtering and abnormal rejection are performed on the three-dimensional coupling test data of the water and soil machine, sliding mean smoothing filter is used to remove high-frequency noise, and mutation and distortion points are identified through abnormal limit value and spatial consistency detection, that is, abnormal samples are automatically judged according to the upper and lower limits of physical parameters and the difference threshold between adjacent measuring points, and the distortion points are corrected by using the time series interpolation completion method to avoid the interference of abnormal signals on the overall analysis result; the three-dimensional coupling test data of the water and soil machine is subjected to Z-score standardization and dimensionless minimum maximum normalization processing; a coupling test database is established, the data are organized according to the time stamp and spatial coordinate double index structure, and the original and preprocessed three-dimensional coupling test data of the water and soil machine are structured and stored in the coupling test database.

[0034] AsFigure 3 As shown, it is a configuration diagram of a shield tunnel mechanical and electrical numerical control and test integrated model test platform. The test platform mainly includes a soil box, a shield machine, a counterforce frame, a control console and a data acquisition system. The soil box is used to build a controllable three-dimensional water-soil coupling test environment, and the inside can be filled with test soil with adjustable density and water content. The shield machine is arranged at the front end of the soil box, used to simulate the behavior of cutterhead propulsion, soil removal and seepage disturbance in the shield tunneling process. The counterforce frame is used to provide stable counterforce support for the shield machine to realize controllable loading of the thrust force. The control console is connected with the shield machine and the counterforce frame through hydraulic and electrical control lines, used to adjust the propulsion speed, flow and pressure parameters. The data acquisition system is arranged at the bottom and both sides of the soil box, electrically connected with various sensors, used to collect real-time water-soil machine three-dimensional coupling test data including pore water pressure, water content, stress and flow, and transmit the test data to the coupling analysis and closed-loop control module of the computer end. Through the above structural configuration, the test platform can realize the dynamic coupling simulation and data closed-loop feedback among water, soil and structure in the shield tunneling process under laboratory conditions, and provide accurate experimental support for the study of the stress, seepage and water content evolution in the shield construction process in complex water-rich strata.

[0035] In the embodiment, high space-time synchronization and physically reliable collection of multi-source test data are realized, each parameter is obtained by a real sensor to avoid experience estimation error; the data stability and noise resistance are improved through joint time service, temperature compensation and sliding filter; abnormal detection and interpolation correction ensure data continuity and reliability; after standardization and normalization, different physical quantity scales are unified, the constructed space-time double index database provides accurate data support for subsequent three-dimensional field reconstruction and coupling analysis, and the accuracy and repeatability of the test are significantly improved.

[0036] Specifically, the process of mapping the pre-processed three-dimensional coupled water-soil machine test data to a unified three-dimensional grid and reconstructing the multi-distribution fields of pore pressure, water content, stress, and mean effective stress is as follows: The pre-processed three-dimensional coupled water-soil machine test data is mapped to a unified three-dimensional grid according to spatial coordinates. The three-dimensional grid is constructed using a regular cubic element division method. The element size is adaptively determined according to the geometric scale of the specimen and the distribution density of the sensing points. The grid nodes correspond one-to-one with the coordinates of the sensing points, and all data channels are synchronized based on timestamps. Three-dimensional interpolation is performed on pore water pressure, volumetric water content, vertical total stress, and lateral total stress, respectively. Cubic spline interpolation is used to complete the data in areas with missing or non-measuring points to obtain continuously distributed three-dimensional field information, and the pore pressure field, water content field, and stress field components are constructed. Through calculation... The ratio of water content to porosity yields the saturation value at each spatial point, ranging from 0 to 1. This saturation value reflects the water content of the soil in different areas. A saturation field is generated using spatial interpolation. The total head is obtained by converting the pore water pressure at different spatial locations into water density and gravitational acceleration, and then superimposing the elevations. The water density is taken as the measured value under experimental conditions, and the gravitational acceleration is taken as the standard constant 9.81 m / s². The difference in total head between the inlet and outlet measuring points is taken as the head difference. Based on the inflow rate, outlet flow rate, and head difference, the equivalent permeability coefficient for each region is calculated according to Darcy's law. The effective cross-sectional area of ​​the sample and the flow path length are introduced into the Darcy calculation, and boundary effects are corrected using an experimental calibration factor. The basic form is... ,in, For seepage flow, The equivalent permeability coefficient, For the flow cross-sectional area, Due to head difference, The flow path length is used; and the equivalent permeability coefficient is corrected for viscosity using water temperature data. The viscosity correction coefficient is calculated based on the empirical formula of water temperature and dynamic viscosity to reflect the actual impact of temperature changes on seepage characteristics, forming an equivalent permeability coefficient field. Based on the vertical total stress, lateral total stress, and pore water pressure data, the effective stress in the vertical and lateral directions is calculated respectively, that is, the pore water pressure at each measuring point is subtracted from the total stress to obtain the distribution of vertical and lateral effective stress. The vertical effective stress is averaged with twice the lateral effective stress to obtain the average effective stress value at each spatial point. The average effective stress is used to comprehensively reflect the changing trend of the principal stress state in the three-dimensional stress field, and can characterize the degree of soil stress balance. The average effective stress field is constructed by spatial interpolation method. Finally, a multi-distribution field that can continuously describe the changes in hydraulic and stress states in each region is formed, providing basic data support for subsequent coupled balance analysis and closed-loop control.

[0037] In this implementation scheme, by establishing a unified three-dimensional mesh and multi-physics interpolation reconstruction, the spatial continuous expression of multi-source parameters such as pore pressure, water content, stress, and saturation is realized, which significantly improves the data resolution and the integrity of field variables. The introduction of Darcy's law and temperature viscosity correction makes the permeability characteristics closer to the real working conditions. Through the calculation of average effective stress and the fusion of multi-distribution fields, the coupling state of soil stress and seepage can be accurately reflected, supporting the fine assessment and dynamic control of water-soil coupling imbalance, and improving the realism and repeatability of the experimental simulation.

[0038] Specifically, the process of calculating various residual parameters and evaluating the three-dimensional water-soil coupling equilibrium through spatial difference and time derivative of multi-distribution fields is as follows: Based on the pore pressure field, saturation field, equivalent permeability coefficient field, and mean effective stress field, a spatiotemporal discrete calculation framework is established with time step Δt and spatial grid steps Δx, Δy, and Δz as discrete units to ensure the numerical stability and repeatability of derivative calculations. The finite difference method is used to perform derivative operations on the continuous time series and spatial grid to calculate the rate of change of volumetric water content, the rate of change of pore water pressure, and the rate of change of mean effective stress. In the spatial dimension, the head gradient, saturation gradient, and mean effective stress gradient at each point are calculated using neighborhood difference, where the neighborhood difference range is determined according to the grid. The grid resolution is automatically expanded by 1 to 2 cells to enhance the smoothness and noise resistance of gradient calculations. A flux vector field is obtained by multiplying the equivalent permeability coefficient and the total head gradient point by point. This flux vector field describes the direction and intensity of water flow transmission in each spatial cell per unit time. The seepage flux divergence is obtained by discretizing the 3D grid. The mass conservation residual is obtained by dividing the difference between the inflow and outflow rates by the sample volume and subtracting the rate of change of volumetric water content. This mass conservation residual reflects the difference in water volume balance per unit volume and is an important indicator for determining seepage equilibrium. The seepage flux divergence is added to the rate of change of volumetric water content to obtain the seepage equation residual, which characterizes the degree of deviation between the theoretical seepage model and actual observations. The stress-pore pressure consistency residual is obtained by adding the product of the average effective stress change rate and the Biot coefficient and the pore water pressure change rate. This reflects the consistency between soil stress and pore water pressure over time and is an important basis for judging the coupling effect. The modulus of the saturation gradient and the modulus of the average effective stress gradient are calculated, and the spatial coupling gradient ratio is obtained by dividing the modulus of the saturation gradient by the sum of the constant and the modulus of the average effective stress gradient. This ratio is used to quantify the synergistic characteristics of spatial changes in water distribution and stress distribution. Based on the same moment, the spatial median of the mass conservation residual distribution is taken as the mass conservation benchmark value. The spatial median of the seepage equation residual distribution is taken as the seepage residual benchmark value. The stress-pore pressure ratio is taken as the... The spatial median of the uniformity residual distribution is used as the benchmark value for stress-pore pressure consistency; the spatial median of the spatial coupling gradient ratio distribution is used as the benchmark value for the spatial coupling gradient ratio; all four benchmark values ​​are used to eliminate the systematic bias in the spatial distribution, so that each residual parameter can be compared and integrated under a unified scale; the mass conservation residual is divided by the mass conservation benchmark value, the seepage equation residual is divided by the seepage residual benchmark value, the stress-pore pressure consistency residual is divided by the stress-pore pressure consistency benchmark value, and the spatial coupling gradient ratio is divided by the spatial coupling gradient ratio benchmark value, respectively, to obtain four ratios. The sum of squares of the four ratios is calculated, and the square root is taken to obtain the three-dimensional water-soil coupling imbalance index, which reflects the comprehensive deviation of multi-source residuals and is used to quantify the current overall imbalance.The negative of the three-dimensional water-soil coupling imbalance index term is used as the exponent for natural exponent calculation. Taking the negative ensures that the imbalance value increases monotonically with the residual. Subtracting the natural exponent calculation result from a constant yields the comprehensive three-dimensional water-soil coupling imbalance value, ranging from 0 to 1. A value closer to 1 indicates a higher degree of coupling imbalance, while a value closer to 0 indicates a balanced state. This value can serve as the core criterion for subsequent closed-loop control and hydraulic regulation.

[0039] The specific formula for the comprehensive value of the three-dimensional water-soil coupling imbalance is as follows:

[0040] ;

[0041] In the formula, This represents the comprehensive value of three-dimensional soil-water coupling imbalance, used to comprehensively characterize the degree of dynamic incoordination between water migration, pore water pressure changes, effective stress response, and spatial coupling characteristics in the soil, and quantitatively describe the overall equilibrium state of soil hydraulic coupling. When it approaches 0, it is in a state of coordinated equilibrium. When the value approaches 1, it indicates a significant imbalance in the hydraulic response, and a decrease in the stability of the earth pressure balance during the shield tunneling test. Indicates the inflow rate; Indicates the outflow rate; Indicates the volume of the sample; This indicates the rate of change of volumetric moisture content; This represents the reference value for the conservation of mass; It represents the residual of mass conservation, characterizes the balance between the inflow and outflow of water and the change in soil water storage, and determines whether there is leakage, poor sealing and abnormal accumulation of water content; Represents the equivalent permeability coefficient; Indicates the total head; Indicates the diffusion of permeation flux; This represents the baseline value for seepage residual; It represents the residual of the seepage equation, measures the degree of matching between the seepage driving force and the change in water storage, and reflects the coordination between the local seepage direction and the permeability. This represents the average effective rate of change of stress; Represents the Biot coefficient; This represents the rate of change of pore water pressure; Indicates the benchmark value for stress pore pressure consistency; It represents the stress-pore pressure consistency residual, reflects the time coupling relationship between stress change and pore pressure response, determines whether stress and pore pressure respond synchronously, and reveals mechanical hysteresis and overpressure phenomena. Represents the magnitude of the saturation gradient; The modulus representing the average effective stress gradient; This represents the spatial coupling gradient ratio to the baseline value; This represents the spatial coupling gradient ratio.

[0042] In this embodiment, Table 1 is a comprehensive data table of three-dimensional water-soil coupling imbalance. The table displays the mass conservation residual, seepage equation residual, stress-pore pressure consistency residual, spatial coupling gradient ratio, mass conservation baseline value, seepage residual baseline value, pore pressure consistency baseline value, spatial coupling gradient ratio baseline value, and three-dimensional water-soil coupling imbalance comprehensive value at a certain measuring point at five different times. Specifically, at time 1, the mass conservation residual is 0.94, the seepage equation residual is 1.01, the stress-pore pressure consistency residual is 1.08, the spatial coupling gradient ratio is 0.97, the mass conservation baseline value is 0.94, the seepage residual baseline value is 1.01, and the pore pressure consistency baseline value is... The value is 1.08, the spatial coupling gradient ratio benchmark value is 0.97, and the comprehensive value of three-dimensional water-soil coupling imbalance is 0.865; the mass conservation residual corresponding to time 2 is 1.06, the seepage equation residual is 1.09, the stress-pore pressure consistency residual is 1.13, the spatial coupling gradient ratio is 1.03, the mass conservation benchmark value is 1.00, the seepage residual benchmark value is 1.07, the stress-pore pressure consistency benchmark value is 1.10, the spatial coupling gradient ratio benchmark value is 1.00, and the comprehensive value of three-dimensional water-soil coupling imbalance is 0.874; the mass conservation residual corresponding to time 3 is 1.19. The residuals of the seepage equation are 1.23, the stress-pore pressure consistency residuals are 1.29, the spatial coupling gradient ratio is 1.12, the mass conservation baseline value is 1.06, the seepage residual baseline value is 1.13, the stress-pore pressure consistency baseline value is 1.13, the spatial coupling gradient ratio baseline value is 1.03, and the comprehensive value of the three-dimensional water-soil coupling imbalance is 0.891. At time 4, the residuals of the mass conservation equation are 1.33, the seepage equation residuals are 1.39, the stress-pore pressure consistency residuals are 1.47, the spatial coupling gradient ratio is 1.17, the mass conservation baseline value is 1.19, and the seepage residuals are... The baseline value is 1.29, the stress-pore pressure consistency baseline value is 1.27, the spatial coupling gradient ratio baseline value is 1.12, and the comprehensive value of three-dimensional water-soil coupling imbalance is 0.889. The mass conservation residual corresponding to time 5 is 1.16, the seepage equation residual is 1.10, the stress-pore pressure consistency residual is 1.21, the spatial coupling gradient ratio is 1.06, the mass conservation baseline value is 1.19, the seepage residual baseline value is 1.29, the stress-pore pressure consistency baseline value is 1.20, the spatial coupling gradient ratio baseline value is 1.10, and the comprehensive value of three-dimensional water-soil coupling imbalance is 0.851.

[0043] Table 1. Comprehensive Values ​​of Three-Dimensional Soil-Water Coupling Imbalance

[0044]

[0045] like Figure 4As shown, this is a diagram illustrating the co-evolution of the three-dimensional soil-water coupling residuals and the comprehensive imbalance value. It displays the dynamic changes in the mass conservation residuals, seepage equation residuals, stress-pore pressure consistency residuals, normalized ratios of spatial coupling gradient ratios, and the comprehensive three-dimensional soil-water coupling imbalance value at five time points. Different colored curves represent the temporal changes of the four types of normalized residual ratios, and the black dashed line represents the overall trend of the comprehensive three-dimensional soil-water coupling imbalance value at the measuring points. Based on Table 1 and... Figure 4 It can be seen that the normalized ratios of each residual all show a synchronous upward trend from time 1 to time 3, indicating that they are in a process of gradual imbalance. After time 3, some of the normalized ratios of the residuals tend to stabilize or decrease, indicating that hydraulics and stress are gradually rebalancing. The three-dimensional water-soil coupling imbalance comprehensive value is basically consistent with the trend of each normalized ratio of the residuals. The change is small but reflects the overall coupling adjustment trend. The trend in the figure shows that the experiment can truly reflect the synergistic evolution law between water, soil and stress in complex water-rich strata, and has good dynamic response consistency and controllability.

[0046] In this implementation scheme, by introducing a spatiotemporal discrete computing framework and multi-distribution field difference analysis, a unified quantitative description of pore pressure, stress, and seepage behavior is achieved, which can accurately identify the non-equilibrium state of the water and soil system in the time and space dimensions. By constructing multiple types of residual parameters and fusing them into a comprehensive value of imbalance, the complex hydraulic-stress coupling relationship has a calculable and evaluable quantitative index, thereby providing a scientific basis for subsequent dynamic regulation and closed-loop control, and significantly improving the diagnostic accuracy and response sensitivity of the experiment.

[0047] Specifically, the process of determining the hydraulic stress state and implementing flow and pressure balance control is as follows: Based on the three-dimensional water-soil coupling imbalance comprehensive value, the central control module performs spatial distribution visualization and threshold comparison analysis on the real-time calculated three-dimensional water-soil coupling imbalance comprehensive value, constructing a three-dimensional water-soil coupling imbalance comprehensive value distribution field. The distribution field uses grid cells as the basic calculation unit, and the three-dimensional water-soil coupling imbalance comprehensive value in each cell is used to reflect the degree of hydraulic and stress coordination in a local area. When the three-dimensional water-soil coupling imbalance comprehensive value in any area is detected to be higher than the balance threshold, it is determined to be a local hydraulic stress imbalance state, triggering the boundary control loop. The central control module generates control commands and sends them to the hydraulic pumps and valve actuators to achieve closed-loop regulation of corresponding flow and pressure. If the comprehensive value of the three-dimensional water-soil coupling imbalance on the inflow side is higher than that on the outflow side, pressure reduction control is implemented at the inflow end to reduce the opening of the inflow valve, thereby reducing the inflow pressure and the fluid infiltration rate, thus weakening the soil disturbance caused by the excessively high local hydraulic gradient. When the comprehensive value of the three-dimensional water-soil coupling imbalance on the outflow side is higher than that on the inflow side, discharge increase control is implemented at the outflow end to increase the opening of the outflow valve. At the same time, the flow distribution of the hydraulic pump outlet branch is coordinated to restore pressure balance through short-term drainage, avoiding the formation of reverse seepage or local pore pressure accumulation. To prevent control jitter caused by frequent threshold crossings when approaching the equilibrium threshold, a hysteresis control range and dead zone threshold are preferably set. The hysteresis control interval is used to delay the triggering of control actions within a range where the comprehensive value of the three-dimensional water-soil coupling imbalance is close to the equilibrium threshold, providing a buffer for the control output to switch up and down. The dead zone threshold is used to keep the control output unchanged within small disturbances, ensuring that minor numerical fluctuations do not cause malfunctions. The range of small disturbances can be adaptively adjusted based on the sampling noise variance. In addition, to avoid frequent actions of the actuator, the central control module sets a minimum execution step size parameter, which is the minimum adjustment unit for valve opening and pump speed regulation. When the calculated adjustment command amplitude is less than the minimum execution step size, the current state remains unchanged, thereby achieving anti-jitter, delayed response, and life protection for the actuator. If the comprehensive value of the three-dimensional water-soil coupling imbalance exceeds the equilibrium threshold for a duration exceeding the allowable time threshold, a precision water pump will perform a staged injection and drainage operation. The staged injection and drainage process is carried out in segments over time, and the injection and drainage rate of each stage is automatically corrected according to the trend of the three-dimensional water-soil coupling imbalance comprehensive value in the previous stage. When the three-dimensional water-soil coupling imbalance comprehensive value shows a downward trend, the injection and drainage rate is gradually reduced to avoid over-adjustment; when the three-dimensional water-soil coupling imbalance comprehensive value decreases slowly or fluctuates more, the flow rate output is increased to accelerate recovery. At the same time, through threshold constraints and safety limits, the injection and drainage process is ensured to be smooth and without pressure surges, achieving gradual and stable control of pressure recovery and dynamic balance of hydraulic stress. When the comprehensive value of the three-dimensional water-soil coupling imbalance across the entire field is less than or equal to the equilibrium threshold, it is determined to be a hydraulic stress coordinated and stable state, and the current valve opening and flow rate output are maintained; at the same time, the comprehensive value of the three-dimensional water-soil coupling imbalance at each monitoring point, as well as the changes in valve opening, influent flow rate, and effluent flow rate, are written into the coupling test database.

[0048] In this implementation plan, by constructing a three-dimensional water-soil coupling imbalance comprehensive value distribution field and combining it with dynamic threshold comparison, the accurate identification and graded response of local hydraulic stress imbalance state are realized. Through the linkage control of the inlet and outlet water ends and the graded injection and drainage strategy, the hydraulic balance can be quickly restored while maintaining stability, avoiding abnormal accumulation of pore pressure and stress mutation. At the same time, by combining database recording and closed-loop control, the real-time adjustment, traceability and self-learning optimization of the test process are realized, which significantly improves the response accuracy and experimental reproducibility.

[0049] Specifically, when the hydraulic stress state is unbalanced, the process of evaluating and correcting the flux adjustment amount by combining three-dimensional water-soil coupling balance and multiple residual parameters is as follows: The distribution field of the three-dimensional water-soil coupling imbalance comprehensive value is received; the average of the global three-dimensional water-soil coupling imbalance comprehensive value is calculated to obtain the three-dimensional water-soil coupling imbalance average value, which reflects the overall degree of imbalance between the hydraulic and stress fields; simultaneously, the average values ​​of the three-dimensional water-soil coupling imbalance comprehensive values ​​at the inlet and outlet ends and in the adjacent area are calculated to obtain the average imbalance comprehensive value at the inlet end and the average imbalance comprehensive value at the outlet end, in order to distinguish the asymmetric imbalance characteristics at the boundary and provide a directional basis for boundary adjustment; the mass conservation residual, seepage equation residual, stress-pore pressure consistency residual, and spatial coupling of all measuring points are obtained. The gradient ratio is calculated, and the average values ​​are obtained to obtain the mean values ​​of the mass conservation residual, seepage equation residual, stress-pore pressure consistency residual, and spatial coupling gradient ratio, respectively, to comprehensively evaluate the overall conservation, seepage consistency, pore pressure-stress coordination, and spatial gradient coupling. By integrating the product of the equivalent permeability coefficient field and the total head along the normal component at the inlet and outlet boundaries, with the normal direction of the integration grid determined by the boundary normal of the physical model box, the inlet and outlet boundary fluxes are obtained to reflect the actual seepage flow output capacity at both ends. A sliding time window, with its duration automatically adjusted according to the sampling frequency and ranging from 30 to 120 seconds, is used to smooth out the influence of random fluctuations and filter the inlet and outlet flow. The median of the average fluxes at the inlet and outlet boundaries is used to obtain the flux reference value. The rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance is calculated using the finite difference method, and the median of the comprehensive mean of the three-dimensional water-soil coupling imbalance is selected to obtain the comprehensive coupling imbalance reference value. This comprehensive coupling imbalance reference value is used as a reference scale for dynamically calibrating the system's imbalance changes. Simultaneously, the arithmetic mean of the average inflow and outflow rates within the sliding time window is taken to obtain a reference flux value, which serves as the amplitude constraint benchmark for the regulation and control output. The difference between the average comprehensive imbalance value at the inlet and outlet is calculated to obtain the imbalance term, reflecting the degree of hydraulic stress imbalance in the boundary region. The difference between the flux at the inlet and outlet is calculated and divided by the flux reference value. The boundary flux deviation term is obtained to measure the boundary asymmetry of seepage flux; the imbalance change rate term is obtained by dividing the rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance by the comprehensive benchmark value of the coupling imbalance, which describes the dynamic trend of imbalance change; the ratios of the mean of the mass conservation residual to the mass conservation benchmark value, the ratio of the mean of the seepage equation residual to the seepage residual benchmark value, the ratio of the mean of the stress-pore pressure consistency residual to the stress-pore pressure consistency benchmark value, and the ratio of the mean of the spatial coupling gradient ratio to the spatial coupling gradient ratio benchmark value are calculated. These four ratios are used to normalize the dimensional differences of different residual indices in order to unify the measurement system; the square root of the sum of the squares of the four ratios is used to obtain the coupling weight term, which characterizes the comprehensive contribution weight of various coupling imbalance effects.Multiplying the sum of the imbalance term, boundary flux deviation term, and imbalance change rate term by the coupling weight term achieves dynamic multi-factor coupled regulation, ensuring that the flux correction direction aligns with the overall imbalance trend. Substituting these into the hyperbolic tangent function for calculation and nonlinear shaping limits the output signal to ±1, achieving a smooth dynamic response and amplitude constraint. Preferably, the introduction of the hyperbolic tangent function not only serves as numerical normalization and amplitude limiting but also compensates for the saturation zone and hysteresis characteristics of hydraulic pumps and electrically controlled valves during actual execution. Specifically, when the control command approaches the pump or valve's limit opening range, the tanh function output tends to flatten, suppressing nonlinear amplification of the signal in the limit zone and preventing the actuator from entering the mechanical saturation zone. In the smaller signal range, the tanh curve has a steeper slope, allowing for early activation compensation for pump and valve response hysteresis, improving regulation sensitivity and response speed, thereby achieving bidirectional compensation for hardware hysteresis and proportional valve dead zone. Multiplying this by the current reference flux value yields the corrected flux adjustment value, which serves as the target adjustment command input for subsequent hydraulic pump and valve actuators, realizing a closed-loop correction process for automatic injection and drainage control. ;

[0050] The specific formula for correcting the flux adjustment value is as follows:

[0051] ;

[0052] In the formula, This indicates the corrected flux adjustment value, which is used in shield tunnel water-soil coupling model tests to automatically correct the flux at the inlet and outlet water boundaries based on the degree of multi-field coupling imbalance, so as to realize the adaptive pressure and flow balance control of the test. The execution module acts on the valve flow control in real time. This represents the current reference flux value, indicating the average transport capacity of the current influent and effluent, and is used to limit the adjustment range. This represents the average comprehensive value of imbalance at the inlet end; This represents the average comprehensive value of imbalance at the outlet. Indicates the inlet boundary flux; Indicates the flux at the outlet boundary; Indicates the baseline value for flux; This represents the rate of change of the comprehensive mean value of the three-dimensional water-soil coupling imbalance. This represents the comprehensive baseline value for coupling imbalance; This represents the mean of the mass conservation residuals; This represents the mean residual of the seepage equation; This represents the mean residual value for stress pore pressure consistency. This represents the mean of the spatial coupling gradient. This represents the reference value for the conservation of mass; This represents the baseline value for seepage residual; Indicates the benchmark value for stress pore pressure consistency; This represents the spatial coupling gradient ratio to the baseline value; The imbalance term represents the difference in the comprehensive value of the three-dimensional water-soil coupling imbalance in the inlet and outlet water regions, which is used to reflect the unevenness of stress and hydraulic coupling at both ends of the soil. It represents the boundary flux deviation term, which is normalized by the difference between the inlet and outlet boundary fluxes. It measures the degree of mismatch in the current seepage flux transmission and is a direct feedback quantity of the flow boundary. The term representing the rate of change of imbalance characterizes the rate of change of the combined value of coupled imbalance over time, reflecting dynamic response capability and fluctuation trend; The term represents the coupling weight, which is the normalized ratio of the four types of residuals: mass conservation, seepage equation, consistency, and spatial gradient. It also represents the relative contribution weight of each type of imbalance in the overall regulation.

[0053] In this implementation scheme, a quantifiable and self-correcting flux regulation mechanism is established through comprehensive analysis of multi-source residual information and boundary flux characteristics. This enables dynamic assessment and refined control of the imbalance state in complex water-soil coupled systems. By introducing a sliding time window and nonlinear constraint functions, the regulation process is made smooth and stable, effectively preventing over-adjustment and oscillations, improving the response accuracy and convergence speed of flux regulation, thereby achieving automatic hydraulic stress equilibration and long-term operational stability.

[0054] Specifically, the process of driving the hydraulic pump and valve actuator to regulate the inlet and outlet water flow is as follows: When a local hydraulic stress imbalance is detected, the corrected flux regulation value is calculated and written into the coupling test database, and the corrected flux regulation value is transmitted to the hydraulic pump and valve actuator in real time; when the corrected flux regulation value is greater than 0, the actuator at the inlet end is controlled to increase the flow output, that is, the pump speed is increased by controlling the hydraulic pump frequency converter, so that the inlet flow increases according to the proportional gain coefficient, and the valve opening at the outlet end is adjusted synchronously to maintain the overall pressure balance and prevent local overpressure; when the corrected flux regulation value is less than 0, the actuator performs the opposite action, automatically reducing the hydraulic pump output pressure, reducing the inlet flow rate, reducing the inlet pressure and reducing the outlet discharge rate, and achieving the balance regulation of the back pressure at the discharge end through synchronous control to avoid soil disturbance caused by instantaneous pressure drop; at the same time, the change rate of the three-dimensional water-soil coupling imbalance comprehensive mean is monitored, and when the change rate of the three-dimensional water-soil coupling imbalance comprehensive mean decreases below the change threshold, the change is controlled. The system locks the current flow output, maintaining the current pump speed and valve opening, entering a steady-state holding mode to prevent secondary disturbances caused by over-correction. When the corrected flux adjustment value exhibits continuous reverse changes or the amplitude of the corrected flux adjustment value exceeds the proportional threshold and fails to converge, it is determined to be in an oscillation or over-adjustment state. Continuous reverse changes refer to the corrected flux adjustment value alternating signs within three or more adjacent sampling periods, i.e., fluctuations such as "positive, negative, positive" or "negative, positive, negative." The amplitude of the corrected flux adjustment value exceeding the proportional threshold and failing to converge refers to the absolute value of the corrected flux adjustment value exceeding 10% of the current reference flux value, and the variance exceeding the stability threshold within several consecutive time windows. The system automatically triggers anti-vibration control logic, suppressing oscillations by reducing the adjustment step size, for example, by decreasing the proportional factor by 0.5 and extending the sampling integral time constant. This limits the adjustment step size, entering a limited-amplitude self-stabilization mode. In this mode, the flux adjustment curve automatically and smoothly transitions, ensuring the stability and safety of the overall response.

[0055] In this implementation scheme, by dynamically judging and limiting the amplitude self-stabilizing control of the flux adjustment value, the refined adjustment and real-time closed-loop stability of the hydraulic pump and valve are achieved. Through continuous monitoring of flux change trends and quantitative identification of oscillation and over-adjustment states, anti-vibration logic can be automatically triggered in the early stage of fluctuations, dynamically reducing the adjustment step size and smoothing the output flux curve, thereby effectively avoiding overshoot and oscillation of flow and pressure, improving the response stability and control accuracy of the adjustment process, and ensuring the safe and stable operation of the three-dimensional water-soil coupling system under complex working conditions.

[0056] Specifically, the process for evaluating the consistency of dynamic response based on the three-dimensional water-soil coupling balance change rate and the modified flux regulation change rate is as follows: The modified flux regulation value and the three-dimensional water-soil coupling imbalance comprehensive mean are received. A sliding time window, with a window length adjustable from 30s to 120s depending on the response frequency, is used to smooth short-term fluctuations and capture trend change characteristics. The change rate sequence of the three-dimensional water-soil coupling imbalance comprehensive mean is calculated. The change rate is calculated using the difference method, defined as the difference between two adjacent sampling points divided by the time interval, to characterize the instantaneous change rate of the imbalance comprehensive mean. The standard deviation and average change rate of the three-dimensional water-soil coupling imbalance comprehensive mean are also calculated. The standard deviation characterizes the degree of fluctuation in the change, while the average change rate reflects the overall trend. The response trend is analyzed; simultaneously, the rate of change of the corrected flux regulation value is calculated, which is the difference ratio of the corrected flux regulation value within a continuous sampling period, to reflect the dynamic sensitivity of the flow regulation process; the coupling change deviation value is obtained by subtracting the average change rate from the current three-dimensional water-soil coupling imbalance comprehensive mean change value, which measures the instantaneous deviation of the current coupling state from the overall trend. The larger the value, the more significant the deviation from the equilibrium trend; the flux response value is obtained by multiplying the current corrected flux regulation value change rate by the proportional regulation weight factor; the absolute difference between the coupling change deviation value and the flux response value is calculated and divided by the sum of the standard deviation of the three-dimensional water-soil coupling imbalance comprehensive mean change rate and the stability constant value. The stability constant value is used to avoid numerical instability problems when the denominator approaches zero, and is set to a value of [value missing]. The normalized dynamic difference value is obtained, which is used to comprehensively measure the real-time consistency between coupling changes and flux response. The smaller the value, the more synchronized the trends of the two changes are. The negative sign of the normalized dynamic difference value is taken as the exponent, and natural exponentiation is performed to obtain the dynamic response consistency value. The dynamic response consistency value is between 0 and 1. A value close to 1 indicates a high degree of response consistency, while a value close to 0 indicates dynamic decoupling or response mismatch.

[0057] The specific formula for the dynamic response consistency value is as follows:

[0058] ;

[0059] In the formula, This represents the dynamic response consistency value, used to quantify the synchronicity between flux regulation behavior and the three-dimensional water-soil coupling dynamic change process in the experiment; This represents the current rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance, used to reflect the dynamic trend of water-soil interaction. The average rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance is used to measure the overall change benchmark within the sliding time window; This represents the rate of change of the current corrected flux regulation value, used to characterize the regulation speed of hydraulic pumps and valves in flow control; The standard deviation of the comprehensive mean of the three-dimensional water-soil coupling imbalance is used to normalize the time fluctuation amplitude. This represents a stable constant value, used to prevent numerical instability when the denominator approaches zero. Its value is [value missing]. ; The proportional adjustment weight factor is obtained by adaptively fitting the data of the deviation value of coupling change and the rate of change of the corrected flux adjustment value within the sliding window using Huber loss and L2 regularized ridge regression algorithm. .

[0060] In this implementation scheme, a quantitative assessment of the consistency between water-soil coupling changes and flux regulation response is achieved through sliding time window and dynamic normalized difference analysis. It can identify the dynamic deviation between flow control and coupling equilibrium in real time, and smooth the difference response using a natural exponential function to avoid misjudgments caused by short-term fluctuation amplification. This method effectively improves the adaptive judgment capability of nonlinear response characteristics, making the hydraulic stress control process more stable and accurate, and providing a reliable basis for subsequent threshold optimization and closed-loop regulation.

[0061] Specifically, the process of updating parameters and correcting thresholds based on dynamic response consistency is as follows: The dynamic response consistency value is calculated, written into the coupled test database, and compared with the consistency threshold. When the dynamic response consistency is greater than or equal to the consistency threshold, it is determined to be in a stable state of consistency regulation, meaning the current flux response is highly matched with the water-soil coupling change, indicating that the output of the control algorithm has stability and convergence. The baseline values ​​corresponding to the current algorithm and each parameter are maintained, including the mass conservation baseline value, seepage residual baseline value, stress-pore pressure consistency baseline value, spatial coupling gradient ratio baseline value, flux baseline value, and comprehensive baseline value of coupling imbalance, to avoid unnecessary disturbance adjustments during the stable phase. When the dynamic response consistency is less than the consistency threshold, it indicates that the response has deviated or the regulation is lagging, requiring adaptive optimization to restore dynamic matching. The baseline values ​​corresponding to each parameter are updated using the median value of the parameter distribution within the sliding time window as the update target. The sliding time window is used to smooth out noise effects and extract parameter change trends. Adaptive adjustment is performed according to a weighted smoothing method, i.e., through a recursive parameter update formula: Where α is the smoothing coefficient, typically ranging from 0.1 to 0.3. This indicates the baseline value to be updated. The median value of the baseline distribution is used to achieve progressive self-learning correction of parameters. Simultaneously, based on historical data from the coupled experimental database, the correlation between the dynamic response consistency value and the rate of change sequence of the three-dimensional water-soil coupling imbalance comprehensive value is modeled and analyzed to identify the long-term evolution trend of dynamic coupling characteristics. Using a Bayesian optimization algorithm, with historical experimental data as prior information and system stability and response consistency as objective functions, Gaussian process regression is used as a surrogate model, and the radial basis function (RBF) is optimally selected. The kernel automatically updates noise variance and length-scale hyperparameters through maximum likelihood estimation to form a probabilistic prediction of the parameter space. During optimization, the equilibrium threshold is limited to 0.6 to 0.95, and the consistency threshold is limited to 0.7 to 0.98 to ensure that the optimization results are within a stable and controllable range. An optimization update is performed every 50 to 200 sampling periods, and the objective function value is recorded and backtested after each update. To avoid threshold oscillations caused by frequent updates, an optimization cooldown period is set, which is more than 5 times the duration of the sliding window. During the optimization cooldown period, parameters are frozen and not updated. Through the optimization mechanism, the equilibrium threshold and consistency threshold can be optimized and updated in long-term operation to balance the system response speed and stability, and gradually improve the global convergence performance of parameter adjustment.

[0062] In this implementation scheme, an adaptive optimization under different operating conditions is achieved by constructing a dynamic response consistency value comparison and self-learning parameter update mechanism. When response consistency decreases, the system can automatically identify the degree of deviation and perform smooth correction based on the median value of the parameter distribution within a sliding time window. Simultaneously, a Bayesian optimization algorithm is used to dynamically optimize and update the balance and consistency thresholds, thereby maintaining high stability and fast convergence during long-term operation. This effectively avoids over-adjustment and parameter drift problems, significantly improving the self-learning capability and overall control accuracy of the model testing platform.

[0063] Reference Figure 2As shown, the second aspect of the present invention provides an integrated model test platform for shield tunnel electromechanical numerical control and testing, applied to the aforementioned integrated model test method for shield tunnel electromechanical numerical control and testing, including: a data acquisition and preprocessing module for real-time acquisition of three-dimensional coupling test data of water and soil machinery, and preprocessing the three-dimensional coupling test data of water and soil machinery; a coupling analysis and balance evaluation module for mapping the preprocessed three-dimensional coupling test data of water and soil machinery to a unified three-dimensional grid, reconstructing the multi-distribution field of pore pressure, water content, stress, and mean effective stress; calculating multiple types of residual parameters and evaluating the three-dimensional water and soil coupling balance through the spatial difference and time derivative of the multi-distribution field, determining the hydraulic stress state, and executing the balance control of flow and pressure; a flow regulation and closed-loop control module for evaluating and correcting the flux adjustment amount in combination with the three-dimensional water and soil coupling balance and multiple types of residual parameters when the hydraulic stress state is unbalanced, and driving the hydraulic pump and valve execution unit to realize the regulation of inlet and outlet water flow; and a self-learning and threshold optimization module for evaluating the dynamic response consistency based on the change rate of the three-dimensional water and soil coupling balance and the change rate of the corrected flux adjustment amount, updating parameters and correcting the threshold according to the dynamic response consistency.

[0064] This implementation plan achieves intelligent control and quantitative analysis of the entire process of multi-field coupling between water, soil, and structure in shield tunneling model tests. Through modular architecture design, it enables a fully closed-loop operation from data acquisition, coupling analysis, and equilibrium determination to flow regulation and threshold self-learning optimization, significantly improving the automation and accuracy of the testing process. It can reflect the stress and seepage synergistic changes in shield tunneling under complex water-rich strata in real time, achieving precise regulation and dynamic equilibrium control of the hydraulic stress state, improving test reproducibility and safety, and providing experimental basis for shield tunneling parameter optimization and risk prediction.

[0065] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. As those skilled in the art will understand, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A test method for an integrated model of electromechanical numerical control and testing in shield tunnels, characterized in that, Includes the following steps: S1, real-time acquisition of three-dimensional coupled test data of the water and soil machine, and data preprocessing of the three-dimensional coupled test data of the water and soil machine; S2 maps the pre-processed three-dimensional coupling test data of water and soil machinery to a unified three-dimensional grid, reconstructs the multi-distribution field of pore pressure, water content, stress and mean effective stress; calculates various residual parameters and evaluates the three-dimensional water and soil coupling balance through the spatial difference and time derivative of the multi-distribution field, determines the hydraulic stress state, and executes the balance control of flow and pressure. S3, when the hydraulic stress state is unbalanced, combines the three-dimensional water-soil coupling balance and multiple residual parameters to evaluate and correct the flux adjustment amount, and drives the hydraulic pump and valve actuator to realize the adjustment of inlet and outlet water flow. S4. Based on the three-dimensional water-soil coupling balance change rate and the modified flux regulation change rate, the dynamic response consistency is evaluated, and the parameters are updated and the threshold is corrected according to the dynamic response consistency.

2. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process for preprocessing the real-time acquisition of the three-dimensional coupled test data of the soil and water conservancy machine is as follows: Real-time acquisition of three-dimensional coupled water and soil testing data, including: sample volume, measuring point elevation, porosity, Biot coefficient, groundwater level, pore water pressure, volumetric water content, total vertical stress, total lateral stress, influent flow rate, effluent flow rate, valve opening, soil temperature, and spatial coordinates and unified timestamp of each sensing point. The timing error of all sensor nodes is controlled through precise time synchronization; the main sampling frequency is set, and linear interpolation resampling is performed on pore water pressure, total vertical stress, total lateral stress, influent flow rate, and effluent flow rate; zero-order hold is used for groundwater level, volumetric water content, water temperature, and valve opening; temperature compensation and calibration conversion are performed, and pore water pressure, volumetric water content, influent flow rate, and effluent flow rate are corrected using temperature data at the same point; baseline correction is performed based on static water conditions to eliminate zero drift; filtering and anomaly removal are performed on the three-dimensional coupled test data of the water-soil machinery, using smoothing filtering to remove high-frequency noise, and identifying abrupt changes and distortion points through anomaly limit and spatial consistency detection; the three-dimensional coupled test data of the water-soil machinery are standardized and dimensionless normalized; a coupled test database is established, and the original and pre-processed three-dimensional coupled test data of the water-soil machinery are stored in the coupled test database.

3. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process of mapping the preprocessed three-dimensional coupled water and soil test data to a unified three-dimensional grid to reconstruct the multi-distribution fields of pore pressure, water content, stress, and mean effective stress is as follows: The pre-processed three-dimensional coupled water and soil test data were mapped to a unified three-dimensional grid according to spatial coordinates, and all data channels were synchronized based on timestamps; three-dimensional interpolation was performed on pore water pressure, volumetric water content, vertical total stress and lateral total stress respectively to construct pore pressure field, water content field and stress field components; The saturation value at each spatial point is obtained by calculating the ratio of volumetric water content to porosity, and a saturation field is generated using spatial interpolation. By measuring the pore water pressure at different spatial locations and combining it with the elevation of each measuring point, the total head is obtained by converting the pore water pressure at each measuring point into water density and gravitational acceleration and then superimposing the measuring point elevation. The difference between the total head at the measuring points at the inlet and outlet ends is taken as the head difference. Based on the inflow rate, outflow rate, and head difference, the equivalent permeability coefficient of each region is calculated according to Darcy's law. The equivalent permeability coefficient is then corrected for viscosity using water temperature data to form an equivalent permeability coefficient field. Based on the data of total vertical stress, total lateral stress, and pore water pressure, the effective stress in the vertical and lateral directions is calculated respectively. That is, the pore water pressure at the corresponding location is subtracted from the total stress at each measuring point to obtain the distribution of effective vertical stress and effective lateral stress. The effective vertical stress is averaged with twice the effective lateral stress to obtain the average effective stress value at each spatial point, and the average effective stress field is constructed by spatial interpolation.

4. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process of calculating multiple types of residual parameters and evaluating the three-dimensional water-soil coupling equilibrium through spatial difference and time derivative of multi-distribution fields is as follows: Based on the pore pressure field, saturation field, equivalent permeability coefficient field, and mean effective stress field, the finite difference method is used to perform derivative operations on the continuous time series and spatial grid to calculate the rate of change of volumetric water content, the rate of change of pore water pressure, and the rate of change of mean effective stress. In the spatial dimension, the head gradient, saturation gradient, and mean effective stress gradient at each point are calculated using neighborhood difference. The flux vector field is obtained by multiplying the equivalent permeability coefficient and the total head gradient point by point. The seepage flux divergence is obtained by discretizing the three-dimensional grid. The mass conservation residual is obtained by dividing the difference between the influent flow rate and the effluent flow rate by the sample volume and subtracting the rate of change of volumetric water content; the seepage flux divergence is added to the rate of change of volumetric water content to obtain the seepage equation residual; the stress-pore pressure consistency residual is obtained by adding the product of the average effective stress change rate and the Biot coefficient and the pore water pressure change rate; the modulus of the saturation gradient and the modulus of the average effective stress gradient are calculated, and the spatial coupling gradient ratio is obtained by dividing the modulus of the saturation gradient by the sum of the constant and the modulus of the average effective stress gradient. Based on the same moment, the spatial median of the mass conservation residual distribution is taken as the mass conservation benchmark value; the spatial median of the seepage equation residual distribution is taken as the seepage residual benchmark value; the spatial median of the stress-pore pressure consistency residual distribution is taken as the stress-pore pressure consistency benchmark value; and the spatial median of the spatial coupling gradient ratio distribution is taken as the spatial coupling gradient ratio benchmark value. Four ratios are obtained by dividing the mass conservation residual by the mass conservation benchmark value, the seepage equation residual by the seepage residual benchmark value, the stress-pore pressure consistency residual by the stress-pore pressure consistency benchmark value, and the spatial coupling gradient ratio by the spatial coupling gradient ratio benchmark value. The sum of squares of the four ratios is calculated, and the square root is taken to obtain the three-dimensional water-soil coupling imbalance index. The negative of the three-dimensional water-soil coupling imbalance index is used as the exponent for natural exponent calculation. The result of the natural exponent calculation is subtracted from the constant to obtain the comprehensive value of the three-dimensional water-soil coupling imbalance.

5. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process for determining the hydraulic stress state and performing flow and pressure balance control is as follows: Based on the comprehensive value of three-dimensional water-soil coupling imbalance, a distribution field of the comprehensive value of three-dimensional water-soil coupling imbalance is constructed. When the comprehensive value of three-dimensional water-soil coupling imbalance in any region is higher than the equilibrium threshold, it is determined to be a local hydraulic stress imbalance state, triggering the boundary control loop: if the comprehensive value of three-dimensional water-soil coupling imbalance on the inflow side is higher than that on the outflow side, pressure reduction control is implemented at the inflow end, reducing the opening of the inflow valve; if the comprehensive value of three-dimensional water-soil coupling imbalance on the outflow side is higher than that on the inflow side, discharge increase control is implemented at the outflow end, increasing the opening of the outflow valve to restore pressure balance through short-term drainage; if the comprehensive value of three-dimensional water-soil coupling imbalance is higher than the equilibrium threshold for a duration exceeding the time allowable threshold, the precision water pump performs a staged injection and drainage operation. When the overall three-dimensional water-soil coupling imbalance value is less than or equal to the equilibrium threshold, it is determined to be a hydraulic stress coordination and stability state, and the current valve opening and flow output are maintained. Simultaneously, the comprehensive value of the three-dimensional water-soil coupling imbalance at each monitoring point, as well as the changes in valve opening, inflow rate, and outflow rate, are written into the coupling test database.

6. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process for evaluating and correcting the flux adjustment amount when the hydraulic stress state is unbalanced, combining three-dimensional water-soil coupling balance and multiple types of residual parameters, is as follows: The system receives the distribution field of the three-dimensional water-soil coupling imbalance comprehensive value, calculates the average of the global three-dimensional water-soil coupling imbalance comprehensive value to obtain the three-dimensional water-soil coupling imbalance comprehensive mean value, and calculates the average of the three-dimensional water-soil coupling imbalance comprehensive values ​​at the inlet and outlet ends and in the adjacent area to obtain the average imbalance comprehensive value at the inlet end and the average imbalance comprehensive value at the outlet end. It also obtains the mass conservation residual, seepage equation residual, stress-pore pressure consistency residual, and spatial coupling gradient ratio at all measuring points, and calculates the average of these values ​​to obtain the average mass conservation residual, the average seepage equation residual, the average stress-pore pressure consistency residual, and the average spatial coupling gradient ratio. Finally, it calculates the inlet end boundary flux and the outlet end boundary flux by integrating the product of the equivalent permeability coefficient field and the total head along the normal component at the inlet and outlet end boundaries. Based on the sliding time window, the median of the average values ​​of the inlet boundary flux and the outlet boundary flux is used to obtain the flux benchmark value. The rate of change of the three-dimensional water-soil coupling imbalance comprehensive mean is calculated by the difference method, and the median of the three-dimensional water-soil coupling imbalance comprehensive mean is used to obtain the coupling imbalance comprehensive benchmark value. At the same time, the arithmetic mean of the average values ​​of the inlet flow and the outlet flow within the sliding time window is taken to obtain the reference flux value. The imbalance difference term is obtained by calculating the difference between the average comprehensive imbalance value at the inlet and the average comprehensive imbalance value at the outlet. The boundary flux deviation term is obtained by calculating the difference between the flux at the inlet and the flux at the outlet and dividing it by the flux reference value. The imbalance change rate term is obtained by dividing the rate of change of the three-dimensional water-soil coupling imbalance mean by the coupled imbalance reference value. The coupling weight term is obtained by calculating the ratio of the mean of the mass conservation residual to the mass conservation reference value, the ratio of the mean of the seepage equation residual to the seepage residual reference value, the ratio of the mean of the stress-pore pressure consistency residual to the stress-pore pressure consistency reference value, and the ratio of the mean of the spatial coupling gradient ratio to the spatial coupling gradient ratio reference value. The square root of the sum of the squares of the four ratios is obtained. The coupling weight term is obtained by multiplying the sum of the imbalance difference term, the boundary flux deviation term, and the imbalance change rate term by the coupling weight term, substituting it into the hyperbolic tangent function, and multiplying it by the current reference flux value.

7. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process by which the driving hydraulic pump and valve actuator achieve the regulation of inlet and outlet water flow is as follows: When a local hydraulic stress imbalance is detected, the corrected flux adjustment value is calculated and written into the coupled test database, and the corrected flux adjustment value is transmitted to the hydraulic pump and valve actuator in real time. When the corrected flux adjustment value is greater than 0, the actuator at the inlet end is controlled to increase the flow output, and the valve opening at the outlet end is adjusted synchronously. When the corrected flux adjustment value is less than 0, the actuator performs the opposite action, reducing the inlet pressure and decreasing the outlet discharge rate. Simultaneously monitor the rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance. When the rate of change of the comprehensive mean of the three-dimensional water-soil coupling imbalance decreases to below the change threshold, lock the current flow output. When the corrected flux adjustment value shows continuous reverse change or the amplitude of the corrected flux adjustment value exceeds the proportional threshold and does not converge, it is determined to be an oscillation or over-adjustment state. The adjustment step size is then limited, and the mode of amplitude limiting self-stabilization is entered.

8. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process for evaluating the consistency of dynamic response based on the three-dimensional water-soil coupling equilibrium change rate and the corrected flux regulation change rate is as follows: Receive the corrected flux adjustment value and the three-dimensional water-soil coupling imbalance comprehensive mean value. Based on the sliding time window, calculate the change rate sequence of the three-dimensional water-soil coupling imbalance comprehensive mean value, and calculate the standard deviation and average change rate of the three-dimensional water-soil coupling imbalance comprehensive mean value. At the same time, calculate the change rate of the corrected flux adjustment value. The coupling change deviation value is obtained by subtracting the average change rate from the current three-dimensional water-soil coupling imbalance comprehensive mean change rate; the flux response value is obtained by multiplying the current corrected flux regulation value change rate with the proportional regulation weight factor. The absolute difference between the coupling change deviation and the flux response value is calculated and divided by the sum of the standard deviation of the three-dimensional water-soil coupling imbalance comprehensive mean change rate and the stable constant value to obtain the normalized dynamic difference value. The normalized dynamic difference value is negatively represented as the exponent and natural exponent is used to obtain the dynamic response consistency value.

9. The integrated model test method for electromechanical numerical control and testing of shield tunnels according to claim 1, characterized in that, The specific process of updating parameters and correcting thresholds based on dynamic response consistency is as follows: The dynamic response consistency value is calculated and written into the coupled test database, and compared with the consistency threshold. When the dynamic response consistency is greater than or equal to the consistency threshold, it is determined to be a stable state of consistency adjustment, and the current algorithm and the baseline values ​​corresponding to each parameter are maintained. When the dynamic response consistency is less than the consistency threshold, the baseline values ​​corresponding to each parameter are updated with the median value of the parameter distribution within the sliding time window as the update target, and adaptive adjustment is performed according to the weighted smoothing method. Meanwhile, based on historical data in the coupled test database, the equilibrium threshold and consistency threshold are optimized and updated using the rate of change sequence of dynamic response consistency value and three-dimensional water-soil coupling imbalance comprehensive value through Bayesian optimization algorithm.

10. A shield tunnel electromechanical numerical control and testing integrated model test platform, characterized in that, include: The data acquisition and preprocessing module is used to acquire the three-dimensional coupled test data of the water and soil machine in real time and to perform data preprocessing on the three-dimensional coupled test data of the water and soil machine. The coupling analysis and equilibrium assessment module is used to map the pre-processed three-dimensional coupling test data of water and soil machinery to a unified three-dimensional grid, reconstruct the multi-distribution fields of pore pressure, water content, stress and mean effective stress; calculate various residual parameters through the spatial difference and time derivative of the multi-distribution fields and evaluate the three-dimensional water and soil coupling equilibrium, determine the hydraulic stress state, and execute the balance control of flow and pressure. The flow regulation and closed-loop control module is used to evaluate and correct the flux regulation amount when the hydraulic stress state is unbalanced by combining three-dimensional water-soil coupling balance and multiple types of residual parameters, and to drive the hydraulic pump and valve actuator to realize the regulation of inlet and outlet water flow. The self-learning and threshold optimization module is used to evaluate the consistency of dynamic response based on the three-dimensional water-soil coupling balance change rate and the modified flux regulation change rate, and update parameters and correct thresholds according to the consistency of dynamic response.

Images