Ground subsidence micro-motion monitoring system and method thereof

Abstract

The invention relates to the technical field of land subsidence disaster early warning, in particular to a land subsidence micro-motion monitoring system and method. The system comprises a geomechanical model construction module, a micro-motion event interpretation module, a damage-stress coupling evolution module and a risk probability prediction module. The system obtains seismic moments by interpreting a micro-seismic event in real time; the core of the method is that a current accumulated damage factor, real-time shear stress and normal stress are solved by applying a damage amplification effect based on seismic moments and historical accumulated damage factors, and a time-varying instability risk index and an instability probability are predicted; according to the method, discrete micro-seismic data are assimilated into continuous damage accumulation and stress redistribution processes in the rock-soil body, and conversion from passive recording to internal state quantitative early warning is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ground subsidence disaster early warning, in particular to a ground subsidence micro-motion monitoring system and method thereof. BACKGROUND

[0002] In the field of geotechnical engineering and ground subsidence monitoring, a large number of high-frequency microseismic events flow will be generated by the micro-fracture of the internal rock-soil mass; the existing technology mostly stays at the passive recording level of these events, lacking the physical mechanism of associating discrete microseismic events with the continuous damage accumulation and stress redistribution in the internal rock-soil mass; the lack of such mechanism leads to two main defects: one is the inability to quantify the internal damage and stress state; the other is the difficulty in distinguishing benign noise from key precursors of instability from the massive data, which easily leads to a warning storm, resulting in ineffective warning; Therefore, how to establish an evolution model that can balance real-time and accuracy, and real-time assimilate high-frequency and discrete micro-event data into continuous internal state evolution, and accordingly quantify and predict macro-instability risk, is a technical problem that needs to be solved. SUMMARY

[0003] To solve the above technical problems, the present application provides a ground subsidence micro-motion monitoring system and method, in particular, the technical solution of the present application is as follows: A ground subsidence micro-motion monitoring system, comprising: A geomechanical model construction module for constructing a three-dimensional geological grid model and providing an initial stress field and initial mechanical parameters; A micro-motion event interpretation module for real-time interpretation of microseismic events and output of seismic moment; A damage-stress coupling evolution module for receiving the seismic moment and calculating the current cumulative damage factor, real-time shear stress and real-time normal stress based on the historical cumulative damage factor maintained by the module; A risk probability prediction module for receiving the current cumulative damage factor, real-time shear stress, real-time normal stress and initial mechanical parameters, and calculating the time-varying instability risk index and instability probability; The damage-stress coupling evolution module is specifically used for: According to the seismic moment, calculating the basic damage degree; Based on the basic damage degree and the historical cumulative damage factor, applying damage amplification effect to calculate the actual damage increment; According to the actual damage increment, updating the historical cumulative damage factor to generate the current cumulative damage factor; According to the change of the current cumulative damage factor, performing a stress calculation step to generate the real-time shear stress and the real-time normal stress.

[0004] Preferably, the risk probability prediction module is specifically used for: receiving the current cumulative damage factor and the initial mechanical parameter; calculating a dynamic elastic modulus based on the current cumulative damage factor and the initial mechanical parameter; calculating a dynamic cohesion based on the current cumulative damage factor and the initial mechanical parameter; calculating a dynamic internal friction angle based on the current cumulative damage factor and the initial mechanical parameter.

[0005] Preferably, the risk probability prediction module is further specifically used for: determining a real-time load based on the real-time shear stress; determining a real-time resistance based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle; calculating a ratio of the real-time load to the real-time resistance to generate the time-varying instability risk index.

[0006] Preferably, the stress calculation step specifically includes: judging whether the current cumulative damage factor exceeds a preset global triggering threshold; when the current cumulative damage factor does not exceed the global triggering threshold, calculating the real-time shear stress and the real-time normal stress by using a preset local stress transfer function; when the current cumulative damage factor exceeds the global triggering threshold, triggering the geomechanical model construction module to perform global recalculation to generate a global stress field; and calibrating and outputting the real-time shear stress and the real-time normal stress by using the global stress field.

[0007] Preferably, when performing the global recalculation, the geomechanical model construction module is specifically used for: using the dynamic elastic modulus calculated by the risk probability prediction module as an updated model stiffness to perform the global recalculation.

[0008] Preferably, the system further includes: a macroscopic response monitoring module for monitoring a macroscopic displacement of the rock-soil mass to generate measured displacement data; a model calibration module for: calculating a model predicted displacement by the geomechanical model construction module according to the dynamic elastic modulus; calculating a residual error between the model predicted displacement and the measured displacement data; iteratively adjusting a model calibration parameter in the damage-stress coupling evolution module and the risk probability prediction module by using a data assimilation algorithm to minimize the residual error.

[0009] Preferably, the model calibration parameters include: a calibration coefficient related to a foundation damage degree, a damage amplification coefficient, a nonlinearity index, and a material degradation index.

[0010] A ground subsidence micro-motion monitoring method, comprising: real-time interpretation of microseismic events by a micro-motion event interpretation module, and output of seismic moment; receiving of the seismic moment by a damage-stress coupling evolution module, and calculation of a current cumulative damage factor, real-time shear stress, and real-time normal stress based on a historical cumulative damage factor maintained by the module; calculation of a time-varying instability risk index and an instability probability by a risk probability prediction module based on the current cumulative damage factor, the real-time shear stress, the real-time normal stress, and initial mechanical parameters provided by a geomechanical model construction module.

[0011] Preferably, the step of calculating the current cumulative damage factor, the real-time shear stress, and the real-time normal stress specifically comprises: calculation of a foundation damage degree according to the seismic moment; calculation of an actual damage increment based on the foundation damage degree and the historical cumulative damage factor by applying a damage amplification effect; updating of the historical cumulative damage factor according to the actual damage increment to generate the current cumulative damage factor; execution of a stress calculation step to generate the real-time shear stress and the real-time normal stress; wherein the stress calculation step specifically comprises: judgment of whether the current cumulative damage factor exceeds a preset global trigger threshold; when the current cumulative damage factor does not exceed the global trigger threshold, calculation of the real-time shear stress and the real-time normal stress by using a preset local stress transfer function; when the current cumulative damage factor exceeds the global trigger threshold, triggering of the geomechanical model construction module to execute global recalculation to generate a global stress field; and calibration and output of the real-time shear stress and the real-time normal stress by using the global stress field.

[0012] Preferably, the step of calculating the time-varying instability risk index and the instability probability specifically comprises: calculation of a dynamic elastic modulus based on the current cumulative damage factor and the initial mechanical parameters; calculation of a dynamic cohesion based on the current cumulative damage factor and the initial mechanical parameters; calculating a dynamic internal friction angle based on the current cumulative damage factor and the initial mechanical parameters; determining a real-time load based on the real-time shear stress; determining a real-time resistance based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle; calculating a ratio of the real-time load to the real-time resistance to generate the time-varying instability risk index.

[0013] Compared with the prior art, the present application has the following beneficial effects: 1. The present application establishes a set of physical evolution mechanism, which real-time assimilates massive, discrete microseismic event data into continuous damage accumulation and stress redistribution process inside the rock-soil mass, solving the defect that the prior art can only passively record and cannot quantify the internal damage and stress state; 2. The present application ingeniously solves the core contradiction between the high real-time requirement of microseismic data and the time-consuming nature of global stress field calculation by adopting the combination of high-frequency local approximation calculation and low-frequency global precise calibration through the innovative global-local decoupling calculation architecture, ensuring the timeliness of system response and the long-term accuracy of results; 3. The present application introduces damage amplification effect to simulate damage history correlation and calculates time-varying instability risk index based on dynamic load and dynamic resistance; the index improves the traditional static safety factor and can dynamically quantify the consumption process of safety margin, thereby accurately distinguishing between benign noise and key instability precursor, solving the problem of early warning storm; 4. The present application introduces a feedback mechanism based on field measured macroscopic displacement data, automatically inverts and calibrates key parameters inside the model through data assimilation algorithm, solving the problem that model parameter relies on distorted laboratory calibration and is difficult to implement on site, greatly improving the engineering practical value and prediction accuracy of the system. BRIEF DESCRIPTION OF DRAWINGS

[0014] The present application will be further explained below in conjunction with the drawings and examples: Figure 1 is a structural diagram of the system of the present application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical scheme and advantages of the present application clearer and more apparent, the present application will be further described in detail below in conjunction with specific examples.

[0016] Example 1: Please refer to Figure 1 A ground subsidence micro-motion monitoring system, comprising: A geomechanical model construction module for constructing a three-dimensional geological grid model and providing an initial stress field and initial mechanical parameters; a micro-motion event interpretation module for interpreting micro-motion events in real time and outputting seismic moment; a damage-stress coupling evolution module for receiving the seismic moment and calculating the current cumulative damage factor and real-time shear stress and real-time normal stress based on a historical cumulative damage factor maintained by the module; a risk probability prediction module for receiving the current cumulative damage factor and real-time shear stress and real-time normal stress and initial mechanical parameters and calculating a time-varying instability risk index and instability probability; the damage-stress coupling evolution module is specifically configured to: calculate a basic damage degree according to the seismic moment; calculate an actual damage increment based on the basic damage degree and the historical cumulative damage factor by applying a damage amplification effect; update the historical cumulative damage factor according to the actual damage increment to generate the current cumulative damage factor; perform a stress calculation step according to a change in the current cumulative damage factor to generate the real-time shear stress and the real-time normal stress.

[0017] The embodiment provides a micro-motion monitoring system for ground subsidence, which aims to deduce and quantify a hidden damage accumulation and stress redistribution process in a rock-soil body in real time from a mass of micro-motion event streams to predict a structural instability risk; In a preferred embodiment, the system comprises: a geomechanical model construction module GMM: The purpose of this module is to establish an initial static geomechanical skeleton of the entire monitoring area; The module is configured to construct a three-dimensional geological grid model, for example, by using finite element method FEM or discrete element method DEM technology, and inputting geological exploration data and rock-soil body physical and mechanical parameters to construct a three-dimensional geological model; The module provides initial stress fields for other dynamic modules of the system and initial mechanical parameters, which refer to benchmark mechanical properties of the rock-soil body in an undamaged state and serve as a benchmark for subsequent dynamic degradation calculation; in the embodiment, the parameters specifically include an initial elastic modulus , an initial cohesion and an initial internal friction angle ; a micro-motion event interpretation module MEM: The purpose of this module is to serve as a real-time sensing unit of the system and capture precursor signals released by micro-fractures in the rock-soil body in real time; The module is configured to use a standard sensor array such as a geophone and a seismological source positioning algorithm to interpret micro-motion events in real time, and the output is a seismic moment ; seismic moment It refers to a physical quantity used to characterize the energy release scale of microseismic events. Its source is obtained by real-time interpretation by this module, and its function is to serve as an event input source that drives subsequent damage evolution. Damage-Stress Coupled Evolution Module (DSEM): This module is the core evolution module of this invention, and its purpose is to assimilate discrete microseismic events into continuous internal state evolution. This module is used to receive seismic moments. And based on the historical cumulative damage factor maintained by this module Through a series of coupled calculations, the current cumulative damage factor is calculated. and real-time shear stress and real-time normal stress ; Historical cumulative damage factors : refers to model unit i in t The accumulated damage state at time 1 is a dimensionless scalar from 0 to 1, which is derived from the previous iteration output of this module and serves as a historical benchmark for calculating the current damage increment. Current cumulative damage factor : refers to the latest damage state of model unit i at time t, after assimilating the new event k. It is obtained by calculation by this module and its function is to characterize the current degree of material degradation and serve as the input of the risk probability prediction module. Real-time shear stress and real-time normal stress This refers to the cumulative damage. The change leads to a change in material stiffness, which in turn triggers stress redistribution. The latest stress state of element i at time t is as follows: In this embodiment, the damage-stress coupling evolution module is specifically used to execute the following internal logic steps: Step a: Calculate the foundation damage degree based on the seismic moment; The physical dimension N·m Mapped to dimensionless basic damage ; This step introduces the basic damage calculation formula:

[0018] in, The seismic moment is measured in N·m and originates from the micro-motion event interpretation module. Mref is the reference seismic moment, with dimensions in N·m. In this embodiment, it is preferably a fixed constant, for example, Mref = 1.0 N·m, and its function is only to ensure ( ) dimensionless processing; is a calibration coefficient related to the base damage degree, is a dimensionless parameter, and serves to match the brittleness of the rock-soil at a specific site; Step a-1: Damage event mapping; According to the hypocenter location of event k output by the micro-motion event interpretation module, one or more three-dimensional geological grid model units i affected by the event are determined; in a preferred embodiment, a hypocenter envelope or a preset influence radius can be used to distribute the base damage degree to the unit i in which the hypocenter is located; or in another embodiment, according to the distance between event k and unit i , a spatial attenuation function is used to weight to affect multiple adjacent units i; for example, the spatial attenuation function may be a Gaussian function , where is a calibration parameter representing the influence range, used to determine the weight of the distribution of damage energy in space; Step b: Based on the base damage degree and the historical cumulative damage factor, the actual damage increment is calculated by applying the damage amplification effect; This step is one of the innovations of the present application; it solves the defect of the existing model that ignores the correlation of damage history; the technical motivation is that the existing historical damage increases the brittleness of the rock-soil, thereby nonlinearly amplifying the actual damage caused by a new event represented by ;

[0019] , where is the base damage degree, is a dimensionless parameter, and comes from the calculation result of step a; is the historical cumulative damage factor, is a dimensionless parameter, and comes from the state at the previous time of this module; is the damage amplification coefficient, is a dimensionless parameter; is the nonlinear index, is a dimensionless parameter, and is preferably ; Step c: According to the actual damage increment, the historical cumulative damage factor is updated to generate the current cumulative damage factor; The newly calculated damage increment is added to the historical state, and it is ensured that it does not exceed the physical upper limit 1.0 representing complete failure; This step uses the damage accumulation update formula:

[0020] Step d: performing stress calculation step according to the change of the current cumulative damage factor to generate real-time shear stress and real-time normal stress; Cumulative damage The increase will cause the material stiffness, i.e. dynamic elastic modulus, and the purpose of this step is to calculate the stress redistribution caused by the change of this stiffness in real time, so as to obtain the updated and ; Note: the specific implementation of this step is further defined in detail Risk probability prediction module RPPM: This module is the risk decision module of the present application, and its purpose is to collect all current state information and predict future risks; This module is used to receive the current cumulative damage factor , real-time shear stress , real-time normal stress , all from the DSEM module, and initial mechanical parameters from the GMM module, to calculate the time-varying instability risk index and instability probability ; Time-varying instability risk index : Instability probability : refers to the probability of instability of the monitoring area within a future time window, for example 24 hours, based on field and parameter uncertainty, such as through Monte Carlo simulation; ; The system disclosed in this embodiment establishes a complete quantitative chain from micro events to macro state to future risk through the cooperative work of the above four modules, especially through the logical closed loop of damage amplification and stress calculation inside the damage-stress coupling evolution module. It solves the two major pain points in the prior art that the storm warning cannot distinguish between benign noise and key precursors and the mechanism is missing to quantify the internal damage and stress state, realizes the leap from passive event recording to active risk prediction, and greatly improves the accuracy and timeliness of land subsidence disaster warning.

[0021] Embodiment 2: The risk probability prediction module is specifically used for: receiving the current cumulative damage factor and the initial mechanical parameters; calculating the dynamic elastic modulus based on the current cumulative damage factor and the initial mechanical parameters; calculating the dynamic cohesion based on the current cumulative damage factor and the initial mechanical parameters; calculating the dynamic internal friction angle based on the current cumulative damage factor and the initial mechanical parameters.

[0022] The embodiment is based on embodiment 1, and the internal implementation of the risk probability prediction module is specifically defined; the purpose of this layer of limitation is to realize the physical correlation between micro damage and macro mechanical properties, that is, to quantify How to cause real-time deterioration of the macroscopic strength of the rock-soil body; For further illustration, the risk probability prediction module is specifically used to perform the following steps: Receiving the current cumulative damage factor From DSEM and initial mechanical parameters From GMM; Based on the current cumulative damage factor and the initial mechanical parameters, the dynamic elastic modulus is calculated; The real-time stiffness after damage is calculated, which is a key input for subsequent stress redistribution calculation model calibration; This step adopts the dynamic elastic modulus reduction formula quoted from the standard continuous damage mechanics theory:

[0023] Wherein, The initial elastic modulus is Pa, and the source is the geomechanical model construction module; The current cumulative damage factor is a dimensionless parameter, and the source is the damage-stress coupling evolution module; Based on the current cumulative damage factor and the initial mechanical parameters, the dynamic cohesion is calculated; The real-time cohesion after damage is calculated, which is a key component of the shear strength; This step adopts the dynamic cohesion reduction formula:

[0024] Wherein, The initial cohesion is Pa, and the source is the geomechanical model construction module; The material degradation index cohesion is a dimensionless parameter; Based on the current cumulative damage factor and the initial mechanical parameters, the dynamic internal friction angle is calculated; The real-time internal friction angle after damage is calculated, which is another key component of the shear strength; in order to ensure the rigor of the physical meaning, the friction coefficient representing the friction ability Is reduced; This step adopts the dynamic internal friction coefficient reduction formula:

[0025] Wherein, is the initial internal friction angle, in degree or radian, from the geomechanical model building module; is the material degradation index friction angle, a dimensionless parameter; The current cumulative damage factor outputted by the damage-stress coupling evolution module is converted into the dynamic change of the macroscopic engineering mechanics parameter known by those skilled in the art such as geotechnical engineers, by the above three reduction formulas. This provides a solid, physically-mechanism-compliant input for the subsequent calculation of real-time resistance and time-varying instability risk index, and is a key link for realizing the logical leap from damage to risk.

[0026] Embodiment 3: The risk probability prediction module is further specifically configured to: determine the real-time load based on the real-time shear stress; determine the real-time resistance based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle; calculate the ratio of the real-time load to the real-time resistance to generate the time-varying instability risk index.

[0027] This embodiment further specifically defines the internal implementation of the risk probability prediction module based on Embodiment 2; the purpose of this layer of definition is to aggregate the dynamic load and the dynamic resistance to calculate the decision index. Based on the result of the previous step, the risk probability prediction module is further specifically configured to perform the following steps: determine the real-time load based on the real-time shear stress; determine the load force driving instability; In this embodiment, the real-time load DrivingForce is defined as the real-time shear stress calculated by the damage-stress coupling evolution module; determine the real-time resistance based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle; determine the shear strength resisting instability; The real-time resistance ResistingForce is calculated based on the Mohr-Coulomb failure criterion and using the dynamic parameters and calculated in Embodiment 2; This step adopts the real-time resistance dynamic shear strength calculation formula:

[0028] wherein, is the dynamic cohesion, in Pa, from the calculation result of Embodiment 2; The stress is real-time normal stress, with dimensions in Pa, and originates from the damage-stress coupling evolution module. The dynamic internal friction coefficient is a dimensionless parameter derived from the calculation results of Example 2. Calculate the ratio of real-time load to real-time resistance to generate a time-varying instability risk index; To avoid instability in numerical calculations, this step is specifically used for: Determine real-time resistance ; Set a very small resistance threshold. This threshold is used to determine numerical stability; It is a positive number close to zero, preset to prevent division by zero errors in numerical calculations. For example, it can be based on the initial cohesion. Or it can be determined by the precision of machine calculations; if The time-varying instability risk index will then be... Set to the preset maximum value or mark as invalid; Otherwise (i.e.) ), perform ratio calculation: Time-varying instability risk index =Real-time load / Real-time resistance= / = / ( + ) This embodiment defines a time-varying instability risk index. This core innovative parameter improves the static safety factor in geotechnical engineering. Resistance / load); the present invention The index is a dynamic early warning indicator that measures the load that increases in real time due to stress redistribution. Resistance that decreases in real time due to damage and deterioration Dynamic coupling was implemented; this allows the system to perfectly quantify the real-time consumption process of the safety margin, transforming a statically designed approach. The parameters were modified to be used for dynamic early warning. The index enables precise early warning, solving the problem of early warning storms; the risk probability prediction module is also specifically used to calculate the instability probability based on the time-varying instability risk index. Receiver Time-Varying Instability Risk Index field; Considering initial mechanical parameters The uncertainty is assumed to follow a pre-defined probability distribution; Using the Monte Carlo simulation method, perform N iterations: a. In each iteration, a set of parameters is randomly drawn from the probability distribution.

[0029] b. Using the set of sampled parameters, and substituting into the current and , the formula defined in this embodiment (Embodiment 3) is used to recalculate ; counting the number of times is greater than or equal to 1.0 over N iterations ; calculate the instability probability .

[0030] Embodiment 4: The stress calculation step specifically includes: determining whether the current cumulative damage factor exceeds a preset global trigger threshold; when the current cumulative damage factor does not exceed the global trigger threshold, using a preset local stress transfer function to calculate the real-time shear stress and real-time normal stress; when the current cumulative damage factor exceeds the global trigger threshold, triggering the geomechanical model construction module to perform global recalculation to generate a global stress field; and using the global stress field to calibrate and output the real-time shear stress and real-time normal stress.

[0031] This embodiment further defines the stress calculation step in the damage-stress coupling evolution module based on Embodiment 1; the purpose of this definition is to solve the core contradiction between real-time performance and calculation accuracy; the frequency of microseismic event input is very high, per second or per minute, while the global recalculation of the accurate stress field such as FEM / DEM is very time-consuming, per hour or per day; if global recalculation is performed for each microseismic event, the system will lose real-time performance; if only rough calculation is performed, a large error will be accumulated; This embodiment uses a global-local layered decoupling evolution architecture to solve this problem, and the stress calculation step specifically includes: determining whether the global cumulative damage state exceeds a preset global trigger threshold , which specifically includes: counting the number of units in all N model units whose exceeds a preset unit threshold ; calculating the global average damage factor ; when exceeds a preset number, or , it is determined that the global trigger threshold is exceeded; Global trigger threshold This refers to a preset damage accumulation value; when the accumulated damage is small, its disturbance to the stress field is local; when the accumulated damage exceeds this threshold, it indicates that the structure may have undergone significant changes, and a global high-precision check must be performed; the method for determining this threshold can be predetermined through historical data analysis or numerical simulation. When the current cumulative damage factor does not exceed the global trigger threshold, the local path uses a preset local stress transfer function to calculate the real-time shear stress and real-time normal stress. This is a high-frequency, real-time approximate calculation path; the local stress transfer function is specifically used for: Based on the current cumulative damage factor generated in step c And apply the dynamic elastic modulus reduction formula Calculate the dynamic elastic modulus Changes Computing unit Stiffness loss; This stiffness loss is equivalent to a set of inverse virtual nodal forces. Specifically, the virtual node force Based on continuum mechanics and finite element theory, through Calculate, where, The strain-displacement matrix, For changes in dynamic elastic modulus Exported cells The change in stiffness matrix, For this unit in A dynamic field of response at all times; Using pre-calculated local stress transfer coefficient Calculation by Caused neighboring units Stress increment The local stress transfer coefficient Let i be a Green's function or influence coefficient, whose physical meaning is the unit virtual nodal force at element i. Stress response induced at element j This coefficient can be pre-calculated and stored all at once during the geomechanical model building (GMM) stage by applying unit nodal forces to the initial model and calculating the global response field; This stress increment is superimposed onto the historical stress field to generate real-time shear stress and real-time normal stress: ; When the current cumulative damage factor exceeds the global trigger threshold, the global path triggers the geomechanical model building module to perform a global recalculation to generate a global stress field. This is a low-frequency, high-precision calibration path; at this time, the damage-stress coupling evolution module DSEM will be triggered in reverse and call the geomechanical model construction module GMM to force it to perform a complete, high-precision FEM / DEM numerical simulation to obtain the most accurate global stress field in the current state ; And use the global stress field to calibrate and output the real-time shear stress and real-time normal stress; The system will feed back the calculation results of the high-precision global stress field to the damage-stress coupling evolution module DSEM to calibrate and cover the stress field estimated by the local path in DSEM; thereafter, DSEM continues to perform the next round of local approximate calculation based on this calibrated stress field; This embodiment ingeniously solves the contradiction between real-time performance and precision through the global-local decoupling architecture and state-aware switching mechanism, i.e. threshold judgment; the system runs in the high-frequency real-time mode of local approximation most of the time to ensure immediate response to microseismic events; at the same time, through the low-frequency calibration path of global recalculation, it ensures that the cumulative error of the stress field is always controllable and periodically eliminated, thereby guaranteeing the long-term reliability and real-time performance of the prediction results of the entire system in architecture.

[0032] Embodiment 5: The geomechanical model construction module is specifically used for: Using the dynamic elastic modulus calculated by the risk probability prediction module as the updated model stiffness to perform global recalculation.

[0033] This embodiment further specifies the implementation of the geomechanical model construction module in the global path when performing global recalculation based on embodiment 4; The geomechanical model construction module GMM is specifically used for: Using the dynamic elastic modulus calculated by the risk probability prediction module as the updated model stiffness to perform global recalculation; This embodiment establishes a key state feedback loop; when the global path in embodiment 4 is triggered, the GMM module such as the FEM model needs to know the current material stiffness to perform calculation; this embodiment clearly indicates that the GMM should not use the initial elastic modulus at this time, but must use the dynamic elastic modulus calculated in real time by the risk probability prediction module RPPM according to the logic of embodiment 2, i.e. ; This embodiment ensures the physical reality of the high-precision calibration step of global recalculation; by forcing the GMM to use a dynamic elastic modulus that reflects the current cumulative damage state As the updated model stiffness, the result of global recalculation is able to accurately reflect the true stress distribution of the rock-soil mass in the deteriorated state; this greatly improves the accuracy of calibration and ensures that the entire system can maintain high fidelity even when there is a lot of damage accumulation during long-term operation.

[0034] Embodiment 6: The system further comprises: a macroscopic response monitoring module for monitoring the macroscopic displacement of the rock-soil mass to generate measured displacement data; a model calibration module for: calculating model predicted displacement according to the dynamic elastic modulus through the geomechanical model construction module; calculating the residual error between the model predicted displacement and the measured displacement data; using a data assimilation algorithm to iteratively adjust the model calibration parameters in the damage-stress coupling evolution module and the risk probability prediction module to minimize the residual error.

[0035] This embodiment is based on Embodiment 2 and adds an adaptive calibration mechanism to the system; Embodiments 1 and 2 introduce a large number of custom model parameters such as , etc.; how to determine these parameters is the key to whether the invention can be applied in actual engineering; traditional laboratory calibration methods are severely distorted due to scale effects and other issues, and cannot be applied to the field; To solve this implementability problem, the system further comprises: a macroscopic response monitoring module: The purpose of this module is to provide on-site measured macroscopic feedback as a calibration benchmark for model inversion; This module is used to monitor the macroscopic displacement of the rock-soil mass, for example, using GPS, InSAR, total station or high-precision strain gauges to generate measured displacement data ; a model calibration module: The purpose of this module is to automatically and iteratively adjust the model calibration parameters within the system through model inversion and data assimilation, so that its output matches the on-site measured feedback ; The model calibration module is used to: a calculate model predicted displacement according to the dynamic elastic modulus through the geomechanical model construction module; This module calls the GMM module FEM model and uses the dynamic elastic modulus calculated by the RPPM module Embodiment 2 As input, thus calculating the macroscopic displacement that the system predicts will occur under the current model parameters, denoted as ; b Calculate the residual between the model predicted displacement and the measured displacement data; Calculate ; c Using a data assimilation algorithm, iteratively adjust the model calibration parameters in the damage-stress coupling evolution module and the risk probability prediction module to minimize the residual; Data assimilation algorithms such as Kalman filter, ensemble Kalman filter EnKF or particle filter optimization algorithm will automatically perform this iteration process; it will constantly fine-tune the model calibration parameters see definition, until the residual calculated in step b reach the minimum, for example, less than a certain convergence threshold; The embodiment provides an adaptive calibration mechanism based on real-time inversion on site by introducing a macroscopic response monitoring module and a model calibration module; this solves the key implementability problem of how to determine all user-defined model parameters ; It makes the system parameters no longer rely on distorted laboratory calibration, but can be adaptively adjusted and optimized according to the measured displacement data on site, ensuring that all parameters in the core formulas in the invention have objectivity and traceability, greatly improving the engineering practical value and prediction accuracy of the entire system.

[0036] Embodiment 7: The model calibration parameters include: Calibration coefficients and damage amplification coefficients and nonlinear indices and material degradation indices related to the basic damage degree.

[0037] The embodiment further defines the model calibration parameters adjusted by the model calibration module based on embodiment 6; The model calibration parameters include: Calibration coefficients related to the basic damage degree: Refers to the and in the step a basic damage degree calculation formula in embodiment 1 ; Calibration of the mapping relationship of seismic moment to the basic damage ; Damage amplification coefficient: Refers to the in the step b damage amplification effect formula in embodiment 1 ; Calibration of the sensitivity of historical damage to new damage; Nonlinear index: refers to the damage amplification effect formula in step b of Example 1 ; calibrating the nonlinearity degree of damage amplification effect material degradation index: refers to the dynamic cohesion reduction formula in Example 2 and the dynamic internal friction coefficient reduction formula in Example 2 ; calibrating the rate of macroscopic strength decrease caused by cumulative damage In a preferred embodiment, the global trigger threshold defined in Example 4 can also be regarded as a key model calibration parameter and is incorporated into the parameter list of the present embodiment calibrating the switching sensitivity of the global-local hierarchical decoupling architecture At this time, the parameter should be iteratively optimized and calibrated by the model calibration module defined in Example 6 using the data assimilation algorithm together with parameters such as ; The present embodiment specifies the optimization objective of the data assimilation algorithm in Example 6; by defining these coefficients that have the greatest impact on the dynamic behavior of the model and the most critical physical meaning as calibratable parameters, it ensures that the model calibration module can accurately calibrate the damage mapping, damage amplification, and strength reduction of all core innovative formulas in the present invention, thereby making the entire prediction model most approximate to the physical reality on site.

[0038] Example 8: A ground subsidence micro-motion monitoring method, comprising: real-time interpretation of microseismic events by a micro-motion event interpretation module, and output of seismic moment; receiving the seismic moment by a damage-stress coupling evolution module, and based on the historical cumulative damage factor maintained by the module, calculating the current cumulative damage factor and real-time shear stress and real-time normal stress; receiving the current cumulative damage factor, real-time shear stress, real-time normal stress, and initial mechanical parameters provided by the geomechanical model construction module by a risk probability prediction module, and calculating the time-varying instability risk index and instability probability.

[0039] The present embodiment provides a ground subsidence micro-motion monitoring method, which is applied to a ground subsidence micro-motion monitoring system as claimed in any one of Examples 1 to 7; the method is the core processing flow when the system is running The method comprises: real-time interpretation of microseismic events by a micro-motion event interpretation module, and output of seismic moment; This step corresponds to the function of the MEM module in Example 1 Through the damage-stress coupling evolution module, the seismic moment is received, and based on the historical cumulative damage factor maintained by the module, the current cumulative damage factor and the real-time shear stress and the real-time normal stress are calculated; This step corresponds to the function of the DSEM module in Example 1 Through the risk probability prediction module, the current cumulative damage factor and the real-time shear stress and the real-time normal stress and the initial mechanical parameters provided by the geomechanical model construction module are received, and the time-varying instability risk index and the instability probability are calculated. This step corresponds to the function of the RPPM module in Example 1 The method provided in this embodiment, through the above three core steps, constitutes a complete data processing and prediction closed loop; it realizes the real-time conversion of high-frequency, discrete microseismic event data stream into quantified, continuous damage state and stress state, and outputs the time-varying instability risk index and the instability probability with clear physical meaning and decision value, thereby providing an effective, physical mechanism-based prediction and warning means for ground subsidence disasters.

[0040] Example 9: The step of calculating the current cumulative damage factor and the real-time shear stress and the real-time normal stress specifically includes: According to the seismic moment, the basic damage degree is calculated; Based on the basic damage degree and the historical cumulative damage factor, the actual damage increment is calculated by applying the damage amplification effect; According to the actual damage increment, the historical cumulative damage factor is updated to generate the current cumulative damage factor; The stress calculation step is performed to generate the real-time shear stress and the real-time normal stress; Wherein, the stress calculation step specifically includes: Determine whether the current cumulative damage factor exceeds the preset global trigger threshold; When the current cumulative damage factor does not exceed the global trigger threshold, the real-time shear stress and the real-time normal stress are calculated by using the preset local stress transfer function; When the current cumulative damage factor exceeds the global trigger threshold, the geomechanical model construction module is triggered to perform global recalculation to generate a global stress field; And the global stress field is used to calibrate and output the real-time shear stress and the real-time normal stress.

[0041] This embodiment further defines the step 2, i.e., the step of calculating the current cumulative damage factor and the real-time shear stress and the real-time normal stress, based on Example 8; The step of calculating the current cumulative damage factor and the real-time shear stress and the real-time normal stress specifically includes: According to the seismic moment, calculate the foundation damage degree; This step corresponds to step a of the DSEM in Example 1, which adopts Formula Based on the foundation damage degree and the historical cumulative damage factor, the actual damage increment is calculated by applying the damage amplification effect; This step corresponds to step b of the DSEM in Example 1, which adopts Formula According to the actual damage increment, the historical cumulative damage factor is updated to generate the current cumulative damage factor; This step corresponds to step c of the DSEM in Example 1, which adopts Update formula Perform the stress calculation step to generate the real-time shear stress and the real-time normal stress; And, wherein the stress calculation step specifically includes: Determine whether the global cumulative damage state exceeds the preset global trigger threshold; When the current cumulative damage factor does not exceed the global trigger threshold, the real-time shear stress and the real-time normal stress are calculated using the preset local stress transfer function; When the current cumulative damage factor exceeds the global trigger threshold, trigger the geomechanical model construction module to perform global recalculation to generate a global stress field; And use the global stress field to calibrate and output the real-time shear stress and the real-time normal stress; The method steps disclosed in this embodiment completely correspond to the system module functions in Examples 1 and 4; it specifies the complete operation process of the evolution engine DSEM; through the combination of the two core method steps of damage amplification and global-local decoupling, this method simultaneously realizes the nonlinear simulation of damage history correlation and the consideration of real-time and high precision at the operation level, ensuring the accuracy and timeliness of the current cumulative damage factor and real-time stress output by the method.

[0042] Example 10: The steps of calculating the time-varying instability risk index and the instability probability specifically include: Based on the current cumulative damage factor and the initial mechanical parameters, calculate the dynamic elastic modulus; Based on the current cumulative damage factor and the initial mechanical parameters, calculate the dynamic cohesion; Based on the current cumulative damage factor and the initial mechanical parameters, calculate the dynamic internal friction angle; Based on the real-time shear stress, determine the real-time load; Based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle, determine the real-time resistance; Calculate the ratio of the real-time load to the real-time resistance to generate the time-varying instability risk index.

[0043] The embodiment is based on embodiment 8, and the step 3, i.e., the step of calculating the time-varying instability risk index and the instability probability, is specifically defined; The step of calculating the time-varying instability risk index and the instability probability specifically includes: Based on the current cumulative damage factor and the initial mechanical parameter, the dynamic elastic modulus is calculated; This step corresponds to the step in embodiment 2 Formula Based on the current cumulative damage factor and the initial mechanical parameter, the dynamic cohesion is calculated; This step corresponds to the step in embodiment 2 Formula Based on the current cumulative damage factor and the initial mechanical parameter, the dynamic internal friction angle is calculated; This step corresponds to the step in embodiment 2 Formula Based on the real-time shear stress, the real-time load is determined; This step corresponds to the step in embodiment 3

[0044] Based on the real-time normal stress and the dynamic cohesion and the dynamic internal friction angle, the real-time resistance is determined; This step corresponds to the step in embodiment 3 Formula The ratio of the real-time load and the real-time resistance is calculated to generate the time-varying instability risk index; This step corresponds to the step in embodiment 3 Formula The method steps disclosed in the embodiment completely correspond to the system module functions in embodiments 2 and 3; it specifically stipulates the complete operation process of the decision-making hub RPPM; by performing dynamic strength reduction and risk index collection, the method realizes the conversion of the abstract damage state into the quantitative macroscopic strength at the operation level, and further dynamically couples the real-time load and the real-time resistance to calculate a single and explicit warning index, which provides complete and executable algorithm steps for realizing precise early warning.

[0045] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A ground subsidence micro-motion monitoring system, characterized in that, include: The geomechanical model building module is used to build a three-dimensional geological mesh model and provide the initial stress field and initial mechanical parameters; The micro-seismic event interpretation module is used to interpret micro-seismic events in real time and output seismic moments; The damage-stress coupling evolution module is used to receive the seismic moment and, based on the historical cumulative damage factor maintained by the module, calculate the current cumulative damage factor, real-time shear stress, and real-time normal stress. The risk probability prediction module is used to receive the current cumulative damage factor, the real-time shear stress, the real-time normal stress, and the initial mechanical parameters, and calculate the time-varying instability risk index and instability probability. The damage-stress coupling evolution module is specifically used for: Calculate the foundation damage degree based on the seismic moment; Based on the baseline damage level and the historical cumulative damage factor, the damage amplification effect is applied to calculate the actual damage increment. The historical cumulative damage factor is updated based on the actual damage increment to generate the current cumulative damage factor; Based on the change in the current cumulative damage factor, a stress calculation step is performed to generate the real-time shear stress and the real-time normal stress.

2. The ground subsidence micro-motion monitoring system according to claim 1, characterized in that, The risk probability prediction module is specifically used for: Receive the current cumulative damage factor and the initial mechanical parameters; Calculate the dynamic elastic modulus based on the current cumulative damage factor and the initial mechanical parameters; Calculate the dynamic cohesion based on the current cumulative damage factor and the initial mechanical parameters; Calculate the dynamic internal friction angle based on the current cumulative damage factor and the initial mechanical parameters.

3. The ground subsidence micro-motion monitoring system according to claim 2, characterized in that, The risk probability prediction module is also specifically used for: Based on the real-time shear stress, the real-time load is determined; The real-time resistance is determined based on the real-time normal stress, the dynamic cohesion, and the dynamic internal friction angle. The ratio of the real-time load to the real-time resistance is calculated to generate the time-varying instability risk index.

4. The ground subsidence micro-motion monitoring system according to claim 2, characterized in that, The stress calculation step specifically includes: Determine whether the current accumulated damage factor exceeds a preset global trigger threshold; When the current cumulative damage factor does not exceed the global trigger threshold, a preset local stress transfer function is used to calculate the real-time shear stress and the real-time normal stress. When the current cumulative damage factor exceeds the global trigger threshold, the geomechanical model construction module is triggered to perform a global recalculation to generate a global stress field; The global stress field is used to calibrate and output the real-time shear stress and the real-time normal stress.

5. A ground subsidence micro-motion monitoring system according to claim 4, characterized in that, When performing the global recalculation, the geomechanical model construction module is specifically used for: The dynamic elastic modulus calculated by the risk probability prediction module is used as the updated model stiffness for global recalculation.

6. A ground subsidence micro-motion monitoring system according to claim 2, characterized in that, The system also includes: The macroscopic response monitoring module is used to monitor the macroscopic displacement of the soil and rock mass to generate measured displacement data; The model calibration module is used for: Based on the dynamic elastic modulus, the displacement is predicted by the model through the geomechanical model construction module. Calculate the residual between the model-predicted displacement and the measured displacement data; A data assimilation algorithm is used to iteratively adjust the model calibration parameters in the damage-stress coupling evolution module and the risk probability prediction module to minimize the residual.

7. A ground subsidence micro-motion monitoring system according to claim 6, characterized in that, The model calibration parameters include: The calibration coefficient, damage amplification coefficient, nonlinearity index, and material degradation index are related to the basic damage degree.

8. A method for monitoring ground subsidence micro-motion, characterized in that, The method, applied to a ground subsidence micro-motion monitoring system as described in any one of claims 1 to 7, comprises: The micro-seismic event interpretation module interprets micro-seismic events in real time and outputs seismic moments. The seismic moment is received through the damage-stress coupling evolution module, and the current cumulative damage factor, real-time shear stress, and real-time normal stress are calculated based on the historical cumulative damage factor maintained by the module. The risk probability prediction module receives the current cumulative damage factor, the real-time shear stress, the real-time normal stress, and the initial mechanical parameters provided by the geomechanical model construction module, and calculates the time-varying instability risk index and instability probability.

9. A method for monitoring ground subsidence micro-motion according to claim 8, characterized in that, The steps for calculating the current cumulative damage factor, real-time shear stress, and real-time normal stress specifically include: Calculate the foundation damage degree based on the seismic moment; Based on the baseline damage level and the historical cumulative damage factor, the damage amplification effect is applied to calculate the actual damage increment. The historical cumulative damage factor is updated based on the actual damage increment to generate the current cumulative damage factor; Perform a stress calculation step to generate the real-time shear stress and the real-time normal stress; Specifically, the stress calculation step includes: Determine whether the current accumulated damage factor exceeds a preset global trigger threshold; When the current cumulative damage factor does not exceed the global trigger threshold, a preset local stress transfer function is used to calculate the real-time shear stress and the real-time normal stress. When the current cumulative damage factor exceeds the global trigger threshold, the geomechanical model construction module is triggered to perform a global recalculation to generate a global stress field; The global stress field is used to calibrate and output the real-time shear stress and the real-time normal stress.

10. A method for monitoring ground subsidence micro-motion according to claim 8, characterized in that, The steps for calculating the time-varying instability risk index and instability probability specifically include: Calculate the dynamic elastic modulus based on the current cumulative damage factor and the initial mechanical parameters; Calculate the dynamic cohesion based on the current cumulative damage factor and the initial mechanical parameters; Calculate the dynamic internal friction angle based on the current cumulative damage factor and the initial mechanical parameters; Based on the real-time shear stress, the real-time load is determined; The real-time resistance is determined based on the real-time normal stress, the dynamic cohesion, and the dynamic internal friction angle. The ratio of the real-time load to the real-time resistance is calculated to generate the time-varying instability risk index.

Images