An underwater shield excavation face stability identification and neighborhood structure cooperative control method

Abstract

The application discloses a kind of underwater shield excavation face stability identification and neighborhood structure collaborative control method and system, method includes: in excavation face layout data monitoring, namely acquisition equipment, implement global coverage monitoring to underwater construction influence area, according to the structure characteristics of protected object and safety demand layout settlement and inclination monitoring point, adapt protection level and construction influence range to determine monitoring scheme;To multi-source heterogeneous original data preprocessing, reject abnormal data, correct system deviation and environmental interference error, after standardization conversion and structured integration, establish global monitoring database;Multi-dimensional identification index system covering excavation face dynamic parameter, construction influence domain environmental parameter and neighborhood protected object state parameter is constructed, combined with engineering specification and design requirement, through multi-index fusion analysis and logic determination rule output stable state grade, dynamically match collaborative control strategy;It improves construction safety and controllability.

Description

Technical Field

[0001] This invention belongs to the field of underwater shield tunneling construction safety control technology, and more specifically, relates to a method and system for underwater shield tunneling face stability identification and neighboring structure collaborative control. Background Technology

[0002] Underwater shield tunneling faces complex hydrogeological environments, making the stability control of the excavation face and the safety protection of adjacent structures a core technical challenge in the engineering field. Traditional construction methods often employ single-point or localized monitoring of the excavation face, collecting data only on tunneling parameters or partial ground deformation. This approach fails to comprehensively cover the core state of the excavation face, the environmental impact zone, and the multi-dimensional parameters of protected adjacent structures, resulting in biased monitoring data that cannot fully reflect the coupled influence relationships between various factors.

[0003] In the data processing stage, the raw data is prone to abnormal fluctuations and system deviations due to interference factors such as water flow disturbances and water pressure changes in the underwater environment. Traditional processing methods often rely on simple filtering or manual screening, lacking targeted abnormal data identification and error correction mechanisms, making it difficult to guarantee data quality. At the same time, the inconsistent formats of multi-source data make effective integration difficult, failing to provide systematic data support for stability assessment.

[0004] In terms of stability assessment, existing methods mostly rely on single indicators or empirical thresholds, failing to construct a complete indicator system encompassing multi-dimensional parameters. The assessment process neglects the correlation between dynamic changes in the excavation face and the safety of adjacent structures, resulting in insufficient accuracy and an inability to precisely reflect the stability state at different construction stages. Corresponding control strategies are often pre-set fixed schemes, unable to be dynamically adjusted based on the assessment results. When signs of instability appear at the excavation face, it is difficult to take timely and appropriate control measures, easily leading to safety risks such as excavation face collapse, settlement of adjacent buildings, or pipeline damage.

[0005] These problems not only affect the efficiency and safety of underwater shield tunneling, but may also lead to project delays, economic losses and environmental risks. Therefore, it is urgent to establish a technical system that takes into account comprehensive monitoring, accurate identification and coordinated control to solve the practical problems of excavation face stability and safety control of adjacent structures in underwater shield tunneling, and promote the standardization and refinement of underwater shield tunneling technology. Summary of the Invention

[0006] This invention aims to solve problems such as one-sided monitoring of the excavation face, insufficient data quality, low accuracy of stability assessment, and rigid control strategies in underwater shield tunneling. By constructing a multi-dimensional monitoring network, optimizing data processing procedures, establishing a scientific assessment system and a dynamic collaborative control mode, it achieves accurate assessment of the stability of the excavation face and efficient protection of adjacent structures, thereby improving construction safety and controllability.

[0007] To address the aforementioned deficiencies or improvement needs of existing technologies, as a first aspect of this invention, the present invention provides a method for stability identification and collaborative control of neighboring structures at the underwater shield tunneling excavation face, comprising:

[0008] S1. Deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; conduct full-area monitoring of stratum deformation and water level changes in the underwater construction impact area using monitoring equipment adapted to the underwater environment; for protected objects, deploy settlement, tilt, displacement, and crack monitoring points according to their structural characteristics and safety requirements, with the density of monitoring points and the type of monitoring equipment determined based on the protection level and the scope of construction impact;

[0009] S2. Preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, and correct system deviations and environmental interference errors using error correction methods; and perform unified standardization conversion and structured integration of monitoring data to establish a full-domain monitoring database;

[0010] S3. Construct a multi-dimensional identification index system that includes dynamic parameters of the excavation face, environmental parameters of the construction impact zone, and state parameters of protected objects in the adjacent area; set multi-level stability identification thresholds based on engineering technical specifications, safety risk levels, and design requirements; use a multi-index fusion analysis method to comprehensively evaluate the standardized monitoring data, and output the excavation face stability level results in combination with logical judgment rules;

[0011] S4. Based on the results of the stability assessment of the excavation face, dynamically match the corresponding collaborative control strategy.

[0012] Furthermore, the protected objects in S1 include neighborhood buildings, underground pipelines, and public facilities.

[0013] Furthermore, the process by which the density of monitoring points and the type of monitoring equipment in S1 are determined based on the protection level and the scope of construction impact is as follows:

[0014] The safe allowable deformation of the protected object As one of the core parameters, the allowable deformation is safe. According to engineering technical specifications and design requirements, the geological stability coefficient of the construction impact area is specified. The attenuation distance of the impact of tunnel boring on the surrounding environment was calculated based on the mechanical parameters of the strata and soil within the construction influence area and hydrological conditions. The dynamic change of groundwater level within the construction influence zone was derived from the solid excavation diameter, tunneling parameters, and geological conditions. Real-time data collection and acquisition via underwater water level monitoring equipment; tunnel boring rate. The parameters are recorded in real time by the shield tunneling parameter acquisition device;

[0015] Establish a dynamic calculation relationship for monitoring point deployment density: Monitoring point deployment density The safe allowable deformation of the protected object Inversely proportional to the formation stability coefficient Inversely proportional to the distance at which the impact of construction has diminished. Proportional to, and simultaneously coupled with, the dynamic changes in groundwater level within the construction influence area. With shield tunneling rate The synergistic effect, that is, through the formula The foundation layout density is calculated;

[0016] Furthermore, considering the structural characteristics of the protected object, the density of monitoring equipment in deformation-sensitive areas is increased to 1.5 times that of the foundation; the selection of monitoring equipment type is based on a comparison of the required monitoring data accuracy. Measurement accuracy of monitoring equipment Determine the required accuracy of monitoring data. Based on the safe allowable deformation amount 1 / 10 is determined when This type of monitoring equipment should be selected at that time.

[0017] Furthermore, the process of removing data that deviates from the normal range in S2 is as follows:

[0018] First, a sample set is constructed by extracting continuous monitoring data from the same construction process and geological unit. The mean value of the data is then calculated from the sample set. With covariance matrix Combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate Establish a dynamic calculation relationship for data fluctuation thresholds: through calculation The reciprocal of , The product of these factors yields the operating condition disturbance degree. Based on With covariance matrix traces Constructing dynamic thresholds ;

[0019] Construct a Mahalanobis distance anomaly detection criterion: for each monitoring data to be verified Calculate its value relative to the mean of the sample set. Mahalanobis distance ;when At that time, the data was initially determined to be suspected abnormal data;

[0020] Further, the theoretical reasonable value corresponding to this data is calculated using time-series interpolation. If the deviation between the suspected abnormal data and the theoretical reasonable value exceeds... If the deviation is less than 1 / 2 and there is no corresponding record of construction parameter adjustment, geological change, or environmental disturbance, it is considered to be outside the normal range and is removed; if the deviation is within the allowable range or there is a clear cause of the deviation, the data is retained and associated with the working condition information.

[0021] Furthermore, the error correction method in S2 is specifically as follows:

[0022] First, considering the instrument's own accuracy deviation and installation deviation, an initial error correction function is established by collecting monitoring data from a standard reference source under the same operating conditions:

[0023] Let the standard reference value be The original value of the monitoring is The initial correction equation was obtained by least squares fitting. ,in For slope correction term, The intercept correction term is determined by the statistical fitting relationship between the standard reference source and the original monitoring data;

[0024] Combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate A working condition disturbance compensation model is constructed: by analyzing the coupling relationship between historical monitoring data and corresponding working condition parameters, a nonlinear mapping relationship is established. ,in The data was trained using similar engineering data to quantify the interference of ground disturbance, water level fluctuations, and tunneling rate changes on the monitoring data, thereby obtaining secondary correction values. It enables real-time compensation for errors caused by dynamic changes in operating conditions.

[0025] Finally, a multi-source data consistency verification mechanism is introduced: for data collected by different types of monitoring equipment on the same monitoring object or the same monitoring area, the correlation coefficient matrix of their data change trends is calculated. The trend consistency quantification index, i.e., the largest eigenvalue, is obtained through matrix eigenvalue decomposition. ;when When the value is greater than the mean of all eigenvalues ​​of the correlation coefficient matrix, it indicates that the trends of the multi-source data are consistent, and the arithmetic mean of the multi-source data is taken as the final correction result; when... If the error is less than the mean, trace the source of error, including instrument accuracy, installation status, and working condition adaptability, and re-perform initial calibration and working condition compensation until the consistency of multi-source data trends meets the eigenvalue quantification requirements.

[0026] Furthermore, the method for constructing the multi-dimensional identification index system in S3 is as follows:

[0027] The construction of core state indicators for the excavation face is achieved by selecting the deviation of shield tunneling parameters. Water and soil pressure balance at the excavation face and the deformation rate of soil and rock As a core indicator;

[0028] The construction of environmental indicators for the construction impact zone is achieved by integrating the formation stability coefficient. Dynamic changes in groundwater level and riverbed deformation As an environmental indicator;

[0029] The construction of the safety index dimension for protected objects in the vicinity is achieved by incorporating the cumulative deformation of the protected objects. Deformation rate and differential deformation As a safety indicator;

[0030] Enhance system synergy through index coupling and correlation calculation: Calculate the deformation rate of rock and soil at the excavation face. Deformation rate of neighboring structures Pearson correlation coefficient and the balance of water and soil pressure With formation stability coefficient correlation coefficient By incorporating correlation coefficients into the validity verification of indicators and eliminating indicators with weak correlation to the core stability mechanism, a multi-dimensional identification indicator system with clear hierarchy, tight coupling, and deep correlation with the data of the entire construction process is finally formed.

[0031] Furthermore, the method for determining the stability level of the excavation face in S3 is as follows:

[0032] Continuous time-series data sequences of three dimensions of indicators—core state of the excavation face, construction impact zone environment, and safety of protected objects in the adjacent area—are extracted, and the time-series trend lines of each indicator are calculated in real time using the sliding window method. ,in For the quantitative value of the indicator, It is a time variable;

[0033] Then calculate the coupling evolution coefficient between the core state index of the excavation face and the environmental index of the construction impact zone. ,in This is the time derivative of the deformation rate of the soil and rock mass. The time derivative of the formation stability coefficient is used to quantify the synergistic relationship between the two as construction progresses; the coupling evolution coefficient between the core state index of the excavation face and the safety index of the adjacent structure is calculated. ,in It is the time derivative of the deformation rate of the neighborhood structure, reflecting the dynamic correlation between the excavation face disturbance and the response of the neighborhood structure;

[0034] Furthermore, by calculating the curvature of the time series trend lines of each indicator... The curvature value reflects the degree of drastic change in the index; based on the statistical distribution of curvature in the full-time series data, the coupling result of the mean curvature and the standard deviation is used as a dynamic judgment threshold. ,in The mean curvature, The standard deviation of curvature is used, and the threshold is updated in real time as the data changes during construction.

[0035] Three-level stability determination rules are set: when the curvature of the time series trend lines of all indicators is less than... ,and , When the absolute values ​​of all parameters fall within the middle distribution range of the full-time coupled evolution coefficients, it is considered a "stable state"; when the curvature of the time-series trend line of any one indicator in any dimension is greater than... and less than ,or , When the absolute value of one item exceeds the middle distribution range but does not reach the extreme value range, it is judged as a "warning state"; when the curvature of the time series trend line of two or more indicators in any dimension is greater than 1, it is considered a "warning state". ,or , When the absolute values ​​of all values ​​are in the extreme range, it is determined to be a "dangerous situation".

[0036] Furthermore, the process of dynamically matching the corresponding collaborative control strategy in S4 is as follows:

[0037] Under stable conditions, maintain the established construction parameters and conduct monitoring and inspections at the regular frequency;

[0038] Under early warning conditions, the monitoring frequency is increased at each level, the tunneling parameters and construction process parameters are dynamically adjusted, and adjacent structural protection and reinforcement measures are taken simultaneously.

[0039] In the event of an emergency, the emergency response mechanism should be activated immediately, construction should be suspended, and an emergency reinforcement plan for the excavation face should be implemented. Emergency protection measures for adjacent structures should be carried out in conjunction with the emergency response plan. Once the monitoring data meets the conditions for safe recovery, construction should be gradually resumed. Throughout the process, dynamic coordination between the stability control of the excavation face and the safety protection of adjacent structures should be achieved.

[0040] As a second aspect of the present invention, a stability identification and neighborhood structure collaborative control system for underwater shield tunneling face is also provided, comprising:

[0041] The multi-dimensional monitoring network deployment unit is used to deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; for the stratum deformation and water level changes in the underwater construction impact area, monitoring equipment adapted to the underwater environment is used for full-area coverage monitoring; for the protected objects, settlement, tilt, displacement, and crack monitoring points are deployed according to their structural characteristics and safety requirements, and the density of monitoring points and the type of monitoring equipment are determined according to the protection level and the scope of construction impact.

[0042] The monitoring data preprocessing and integration unit is used to preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, correct system deviations and environmental interference errors using error correction methods, and perform unified standardized conversion and structured integration of monitoring data to establish a full-domain monitoring database.

[0043] The stability state level comprehensive judgment unit is used to construct a multi-dimensional judgment index system that includes dynamic parameters of the excavation face, environmental parameters of the construction influence zone, and state parameters of the protected objects in the adjacent area; based on engineering technical specifications, safety risk levels, and design requirements, multi-level stability judgment thresholds are set; a multi-index fusion analysis method is used to comprehensively judge the standardized monitoring data, and combined with logical judgment rules, the stability state level result of the excavation face is output;

[0044] The collaborative control strategy dynamic matching unit is used to dynamically match the corresponding collaborative control strategy based on the stability state identification result of the excavation face.

[0045] As a third aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, the computer program being executed by a processor of any one of the methods for determining the stability of an underwater shield tunneling face and coordinating the control of neighboring structures.

[0046] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0047] 1. The underwater shield tunneling face stability assessment and neighboring structure collaborative control method of the present invention constructs a multi-dimensional monitoring network covering the excavation face, construction influence zone, and neighboring protected objects. It strategically deploys monitoring equipment and differentiated monitoring points adapted to the underwater environment to achieve comprehensive monitoring of tunneling parameters, soil and rock properties, stratum deformation, water level changes, and structural safety status. This monitoring method overcomes the limitations of traditional monitoring methods that are confined to a single area. By accurately capturing changes in key parameters throughout the entire construction process, it provides comprehensive and continuous raw data support for subsequent stability assessment, ensuring that the data accurately reflects the dynamic working conditions and multi-factor coupled influences of underwater shield tunneling construction, thus laying the foundation for the accuracy of the assessment results.

[0048] 2. The underwater shield tunneling excavation face stability identification and neighboring structure collaborative control method of the present invention establishes a comprehensive monitoring database by performing abnormal data removal, error correction, standardization transformation, and structured integration on multi-source heterogeneous monitoring data. Simultaneously, it constructs a multi-dimensional identification index system including excavation face dynamic parameters, environmental parameters, and structural state parameters, and outputs the stability state level using multi-index fusion analysis and logical judgment rules. This technical process effectively solves the problems of underwater monitoring data being susceptible to environmental interference and the difficulty in integrating complex data types. Data quality is improved through data preprocessing, and the multi-dimensional index system and scientific identification methods achieve accurate classification of the excavation face stability state, providing a reliable basis for matching subsequent control strategies.

[0049] 3. The underwater shield tunneling excavation face stability identification and neighboring structure collaborative control method of the present invention dynamically correlates the stability state level identification results with the collaborative control strategy, and adaptively matches the corresponding control scheme according to different stability states. This collaborative control mode abandons the limitations of traditional fixed control strategies, realizes precise docking between identification results and control actions, and can adjust control measures in a timely manner in response to dynamic changes in the stability state of the excavation face. It effectively addresses the impact of complex working conditions such as ground disturbance and water level fluctuations on the stability of the excavation face and the safety of neighboring structures during underwater shield tunneling construction, significantly improves the safety and controllability of the construction process, and ensures the smooth progress of underwater shield tunneling projects. Attached Figure Description

[0050] Figure 1 This is a flowchart of the underwater shield tunneling face stability identification and neighborhood structure collaborative control method according to an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the settlement measuring point arrangement according to an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of the building observation point layout according to an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of the system units in an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0055] Example 1

[0056] Please refer to Figure 1This embodiment 1 provides a method for stability identification of underwater shield tunneling face and collaborative control of neighboring structures, including:

[0057] S1. Deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; conduct full-area monitoring of stratum deformation and water level changes in the underwater construction impact area using monitoring equipment adapted to the underwater environment; for protected objects, deploy settlement, tilt, displacement, and crack monitoring points according to their structural characteristics and safety requirements, with the density of monitoring points and the type of monitoring equipment determined based on the protection level and the scope of construction impact;

[0058] S2. Preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, and correct system deviations and environmental interference errors using error correction methods; and perform unified standardization conversion and structured integration of monitoring data to establish a full-domain monitoring database;

[0059] S3. Construct a multi-dimensional identification index system that includes dynamic parameters of the excavation face, environmental parameters of the construction impact zone, and state parameters of protected objects in the adjacent area; set multi-level stability identification thresholds based on engineering technical specifications, safety risk levels, and design requirements; use a multi-index fusion analysis method to comprehensively evaluate the standardized monitoring data, and output the excavation face stability level results in combination with logical judgment rules;

[0060] S4. Based on the results of the stability assessment of the excavation face, dynamically match the corresponding collaborative control strategy.

[0061] This embodiment 1 further elaborates on the above steps.

[0062] (1) Deployment of a multi-dimensional monitoring network

[0063] In underwater shield tunneling scenarios, the deployment of monitoring points for protected objects must balance the accuracy of safety protection with construction adaptability. The determination of their deployment density and the type of monitoring equipment must be systematically derived based on the characteristics of construction disturbance and the safety requirements of the protected objects. Protected objects include adjacent buildings, underground pipelines, and public facilities. These objects have different structural characteristics and safety tolerance capabilities, and varying sensitivities to construction disturbances. Therefore, monitoring solutions need to be personalized based on multi-factor collaborative analysis.

[0064] For example, please refer to Figure 2 Road and surface monitoring points are installed using well-drilling methods, either manually or by drilling. Road monitoring points must penetrate the road surface structure and be buried in solid ground (generally at a depth of at least 1 meter). Protective pipes and covers, or protective wells, should be installed for protection.

[0065] Similarly, for example, please refer to Figure 3 The layout of settlement monitoring points and tilt monitoring points can be changed according to the different layouts of the building. Three settlement monitoring points are arranged at the bottom of the point-shaped building, and two tilt monitoring points are arranged at the top. According to the size of the rectangular building, one settlement monitoring point is arranged every 5 to 10 meters, and a corresponding tilt monitoring point is arranged at the top.

[0066] Furthermore, the placement of detection points is based on the safe allowable deformation of the protected object. As one of the core parameters, the allowable deformation is safe. According to engineering technical specifications and design requirements, the allowable settlement of adjacent buildings and the allowable displacement of underground pipelines are specified; the ground stability coefficient of the construction impact area is also specified. The coefficient, calculated based on the mechanical parameters of the soil and rock mass and hydrological conditions within the construction impact zone, reflects the strata's resistance to disturbance. A lower coefficient indicates that the strata are more susceptible to construction impacts, necessitating enhanced monitoring. The attenuation distance of the shield tunneling's impact on the surrounding environment is also considered. Derived from the excavation diameter, tunneling parameters, and geological conditions, this represents the maximum extent of construction disturbance spreading outward from the excavation face; and the dynamic change in groundwater level within the construction influence zone. Real-time data collection via underwater water level monitoring equipment reflects the dynamic fluctuations of the hydrological environment during construction; tunnel boring rate. The parameters of the tunnel boring machine are recorded in real time by the shield tunneling parameter acquisition device, reflecting the rhythm of the disturbance to the surrounding environment caused by the construction progress.

[0067] The determination of the monitoring point density needs to integrate the above-mentioned multi-factor correlation logic: the smaller the allowable deformation, the more sensitive the object is to deformation, and the more dense the monitoring points need to be to capture subtle changes; the lower the stratum stability coefficient, the weaker the stratum's resistance to disturbance, and the more timely the anomalies need to be detected through higher density monitoring; the longer the construction impact attenuation distance, the wider the monitoring coverage, and the more the number of monitoring points needs to be increased to ensure full coverage; the synergistic effect of the dynamic change of groundwater level and the tunnel boring rate will amplify the construction disturbance effect, and the more significant the changes of the two, the higher the monitoring point density needs to be.

[0068] Furthermore, a dynamic calculation relationship for the monitoring point deployment density is established: monitoring point deployment density The safe allowable deformation of the protected object Inversely proportional to the formation stability coefficient Inversely proportional to the distance at which the impact of construction has diminished. Proportional to, and simultaneously coupled with, the dynamic changes in groundwater level within the construction influence area. With shield tunneling rate The synergistic effect, that is, through the formula The foundation layout density is calculated;

[0069] Based on this, the distribution of monitoring points is optimized in combination with the structural characteristics of the protected objects. For different types of objects such as rigid buildings and flexible pipelines, the uniformity of the distribution of monitoring points is adjusted. The density of monitoring points in structural deformation sensitive areas is further increased according to the foundation layout density to ensure that there are no blind spots in the monitoring of key areas. For example, the density of monitoring points in structural deformation sensitive areas is increased by 1.5 times the foundation layout density.

[0070] The selection of monitoring equipment type is based on a comparison of the required monitoring data accuracy. Measurement accuracy of monitoring equipment Determine the required accuracy of monitoring data. Based on the safe allowable deformation amount 1 / 10 is determined when This type of monitoring equipment should be selected to ensure that the collected data accurately reflects the actual state of the protected object, providing reliable data support for subsequent stability assessment.

[0071] (2) Monitoring data preprocessing and integration

[0072] The multi-source monitoring data of underwater shield tunneling comes from different monitoring units. The data types are heterogeneous and are easily affected by underwater environment interference, differences in instrument accuracy and fluctuations in construction conditions. There may be outliers and various errors in the raw data. If it is used directly for subsequent identification, it will seriously affect the accuracy of the results. Therefore, a systematic preprocessing process is required to ensure data quality.

[0073] Outlier removal requires a scientific judgment logic based on construction conditions and data characteristics. This first necessitates extracting continuous monitoring data from the same construction process and geological unit to construct a sample set, and then calculating the mean value of the data from this sample set. With covariance matrix mean The covariance matrix represents the centrality level of the dataset. Reflecting the degree of temporal correlation between data; combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate Establish a dynamic calculation relationship for data fluctuation thresholds: through calculation The reciprocal of , The product of these factors yields the operating condition disturbance degree. Based on With covariance matrix traces Constructing dynamic thresholds traces Reflects the overall dispersion level of the data, and the degree of disturbance under operating conditions. Quantify the impact of construction and geological environment on the data;

[0074] Construct a Mahalanobis distance anomaly detection criterion: for each monitoring data to be verified Calculate its value relative to the mean of the sample set. Mahalanobis distance Mahalanobis distance eliminates the interference of correlation between data dimensions and can accurately characterize the degree of deviation of a single data point from the sample set; when At that time, the data was initially determined to be suspected abnormal data;

[0075] Further, the theoretical reasonable value corresponding to this data is calculated using time-series interpolation. If the deviation between the suspected abnormal data and the theoretical reasonable value exceeds... If the deviation is less than 1 / 2 and there is no corresponding record of construction parameter adjustment, geological change, or environmental disturbance, it is considered to be outside the normal range and is removed; if the deviation is within the allowable range or there is a clear cause of the deviation, the data is retained and associated with the working condition information.

[0076] Error correction requires eliminating inherent instrument biases and dynamic interference from operating conditions in stages, while verifying the correction effect through multi-source data. The specific error correction method is as follows:

[0077] First, considering the instrument's own accuracy deviation and installation deviation, an initial error correction function is established by collecting monitoring data from a standard reference source under the same operating conditions:

[0078] Let the standard reference value be The original value of the monitoring is The initial correction equation was obtained by least squares fitting. ,in For slope correction term, The intercept correction term is determined by the statistical fitting relationship between the standard reference source and the original monitoring data;

[0079] Combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate A working condition disturbance compensation model is constructed: by analyzing the coupling relationship between historical monitoring data and corresponding working condition parameters, a nonlinear mapping relationship is established. ,in The data was trained using similar engineering data to quantify the interference of ground disturbance, water level fluctuations, and tunneling rate changes on the monitoring data, thereby obtaining secondary correction values. It enables real-time compensation for errors caused by dynamic changes in operating conditions.

[0080] Finally, a multi-source data consistency verification mechanism is introduced: for data collected by different types of monitoring equipment on the same monitoring object or the same monitoring area, the correlation coefficient matrix of their data change trends is calculated. The trend consistency quantification index, i.e., the largest eigenvalue, is obtained through matrix eigenvalue decomposition. ;when When the value is greater than the mean of all eigenvalues ​​of the correlation coefficient matrix, it indicates that the trends of the multi-source data are consistent, and the arithmetic mean of the multi-source data is taken as the final correction result; when... If the error is less than the mean, trace the source of error, including instrument accuracy, installation status, and working condition adaptability, and re-perform initial calibration and working condition compensation until the consistency of multi-source data trends meets the eigenvalue quantification requirements.

[0081] After completing the removal of abnormal data and error correction, all monitoring data are uniformly standardized and transformed to eliminate the differences in the dimensions of different types of data. Then, through structured integration, the scattered multi-source data are classified and sorted according to the dimensions such as monitoring objects, monitoring periods, and data types to establish a full-domain monitoring database. This provides standardized and high-quality data support for the subsequent construction of a multi-dimensional identification indicator system and the assessment of stable state levels.

[0082] (3) Comprehensive assessment of stability level

[0083] The stability of the underwater shield tunneling face is affected by multiple factors such as tunneling conditions, environmental disturbances, and the response of neighboring structures. A single-dimensional indicator is insufficient to fully characterize the stable state. It is necessary to construct a multi-dimensional identification indicator system and establish scientific judgment rules in order to achieve accurate judgment.

[0084] The construction of the multi-dimensional identification index system revolves around three key dimensions: the core state of the excavation face, the environment of the construction impact zone, and the safety of protected objects in the adjacent area. Each dimension's indicators are quantified based on corrected monitoring data to ensure close correlation with actual construction. Specifically, the construction method of the multi-dimensional identification index system is as follows:

[0085] The construction of core state indicators for the excavation face is achieved by selecting the deviation of shield tunneling parameters. Water and soil pressure balance at the excavation face and the deformation rate of soil and rock As a core indicator;

[0086] Tunneling parameter deviation Through formula Calculation, where The corrected actual tunneling parameters (such as advance speed and cutterhead torque). These are the baseline tunneling parameters for the corresponding working conditions. The number of tunneling parameter types is used to quantify the degree of deviation between actual tunneling and benchmark conditions;

[0087] Water and soil pressure balance Through formula Calculation, where The soil and water pressure values ​​at different monitoring points on the excavation face are corrected. This represents the average water and soil pressure; the closer the value is to 1, the more even the pressure distribution.

[0088] Deformation rate of rock and soil Through formula Calculation, where , These are the soil deformation monitoring values ​​after correction at adjacent time points, directly reflecting the dynamic changes of the soil at the excavation face;

[0089] The construction of environmental indicators for the construction impact zone is achieved by integrating the formation stability coefficient. Dynamic changes in groundwater level and riverbed deformation As an environmental indicator;

[0090] Formation stability coefficient The calculation results of the mechanical parameters of the strata and soil and the hydrological conditions within the construction influence area are adopted;

[0091] Dynamic variation range of groundwater level Through formula Calculation, where The groundwater level values ​​at each monitoring point within the construction impact zone are corrected to quantify the intensity of hydrological environmental fluctuations.

[0092] Riverbed deformation Through formula Calculation, where The corrected elevation values ​​for the riverbed monitoring points. This refers to the elevation value of the corresponding point before construction. The number of riverbed monitoring points comprehensively reflects the extent of disturbance to the underwater strata caused by construction.

[0093] The construction of the safety index dimension for protected objects in the vicinity is achieved by incorporating the cumulative deformation of the protected objects. Deformation rate and differential deformation As a safety indicator;

[0094] Cumulative deformation Through formula Calculation, where This is the current corrected deformation monitoring value. These are the monitoring values ​​corresponding to the initial construction phase;

[0095] Deformation rate Through formula Calculation, where , This represents the cumulative deformation at adjacent time points;

[0096] Differential deformation Through formula Calculation, where Accurately capture the risk of uneven structural deformation by measuring the cumulative deformation at different monitoring points for the same protected object.

[0097] Enhance system synergy through index coupling and correlation calculation: Calculate the deformation rate of rock and soil at the excavation face. Deformation rate of neighboring structures Pearson correlation coefficient and the balance of water and soil pressure With formation stability coefficient correlation coefficient By incorporating correlation coefficients into the validity verification of indicators and eliminating indicators with weak correlation to the core stability mechanism, a multi-dimensional identification indicator system with clear hierarchy, tight coupling, and deep correlation with the data of the entire construction process is finally formed.

[0098] The core state indicators of the excavation face focus on key parameters that directly reflect the dynamics of the excavation face, selecting the shield tunneling parameter deviation, the water and soil pressure balance at the excavation face, and the deformation rate of the soil and rock mass as core indicators. Correspondingly, the method for determining the stability level of the excavation face is as follows:

[0099] Continuous time-series data sequences of three dimensions of indicators—core state of the excavation face, construction impact zone environment, and safety of protected objects in the adjacent area—are extracted, and the time-series trend lines of each indicator are calculated in real time using the sliding window method. ,in For the quantitative value of the indicator, The time variable is used; the trend line is generated by linear fitting of data from adjacent monitoring periods, reflecting the natural evolution of the indicator as the construction progresses.

[0100] Then calculate the coupling evolution coefficient between the core state index of the excavation face and the environmental index of the construction impact zone. ,in This is the time derivative of the deformation rate of the soil and rock mass. The time derivative of the formation stability coefficient is used to quantify the synergistic relationship between the two as construction progresses; the coupling evolution coefficient between the core state index of the excavation face and the safety index of the adjacent structure is calculated. ,in It is the time derivative of the deformation rate of the neighborhood structure, reflecting the dynamic correlation between the excavation face disturbance and the response of the neighborhood structure;

[0101] Furthermore, by calculating the curvature of the time series trend lines of each indicator... The curvature value reflects the degree of drastic change in the index; based on the statistical distribution of curvature in the full-time series data, the coupling result of the mean curvature and the standard deviation is used as a dynamic judgment threshold. ,in The mean curvature, The standard deviation of curvature is used, and the threshold is updated in real time as the data changes during construction.

[0102] Three-level stability determination rules are set: when the curvature of the time series trend lines of all indicators is less than... ,and , When the absolute values ​​of all parameters fall within the middle distribution range of the full-time coupled evolution coefficients, it is considered a "stable state"; when the curvature of the time-series trend line of any one indicator in any dimension is greater than... and less than ,or , When the absolute value of one item exceeds the middle distribution range but does not reach the extreme value range, it is judged as a "warning state"; when the curvature of the time series trend line of two or more indicators in any dimension is greater than 1, it is considered a "warning state". ,or , When the absolute values ​​of all values ​​are in the extreme range, it is determined to be a "dangerous situation".

[0103] (4) Dynamic matching of collaborative control strategies

[0104] During underwater shield tunneling, the stability of the excavation face and the safety of adjacent structures are constantly changing. Fixed control strategies are difficult to adapt to the safety requirements under different working conditions. It is necessary to dynamically match and coordinate control strategies based on the stability assessment results to achieve precise linkage protection between the stability of the excavation face and the safety of adjacent structures.

[0105] When the assessment result indicates a stable state, it means that the core parameters of the excavation face, the environment of the construction influence zone, and the status of the protected objects in the adjacent area are all within a safe range, and the temporal changes of each indicator are stable with good cross-dimensional coupling and synergy. At this time, there is no need to adjust the core construction plan; the established shield tunneling parameters (such as advance speed, cutterhead torque, etc.) and construction technology should be maintained to ensure construction efficiency. At the same time, monitoring and on-site inspections should be carried out at the regular frequency to track data change trends in real time, ensuring that the stable state is maintained and avoiding increased construction costs or schedule delays due to excessive control.

[0106] When the assessment result is in an early warning state, it indicates an anomaly in a single-dimensional indicator or a weakening of cross-dimensional coupling correlation. Although it has not reached the level of a dangerous situation, it has already shown signs of instability and risk. At this time, a tiered response measure needs to be initiated. The primary task is to progressively increase the monitoring frequency, shorten the data collection interval, and accurately capture the details of indicator changes to provide real-time data support for adjusting control strategies. For the influencing factors corresponding to the abnormal indicators, the tunneling parameters and construction process parameters are dynamically adjusted. For example, the propulsion speed is fine-tuned to balance the water and soil pressure at the excavation face, or the cutterhead rotation speed is optimized to reduce disturbance to the strata. Simultaneously, neighboring structural protection and reinforcement measures are implemented. Based on the type and deformation characteristics of the protected object, targeted reinforcement methods are selected, such as grouting reinforcement of building foundations and setting temporary supports for underground pipelines, to achieve synergistic linkage between excavation face control and neighboring structural protection, curbing further risk development.

[0107] When the assessment result indicates a hazardous situation, it signifies multiple abnormal indicators or severe imbalances across dimensions, resulting in extremely high safety risks such as excavation face collapse and damage to adjacent structures. In this situation, an emergency response mechanism must be activated immediately, and tunnel boring machine (TBM) construction must be suspended immediately to prevent further disturbance and exacerbation of the hazardous situation. An emergency reinforcement plan for the excavation face should be rapidly implemented. Based on geological conditions and the characteristics of the hazardous situation, methods such as grouting reinforcement and sheet pile insertion should be used to stabilize the soil at the excavation face and prevent significant soil erosion. Simultaneously, emergency protection measures for adjacent structures should be implemented, including emergency support and temporary reinforcement of threatened buildings, pipelines, etc., to prevent further structural deformation. During the emergency response, monitoring frequency should be continuously increased to track the reinforcement effect in real time. Once monitoring data shows that the core state of the excavation face, environmental parameters, and deformation of adjacent structures have returned to safe ranges and the conditions for safe resumption of construction are met, construction parameters should be gradually adjusted to resume construction. During the recovery process, data changes should be monitored in stages to ensure that each stage remains under control. Dynamic coordination between excavation face stability control and adjacent structure safety protection should be achieved throughout the entire process to minimize the impact of the hazardous situation.

[0108] The application prospects of this embodiment are primarily reflected in its adaptation to core scenarios in underwater shield tunneling projects, particularly suitable for shield tunneling projects traversing complex waterways such as rivers, lakes, and seas, or in areas with densely packed buildings or important underground pipelines. Its multi-dimensional monitoring network can accurately cover the entire underwater construction scenario, the data preprocessing process can effectively solve data quality problems caused by underwater environmental interference, the multi-dimensional identification system and dynamic judgment rules can achieve accurate classification of stable states, and the differentiated collaborative control strategy can specifically address different risk levels, providing full-process technical support for the project from monitoring and identification to control. This significantly reduces safety risks such as excavation face collapse and damage to adjacent structures, and has significant practical implications for improving the safety and precision of underwater shield tunneling construction.

[0109] Meanwhile, the technical logic of this embodiment can be extended to similar underground projects, providing a referable technical framework for the safety control of projects such as river-crossing tunnels, sea-crossing shield tunnels, and urban underwater utility tunnels. Based on a data-driven self-adaptive identification approach and a collaborative control concept, it can adapt to the needs of different geological conditions and construction scales, reducing reliance on experience while improving project controllability. As underwater shield tunneling projects develop towards deeper waters and more complex geological environments, the technical solution of this embodiment can be continuously iterated through data accumulation and model optimization, providing core support for industry technology upgrades, possessing both current engineering application value and long-term technology promotion potential.

[0110] Example 2

[0111] Please refer to Figure 4 This embodiment 2 provides an underwater shield tunneling face stability identification and neighborhood structure collaborative control system, including:

[0112] The multi-dimensional monitoring network deployment unit is used to deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; for the stratum deformation and water level changes in the underwater construction impact area, monitoring equipment adapted to the underwater environment is used for full-area coverage monitoring; for the protected objects, settlement, tilt, displacement, and crack monitoring points are deployed according to their structural characteristics and safety requirements, and the density of monitoring points and the type of monitoring equipment are determined according to the protection level and the scope of construction impact.

[0113] The monitoring data preprocessing and integration unit is used to preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, correct system deviations and environmental interference errors using error correction methods, and perform unified standardized conversion and structured integration of monitoring data to establish a full-domain monitoring database.

[0114] The stability state level comprehensive judgment unit is used to construct a multi-dimensional judgment index system that includes dynamic parameters of the excavation face, environmental parameters of the construction influence zone, and state parameters of the protected objects in the adjacent area; based on engineering technical specifications, safety risk levels, and design requirements, multi-level stability judgment thresholds are set; a multi-index fusion analysis method is used to comprehensively judge the standardized monitoring data, and combined with logical judgment rules, the stability state level result of the excavation face is output;

[0115] The collaborative control strategy dynamic matching unit is used to dynamically match the corresponding collaborative control strategy based on the stability state identification result of the excavation face.

[0116] Example 3

[0117] This embodiment 3 also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement any step of a method for underwater shield tunneling face stability assessment and neighborhood structure collaborative control.

[0118] The computer-readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0119] For a description of the computer-readable storage medium provided in this application, please refer to the above method embodiments; further details will not be repeated here.

[0120] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for stability assessment of underwater shield tunneling face and collaborative control of neighboring structures, characterized in that, include: S1. Deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; conduct full-area monitoring of stratum deformation and water level changes in the underwater construction impact area using monitoring equipment adapted to the underwater environment; for protected objects, deploy settlement, tilt, displacement, and crack monitoring points according to their structural characteristics and safety requirements, with the density of monitoring points and the type of monitoring equipment determined based on the protection level and the scope of construction impact; S2. Preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, and correct system deviations and environmental interference errors using error correction methods; and perform unified standardization conversion and structured integration of monitoring data to establish a full-domain monitoring database; S3. Construct a multi-dimensional identification index system that includes dynamic parameters of the excavation face, environmental parameters of the construction impact zone, and state parameters of protected objects in the adjacent area; set multi-level stability identification thresholds based on engineering technical specifications, safety risk levels, and design requirements; use a multi-index fusion analysis method to comprehensively evaluate the standardized monitoring data, and output the excavation face stability level results in combination with logical judgment rules; S4. Based on the stability status identification results of the excavation face, dynamically match the corresponding collaborative control strategy; The method for determining the stability level of the excavation face in S3 is as follows: Continuous time-series data sequences of three dimensions of indicators—core state of the excavation face, construction impact zone environment, and safety of protected objects in the adjacent area—are extracted, and the time-series trend lines of each indicator are calculated in real time using the sliding window method. ,in For the quantitative value of the indicator, It is a time variable; Then calculate the coupling evolution coefficient between the core state index of the excavation face and the environmental index of the construction impact zone. ,in This is the time derivative of the deformation rate of the soil and rock mass. The time derivative of the formation stability coefficient is used to quantify the synergistic relationship between the two as construction progresses; the coupling evolution coefficient between the core state index of the excavation face and the safety index of the adjacent structure is calculated. ,in It is the time derivative of the deformation rate of the neighborhood structure, reflecting the dynamic correlation between the excavation face disturbance and the response of the neighborhood structure; Furthermore, by calculating the curvature of the time series trend lines of each indicator... Its curvature value reflects the degree of drastic change in the index; Based on the statistical distribution of curvature in full-time data, the coupling result of the mean curvature and the standard deviation is used as a dynamic judgment threshold. ,in The mean curvature, The standard deviation of curvature is used, and the threshold is updated in real time as the data changes during construction. Three-level stability determination rules are set: when the curvature of the time series trend lines of all indicators is less than... ,and , When the absolute values ​​of all parameters fall within the middle distribution range of the full-time coupled evolution coefficients, it is considered a "stable state"; when the curvature of the time-series trend line of any one indicator in any dimension is greater than... and less than ,or , When the absolute value of one item exceeds the middle distribution range but does not reach the extreme value range, it is judged as a "warning state"; when the curvature of the time series trend line of two or more indicators in any dimension is greater than 1, it is considered a "warning state". ,or , When the absolute values ​​of all values ​​are in the extreme range, it is determined to be a "dangerous situation".

2. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The protected objects in S1 include neighborhood buildings, underground pipelines, and public facilities.

3. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The process by which the density of monitoring points and the type of monitoring equipment in S1 are determined based on the protection level and the scope of construction impact is as follows: The safe allowable deformation of the protected object As one of the core parameters, the allowable deformation is safe. According to engineering technical specifications and design requirements, the geological stability coefficient of the construction impact area is specified. The attenuation distance of the impact of tunnel boring on the surrounding environment was calculated based on the mechanical parameters of the strata and soil within the construction influence area and hydrological conditions. The dynamic change of groundwater level within the construction influence zone was derived from the solid excavation diameter, tunneling parameters, and geological conditions. Real-time data collection and acquisition via underwater water level monitoring equipment; tunnel boring rate. The parameters are recorded in real time by the shield tunneling parameter acquisition device; Establish a dynamic calculation relationship for monitoring point deployment density: Monitoring point deployment density The safe allowable deformation of the protected object Inversely proportional to the formation stability coefficient Inversely proportional to the distance at which the impact of construction has diminished. Proportional to, and simultaneously coupled with, the dynamic changes in groundwater level within the construction influence area. With shield tunneling rate The synergistic effect, that is, through the formula The foundation layout density is calculated; Furthermore, considering the structural characteristics of the protected object, the density of monitoring equipment in deformation-sensitive areas is increased to 1.5 times that of the foundation; the selection of monitoring equipment type is based on a comparison of the required monitoring data accuracy. Measurement accuracy of monitoring equipment Determine the required accuracy of monitoring data. Based on the safe allowable deformation amount 1 / 10 is determined when This type of monitoring equipment should be selected at that time.

4. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The process for removing data that deviates from the normal range in S2 is as follows: First, a sample set is constructed by extracting continuous monitoring data from the same construction process and geological unit. The mean value of the data is then calculated from the sample set. With covariance matrix Combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate Establish a dynamic calculation relationship for data fluctuation thresholds: through calculation The reciprocal of , The product of these factors yields the operating condition disturbance degree. Based on With covariance matrix traces Constructing dynamic thresholds ; Construct a Mahalanobis distance anomaly detection criterion: for each monitoring data to be verified Calculate its value relative to the mean of the sample set. Mahalanobis distance ;when At that time, the data was initially determined to be suspected abnormal data; Further, the theoretical reasonable value corresponding to this data is calculated using time-series interpolation. If the deviation between the suspected abnormal data and the theoretical reasonable value exceeds... If the deviation is less than half of the normal range and there is no corresponding record of construction parameter adjustment, geological change, or environmental disturbance, the data is considered to be outside the normal range and is removed; if the deviation is within the allowable range or there is a clear cause of the deviation, the data is retained and associated with the working condition information.

5. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The error correction method in S2 is specifically as follows: First, considering the instrument's own accuracy deviation and installation deviation, an initial error correction function is established by collecting monitoring data from a standard reference source under the same operating conditions: Let the standard reference value be The original value of the monitoring is The initial correction equation was obtained by least squares fitting. ,in For slope correction term, The intercept correction term is determined by the statistical fitting relationship between the standard reference source and the original monitoring data; Combined with the obtained formation stability coefficient Dynamic changes in groundwater level and shield tunneling rate A working condition disturbance compensation model is constructed: by analyzing the coupling relationship between historical monitoring data and corresponding working condition parameters, a nonlinear mapping relationship is established. ,in The data was trained using similar engineering data to quantify the interference of ground disturbance, water level fluctuations, and tunneling rate changes on the monitoring data, thereby obtaining secondary correction values. It enables real-time compensation for errors caused by dynamic changes in operating conditions. Finally, a multi-source data consistency verification mechanism is introduced: for data collected by different types of monitoring equipment on the same monitoring object or the same monitoring area, the correlation coefficient matrix of their data change trends is calculated. The trend consistency quantification index, i.e., the largest eigenvalue, is obtained through matrix eigenvalue decomposition. ;when When the value is greater than the mean of all eigenvalues ​​of the correlation coefficient matrix, it indicates that the trends of the multi-source data are consistent, and the arithmetic mean of the multi-source data is taken as the final correction result; when... If the error is less than the mean, trace the source of error, including instrument accuracy, installation status, and working condition adaptability, and re-perform initial calibration and working condition compensation until the consistency of multi-source data trends meets the eigenvalue quantification requirements.

6. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The method for constructing the multi-dimensional identification index system in S3 is as follows: The construction of core state indicators for the excavation face is achieved by selecting the deviation of shield tunneling parameters. Water and soil pressure balance at the excavation face and the deformation rate of soil and rock As a core indicator; The construction of environmental indicators for the construction impact zone is achieved by integrating the formation stability coefficient. Dynamic changes in groundwater level and riverbed deformation As an environmental indicator; The construction of the safety index dimension for protected objects in the vicinity is achieved by incorporating the cumulative deformation of the protected objects. Deformation rate and differential deformation As a safety indicator; Enhance system synergy through index coupling and correlation calculation: Calculate the deformation rate of rock and soil at the excavation face. Deformation rate of neighboring structures Pearson correlation coefficient and the balance of water and soil pressure With formation stability coefficient correlation coefficient By incorporating correlation coefficients into the validity verification of indicators and eliminating indicators with weak correlation to the core stability mechanism, a multi-dimensional identification indicator system with clear hierarchy, tight coupling, and deep correlation with the data of the entire construction process is finally formed.

7. The method for stability assessment and collaborative control of the underwater shield tunneling face according to claim 1, characterized in that, The process of dynamically matching the corresponding collaborative control strategy in S4 is as follows: Under stable conditions, maintain the established construction parameters and conduct monitoring and inspections at the regular frequency; Under early warning conditions, the monitoring frequency is increased at each level, the tunneling parameters and construction process parameters are dynamically adjusted, and adjacent structural protection and reinforcement measures are taken simultaneously. In the event of an emergency, the emergency response mechanism should be activated immediately, construction should be suspended, and an emergency reinforcement plan for the excavation face should be implemented. Emergency protection measures for adjacent structures should be carried out in conjunction with the emergency response plan. Once the monitoring data meets the conditions for safe recovery, construction should be gradually resumed. Throughout the process, dynamic coordination between the stability control of the excavation face and the safety protection of adjacent structures should be achieved.

8. A stability assessment and neighborhood structure collaborative control system for underwater shield tunneling face, characterized in that, include: The multi-dimensional monitoring network deployment unit is used to deploy tunneling parameter acquisition devices, soil and rock mechanical parameter sensors, and deformation monitoring equipment at the excavation face; for the stratum deformation and water level changes in the underwater construction impact area, monitoring equipment adapted to the underwater environment is used for full-area coverage monitoring; for the protected objects, settlement, tilt, displacement, and crack monitoring points are deployed according to their structural characteristics and safety requirements, and the density of monitoring points and the type of monitoring equipment are determined according to the protection level and the scope of construction impact. The monitoring data preprocessing and integration unit is used to preprocess the multi-source heterogeneous raw data collected by each monitoring unit, remove data that deviates from the normal range through anomaly data identification methods, correct system deviations and environmental interference errors using error correction methods, and perform unified standardized conversion and structured integration of monitoring data to establish a full-domain monitoring database. The stability state level comprehensive judgment unit is used to construct a multi-dimensional judgment index system that includes dynamic parameters of the excavation face, environmental parameters of the construction influence zone, and state parameters of the protected objects in the adjacent area; based on engineering technical specifications, safety risk levels, and design requirements, multi-level stability judgment thresholds are set; a multi-index fusion analysis method is used to comprehensively judge the standardized monitoring data, and combined with logical judgment rules, the stability state level result of the excavation face is output; The collaborative control strategy dynamic matching unit is used to dynamically match the corresponding collaborative control strategy based on the stability state identification result of the excavation face. The method for determining the stability level of the excavation face is as follows: Continuous time-series data sequences of three dimensions of indicators—core state of the excavation face, construction impact zone environment, and safety of protected objects in the adjacent area—are extracted, and the time-series trend lines of each indicator are calculated in real time using the sliding window method. , For the quantitative value of the indicator, It is a time variable; Calculate the coupling evolution coefficient between the core state indicators of the excavation face and the environmental indicators of the construction impact zone. , This is the time derivative of the deformation rate of the soil and rock mass. The time derivative of the formation stability coefficient is used to quantify the synergistic relationship between the two as construction progresses; the coupling evolution coefficient between the core state index of the excavation face and the safety index of the adjacent structure is calculated. , It is the time derivative of the deformation rate of the neighborhood structure, reflecting the dynamic correlation between the excavation face disturbance and the response of the neighborhood structure; Calculate the curvature of the time series trend lines for each indicator. The curvature value reflects the degree of drastic change in the indicator; Based on the statistical distribution of curvature in full-time data, the coupling result of the mean curvature and the standard deviation is used as a dynamic judgment threshold. , The mean curvature, The standard deviation of curvature is used, and the threshold is updated in real time as the data changes during construction. Three-level stability determination rules are set: when the curvature of all indicator time series trend lines is less than... ,and , When the absolute values ​​of all parameters fall within the middle distribution range of the full-time coupling evolution coefficients, it is determined to be a "stable state"; when the curvature of the time-series trend line of any one indicator is greater than a certain value, it is considered a "stable state". and less than ,or , When one absolute value exceeds the middle distribution range but does not reach the extreme value range, it is judged as a "warning state"; when the curvature of the time series trend line of two or more indicators in any dimension is greater than 1, it is considered a "warning state". ,or , When the absolute values ​​of all values ​​are in the extreme range, it is determined to be a "dangerous situation".

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program is executed by a processor as described in any one of claims 1-7: a method for stability identification of underwater shield tunneling face and collaborative control of neighboring structures.

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