Monitoring cooperation method and device suitable for mine pressure relief support

Abstract

The invention discloses a monitoring cooperation method and device suitable for mine pressure relief supporting, relates to the technical field of mine monitoring, and solves the technical problems that in the prior art, pressure relief construction and stress deformation monitoring of a supporting structure are generally independently carried out, data are separated, and the actual influence of the pressure relief effect on the supporting structure is difficult to evaluate. The method comprises the following steps: acquiring pressure relief construction data, surrounding rock stress state data, support structure data and real-time environment data; scoring pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; evaluating the bearing state of the support structure according to the support structure data and the surrounding rock stress state data; performing dynamic feedback on the pressure relief support system according to the real-time environment data; the pressure relief support system is cooperatively adjusted based on the dynamic feedback result; shutdown loss and repair cost caused by sudden accidents can be reduced; meanwhile, accurate pressure relief and supporting adjustment can prolong the service life of a project, and the maintenance cost of the whole life cycle is reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of mine monitoring, and relates to a monitoring and cooperation technology for mine pressure relief support, in particular to a monitoring and cooperation method and device suitable for mine pressure relief support. BACKGROUND

[0002] Mine pressure relief support is a technology for realizing roadway protection by artificially changing the stress distribution state of surrounding rock; its core principle is that, on the basis of the original support form, high stress is transferred to the deep part of the surrounding rock by expanding the roadway excavation section, adopting pressure relief methods or water injection and other measures, so as to reduce the direct damage of high stress of surrounding rock to the support; the pressure relief support technology effectively controls the deformation of surrounding rock, reduces the risk of roadway collapse and damage, and provides a safe and reliable working environment for mine production; the monitoring and cooperation of mine pressure relief support is a technical mode of organically combining various monitoring means with support measures, and realizing dynamic management through data sharing, real-time feedback and cooperative control; in the process of mine exploitation, the working face advances and the geological structure changes, which continuously changes the stress field of surrounding rock; the monitoring and cooperation can track these changes in real time and dynamically adjust the support strategy; maintenance is carried out before the problem expands, avoiding forced production stop due to roadway instability and ensuring continuous production.

[0003] In the prior art, the stress of the pressure relief and the support structure is monitored, and when the support structure appears abnormal or fails, the reasons are investigated and the support structure is optimized; however, in the prior art, the pressure relief construction and the stress deformation monitoring of the support structure are usually carried out independently, the data is separated, and it is difficult to evaluate the actual influence of the pressure relief effect on the support structure. SUMMARY

[0004] The application aims to at least solve one of the technical problems existing in the prior art; for this purpose, the application provides a monitoring and cooperation method and device suitable for mine pressure relief support, which is used to solve the technical problem that in the prior art, the pressure relief construction and the stress deformation monitoring of the support structure are usually carried out independently, the data is separated, and it is difficult to evaluate the actual influence of the pressure relief effect on the support structure.

[0005] To achieve the above-mentioned purpose, the first aspect of the application provides a monitoring and cooperation method suitable for mine pressure relief support, comprising: obtaining pressure relief construction data, surrounding rock stress state data, support structure data and real-time environment data; scoring the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; evaluating the bearing state of the support structure according to the support structure data and the surrounding rock stress state data; dynamically feeding back the pressure relief support system according to the real-time environment data; cooperatively adjusting the pressure relief support system based on the dynamic feedback result.

[0006] Based on the above steps, the pressure relief effect can be quantitatively evaluated through the correlation analysis of the pressure relief construction data and the surrounding rock stress state, which provides data support for subsequent construction parameter adjustment, avoids safety hazards caused by excessive pressure relief or insufficient pressure relief, and improves the scientific nature of construction and resource utilization rate; in combination with the support structure data and the stress change of surrounding rock, the stress state of the support system can be monitored in real time, the overload risk can be identified in advance, the support structure can be reinforced or replaced, and the collapse accident caused by structural failure can be effectively prevented; the feedback mechanism of real-time environmental data enables the system to dynamically respond to changes in external conditions; based on the dynamic feedback of the collaborative adjustment mechanism, the linkage optimization of pressure relief construction, support structure and environmental factors is realized, the traditional passive maintenance is changed into active prevention through the data-driven decision mode, the downtime loss and repair cost caused by sudden accidents are reduced; at the same time, the precise pressure relief and support adjustment can prolong the service life of the project and reduce the maintenance cost of the whole life cycle.

[0007] Preferably, the scoring of the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data comprises: The pressure relief construction data and the surrounding rock stress data are retrieved; wherein the pressure relief construction data comprises: actual depth, actual angle, actual position, and average drilling speed and average torque at the target layer; the surrounding rock stress state data comprises: surrounding rock stress size and direction before and after pressure relief; The pressure relief scoring function is constructed: The score of the pressure relief construction is calculated according to the pressure relief scoring function; wherein, and are weight coefficients greater than 0; represents the surrounding rock stress before pressure relief construction; represents the surrounding rock stress after pressure relief construction; represents the surrounding rock stress background value not directly affected by pressure relief; represents the stress influence range score.

[0008] Preferably, the stress influence range score is obtained in the following manner: The stress significantly decreased influence area is predicted according to the pressure relief construction data to obtain a prediction area; after the pressure relief is completed, the stress drop amplitudes of the prediction area and the adjacent area outside the prediction area are respectively counted; The stress influence range fitting degree function is constructed: The stress influence range fitting degree after pressure relief is calculated according to the stress influence range fitting degree function; wherein, represents the average value of the stress drop amplitude in the prediction area; represents the average value of the adjacent stress drop amplitude outside the prediction area; represents a minimum constant; obtaining a goodness-of-fit threshold value; comparing the stress influence range goodness-of-fit with the goodness-of-fit threshold value; when the stress influence range goodness-of-fit is not less than a first goodness-of-fit threshold value, then the stress influence range score is 100; otherwise, comparing the stress influence range goodness-of-fit with a second goodness-of-fit threshold value; wherein the goodness-of-fit threshold value comprises the first goodness-of-fit threshold value and the second goodness-of-fit threshold value; the first goodness-of-fit threshold value is greater than the second goodness-of-fit threshold value; when the stress influence range goodness-of-fit is less than the second goodness-of-fit threshold value, then the expression of the stress influence range score is: otherwise, the expression of the stress influence range score is: .

[0009] It should be noted that the goodness-of-fit threshold value is set by professionals according to experience, and the first goodness-of-fit threshold value is generally set to 3; the second goodness-of-fit threshold value is set to 1; the extremely small constant is set according to the actual situation to prevent the denominator from being 0; it can be ignored in actual calculation; the value of the extremely small constant is generally set to 0.001.

[0010] Preferably, the evaluation of the bearing state of the support structure according to the support structure data and the surrounding rock stress state data comprises: retrieving the support structure data, and obtaining a state diagnosis library; wherein the support structure data comprises: anchor rod axial force, support pressure and surface convergence; analyzing and calculating evaluation indexes of the support structure according to the support structure data and the surrounding rock stress state data; matching the evaluation indexes with the state diagnosis library to obtain a comprehensive classification of the bearing state of the support structure; wherein the evaluation indexes comprise: support unit instantaneous load rate, support load collaborative change coefficient, support load uniform distribution index, and stress response sensitivity.

[0011] Preferably, the analysis and calculation of the evaluation indexes of the support structure according to the support structure data and the surrounding rock stress state data comprises: retrieving the support structure data and the surrounding rock stress data; matching the time and space of the support structure data and the surrounding rock stress data to obtain a plurality of sets of analysis data; dividing the plurality of sets of analysis data according to a preset time period; wherein the preset time period comprises: a stable period before pressure relief construction, a stress intense adjustment period after pressure relief construction, and a stress redistribution stable period; constructing a support unit instantaneous load rate analysis function: ; calculating the support unit instantaneous load rate according to the support unit instantaneous load rate analysis function; wherein, represents the real-time measured load of the i th support unit; represents the preset bearing load of the i th support unit; constructing a support load collaborative change coefficient analysis function: ; calculating the support load coordination change coefficient of the support structure according to the support load coordination change coefficient analysis function; is a stress redistribution stable period; is a stable period before pressure relief construction; represents a conversion coefficient of the surrounding rock area or volume controlled by the support structure; ; represents the stress drop value of the surrounding rock; calculating the average value and the standard deviation of the real-time measured load of the support structure in the stress redistribution stable period; through the formula calculating the support load uniform distribution index; wherein, is the average value of the real-time measured load; is the standard deviation of the real-time measured load; fitting the surrounding rock stress size from the stable period before pressure relief construction to the stress redistribution stable period and the real-time measured load of the support structure respectively, to obtain the surrounding rock stress curve σ(t) and the support load curve F(t); calculating the correlation coefficient of the surrounding rock stress curve and the support load curve; analyzing the lag time of the support load curve relative to the surrounding rock stress curve.

[0012] Preferably, the calculation of the correlation coefficient of the surrounding rock stress curve and the support load curve comprises: calling the surrounding rock stress curve and the support load curve; selecting the values of the collection points from the surrounding rock stress curve and the support load curve respectively and integrating them into sequences to obtain the surrounding rock stress sequence and the support load sequence; calculating the average value of the surrounding rock stress sequence and the support load sequence respectively; calculating the deviation between each collection point and the average value; obtaining the covariance sum by calculating the product sum of the deviations of the two sequences; calculating the square sum of the deviations of the surrounding rock stress sequence and the support load sequence respectively to obtain the surrounding rock stress variance sum and the support load variance sum; through the formula calculating the correlation coefficient of the surrounding rock stress curve and the support load curve; wherein, represents the covariance sum; represents the surrounding rock stress variance sum; represents the support load variance sum; represents the standardization function.

[0013] Preferably, the dynamic feedback of the pressure relief support system according to the real-time environmental data comprises: calling the real-time environmental data; wherein, the real-time environmental data comprises: ground sound data and roadway deformation data; the ground sound data comprises: extraction event rate, energy accumulation and event concentration; the roadway deformation data comprises: roof separation increment, separation rate and surface convergence rate; The real-time environment data in a set time period, the comprehensive classification of the bearing state of the support structure, and the score of the pressure relief construction are integrated into a dynamic feedback sequence according to the collection time; the dynamic feedback model is called; the dynamic feedback sequence is input into the dynamic feedback model to obtain a corresponding feedback label; wherein the feedback label is set to a positive integer; the dynamic feedback model is constructed based on an artificial intelligence model.

[0014] Preferably, the dynamic feedback model is constructed based on an artificial intelligence model, comprising: selecting a model and a deep learning framework from an artificial intelligence model library; constructing the model based on the deep learning framework to obtain an intelligent model; obtaining a standard data set; wherein the standard data set includes standard input data consistent with the content attributes of the dynamic feedback sequence, and standard output data consistent with the content attributes of the feedback label; dividing the standard data set into a training set, a validation set, and a test set according to a set proportion; training the intelligent model using the training set; adjusting the internal parameters of the intelligent model using the validation set; testing the intelligent model using the test set to obtain a test index; obtaining an index threshold; comparing the test index with the index threshold; when the test index is greater than the index threshold, marking the intelligent model as a dynamic feedback model; otherwise, re-construction and training of the dynamic feedback model.

[0015] It should be noted that the test index includes accuracy, recall rate, F1 score, and stability; the index threshold and the division proportion of the standard data set are set by technical personnel according to the actual scene.

[0016] Preferably, the dynamic feedback result is based on the dynamic feedback result to adjust the pressure relief support system, comprising: obtaining a collaborative adjustment library; calling the feedback label; matching the feedback label with the collaborative adjustment library to obtain corresponding collaborative adjustment measures; sending the collaborative adjustment measures to the corresponding technical personnel to collaboratively adjust the pressure relief support system.

[0017] The second aspect of the present application provides a monitoring and collaborative device suitable for mine pressure relief support, comprising: a data acquisition unit, a state evaluation unit, and a feedback adjustment unit; The data acquisition unit is used to acquire pressure relief construction data, surrounding rock stress state data, support structure data, and real-time environment data. The state evaluation unit is used to score the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; and evaluate the bearing state of the support structure according to the support structure data and the surrounding rock stress state data. The feedback adjustment unit is configured to perform dynamic feedback on the pressure relief support system according to real-time environmental data, and perform collaborative adjustment on the pressure relief support system based on the dynamic feedback result.

[0018] The third aspect of the present application provides a computer readable storage medium, which stores instructions for performing the method steps in any possible implementation manner of the first aspect.

[0019] Compared with the prior art, the present application has the following beneficial effects: 1. The ratio of the stress difference of the surrounding rock before and after pressure relief to the background stress difference directly reflects the actual stress reduction effect of pressure relief construction on the target area, avoiding subjective evaluation bias; the stress reduction area is predicted based on actual construction data, and the stress reduction amplitude of the predicted area and the adjacent area is statistically predicted to verify the prediction accuracy, providing data support for subsequent construction parameter optimization; by analyzing the relationship between actual drilling speed, torque and other construction data and stress release effect, the influence law of key parameters on pressure relief effect can be identified, providing a basis for adjusting construction parameters; setting a first and second threshold value, the pressure relief effect is evaluated differently; when the degree of agreement is lower than the second threshold value, the score is directly deducted in proportion, and the low-efficiency construction is quickly identified; when the degree of agreement is between the two threshold values, linear scoring is adopted to encourage gradual improvement; the scoring result can directly reflect the pressure relief effect grade, providing graded early warning for engineering safety; the pressure relief scoring function considers the stress release degree and influence range at the same time, avoiding the one-sidedness of a single index; through the scoring result, the low-efficiency construction link is identified, the excessive pressure relief or repeated construction is reduced, and the material and time cost is reduced; timely intervention is made to the construction with low influence range agreement, avoiding local stress concentration caused by uneven pressure relief, and improving the overall structural safety.

[0020] 2、Support structure data and surrounding rock stress data are matched in time and space to eliminate misjudgment caused by data misplacement and ensure that the analysis results truly reflect the interaction between support and surrounding rock; by dividing the stable period before pressure relief construction, the stress adjustment period, and the stress redistribution stable period, the dynamic response characteristics of the support structure at different stages are captured to provide a basis for phased intervention; the current load of the support unit is directly reflected by the immediate load rate, which is the ratio of the current load to the designed bearing capacity, to quickly identify overload risks; the collaborative change coefficient quantifies the collaboration between support load and surrounding rock stress changes, revealing the coupling strength between the support system and the surrounding rock; the uniform distribution index evaluates the uniformity of the support structure stress through the ratio of the load standard deviation to the mean value; stress response sensitivity analyzes the hysteresis of support load changes relative to surrounding rock stress changes to determine the response speed of the support system to surrounding rock deformation; by fitting the surrounding rock stress curve and the support load curve, the correlation between the two is revealed; multiple indexes are integrated into an evaluation vector, matched with a state diagnosis library, and the support structure state classification is output; it can be directly associated with maintenance strategies; it avoids over-maintenance or insufficient maintenance and reduces the life cycle cost.

[0021] 3、Ground sound data and roadway deformation data are integrated in time sequence to eliminate the limitations of a single data source; ground sound data can detect early micro-fracture activities in surrounding rock and reflect potential instability risks; roadway deformation data directly quantifies the deformation degree of the support structure to verify the reliability of ground sound early warning; combined with support structure comprehensive classification and pressure relief construction scoring, a "environment-support-construction" three-dimensional correlation data chain is formed to provide comprehensive input for model analysis; the collaborative adjustment library predefines standardized response plans for different feedback labels to avoid subjective human decision-making. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 A schematic diagram of the overall steps of the method of the present application; Figure 2 A schematic diagram of the pressure relief construction scoring step of the present application; Figure 3 A schematic diagram of the support structure bearing state evaluation step of the present application; Figure 4 A schematic diagram of the dynamic feedback adjustment step of the present application; Figure 5 A schematic diagram of the device unit connection of the present application. DETAILED DESCRIPTION

[0024] The technical solutions of this application will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0025] Please see Figure 1 The first aspect of this application provides a monitoring and coordination method suitable for mine pressure relief support, comprising: S101. Obtain pressure relief construction data, surrounding rock stress state data, support structure data, and real-time environmental data. S102. Score the pressure relief construction based on the pressure relief construction data and the surrounding rock stress state data; S103. Evaluate the bearing capacity of the support structure based on the support structure data and the surrounding rock stress state data. S104. Dynamically provide feedback to the pressure relief support system based on real-time environmental data; S105. Based on the dynamic feedback results, the pressure relief support system is adjusted in a coordinated manner.

[0026] Based on the above steps, the correlation analysis between decompression construction data and surrounding rock stress state allows for a quantitative assessment of the decompression effect, providing data support for subsequent construction parameter adjustments. This avoids safety hazards caused by excessive or insufficient decompression, improving construction scientificity and resource utilization. Combining support structure data with surrounding rock stress changes enables real-time monitoring of the support system's stress state, early identification of overload risks, and early warning for support structure reinforcement or replacement, effectively preventing collapse accidents caused by structural failure. A real-time environmental data feedback mechanism allows the system to dynamically respond to changes in external conditions. A collaborative adjustment mechanism based on dynamic feedback enables the coordinated optimization of decompression construction, support structure, and environmental factors. Through a data-driven decision-making model, traditional passive maintenance is transformed into proactive prevention, reducing downtime losses and repair costs due to sudden accidents. Simultaneously, precise decompression and support adjustments can extend the project's service life and reduce total life-cycle maintenance costs.

[0027] In one possible implementation of the embodiments of this application, combined with Figure 1 ,like Figure 2 As shown, the above S102 can be specifically implemented through the following S201-S205, which are explained in detail below: S201. Retrieve pressure relief construction data and surrounding rock stress data; predict the area affected by significant stress reduction based on pressure relief construction data, and obtain the prediction area; after pressure relief is completed, statistically analyze the stress reduction range in the prediction area and the adjacent area outside the prediction area.

[0028] wherein, the pressure-relief construction data comprises: actual depth, actual angle, actual position, and average drilling speed and average torque at the target layer; the surrounding rock stress state data comprises: surrounding rock stress magnitude and direction before and after pressure relief.

[0029] S202, construct a stress influence range fitness function: ; calculate the stress influence range fitness after pressure relief according to the stress influence range fitness function.

[0030] wherein, represents the average value of the stress drop amplitude in the prediction area; represents the average value of the adjacent stress drop amplitude outside the prediction area; represents a minimum constant.

[0031] S203, obtain a fitness threshold value; compare the stress influence range fitness with the fitness threshold value; when the stress influence range fitness is not less than a primary fitness threshold value, the stress influence range score is 100; otherwise, compare the stress influence range fitness with a secondary fitness threshold value.

[0032] wherein, the fitness threshold value comprises a primary fitness threshold value and a secondary fitness threshold value; the primary fitness threshold value is greater than the secondary fitness threshold value.

[0033] S204, when the stress influence range fitness is less than the secondary fitness threshold value, the expression of the stress influence range score is: ; otherwise, the expression of the stress influence range score is: .

[0034] S205, construct a pressure-relief score function: ; calculate the score of pressure-relief construction according to the pressure-relief score function.

[0035] wherein, and are weight coefficients greater than 0; represents the surrounding rock stress before pressure relief; represents the surrounding rock stress after pressure relief; represents the surrounding rock stress background value not directly affected by pressure relief; represents the stress influence range score.

[0036] Example: a certain coal mine tunnel adopts deep-hole blasting pressure relief, the target layer is sandstone of coal seam roof, the thickness is 8m, and the original stress is 25MPa; Pressure relief construction data: Actual depth = 12m (design 10m, extra depth 2m); Actual angle = 85° (design 90°, deviation -5°); Average drilling speed = 1.2m / min (reflecting rock hardness); Average torque = 350N·m (reflecting drilling resistance); Surrounding rock stress data: Stress before decompression: 25 MPa; Stress in the predicted area after decompression: 18 MPa; Stress in the adjacent area: 22 MPa; Background stress: 24 MPa (areas not affected by decompression). Based on drilling parameters and stress monitoring data, numerical simulation predicts that the stress will decrease significantly within 15m on both sides of the roadway (the design value is 12m). The stress influence range fit function is used to calculate the stress influence range fit, which is 0.693; the first threshold is 0.8 and the second threshold is 0.5; since 0.5 ≤ 0.693 < 0.8, the formula is used: FB = 50 + (0.693 - 1) × 25 = 42.675.

[0037] Parameter settings: α=0.6 (stress reduction weight), β=0.4 (influence range weight); the score obtained by function calculation is 437.07; result analysis: the score is high, but the influence range score is low, and the arrangement of blasting holes needs to be optimized to expand the pressure relief range.

[0038] Based on the above steps, the ratio of the stress difference in the surrounding rock before and after stress relief to the background stress difference directly reflects the actual stress reduction effect of the stress relief construction on the target area, avoiding subjective evaluation bias. The stress reduction area is predicted based on actual construction data, and the accuracy of the prediction is verified by statistically analyzing the stress reduction magnitude between the predicted area and adjacent areas, providing data support for subsequent optimization of construction parameters. By analyzing the relationship between actual drilling speed, torque, and other construction data and the stress release effect, the influence of key parameters on the stress relief effect can be identified, providing a basis for adjusting construction parameters. First-level and second-level thresholds are set to differentiate the stress relief effect. Differentiation evaluation: When the conformity is below the secondary threshold, points are deducted proportionally to quickly identify inefficient construction; when the conformity is between the two thresholds, linear points are added to encourage gradual improvement; the scoring results can intuitively reflect the pressure relief effect level, providing graded early warning for project safety; the pressure relief scoring function considers both the degree of stress release and the scope of influence, avoiding the one-sidedness of a single indicator; inefficient construction links are identified through the scoring results, reducing excessive pressure relief or repeated construction, and lowering material and time costs; timely intervention is provided for construction with low conformity in the scope of influence to avoid local stress concentration caused by uneven pressure relief, thereby improving the overall structural safety.

[0039] In one possible implementation of the embodiments of this application, combined with Figure 1 ,like Figure 3As shown, the above S103 can be specifically implemented through the following S301-S305, which are explained in detail below: S301. Retrieve support structure data and surrounding rock stress data; match the support structure data and surrounding rock stress data in time and space to obtain several sets of analysis data; divide the several sets of analysis data according to preset time periods; The support structure data includes: anchor bolt axial force, support pressure, and surface convergence; the preset time periods include: the stabilization period before pressure relief construction, the period of intense stress adjustment after pressure relief construction, and the period of stress redistribution stabilization.

[0040] S302. Construct the instantaneous load rate analysis function for the support unit: The instantaneous load rate of the support unit is calculated based on the instantaneous load rate analysis function of the support unit.

[0041] in, This represents the real-time measured load of the i-th support unit; This represents the preset load-bearing capacity of the i-th support unit.

[0042] S303. Constructing the analysis function for the coefficient of coordinated variation of support load: The coefficient of variation of the support load is calculated based on the analysis function of the coefficient of variation of the support load.

[0043] in, This is the period of stable stress redistribution; This is the stabilization period before depressurization construction; A conversion factor representing the area or volume of surrounding rock controlled by the support structure; ; indicates the decrease in stress in the surrounding rock.

[0044] S304. Calculate the average value and standard deviation of the real-time measured loads on the support structure during the stress redistribution stabilization period; using the formula... Calculate the uniformity distribution index of the support load.

[0045] in, To measure the average value of the load in real time; This is for measuring the standard deviation of the load in real time.

[0046] S305. Fit the magnitude of the surrounding rock stress and the real-time measured load of the support structure during the period from the stabilization period before the pressure relief construction to the stabilization period of stress redistribution, respectively, to obtain the surrounding rock stress curve σ(t) and the support load curve F(t); calculate the correlation coefficient between the surrounding rock stress curve and the support load curve; and analyze the lag time of the support load curve relative to the surrounding rock stress curve.

[0047] S306. Integrate the instantaneous load rate of the support unit, the coefficient of coordinated variation of the support load, the uniform distribution index of the support load, and the stress response sensitivity into an evaluation index for the support structure; obtain the condition diagnosis library; match the evaluation index with the condition diagnosis library to obtain a comprehensive classification of the bearing condition of the support structure.

[0048] It should be noted that the correlation coefficients for calculating the surrounding rock stress curve and the support load curve include: Retrieve the surrounding rock stress curve and the support load curve; select the data points from the surrounding rock stress curve and the support load curve respectively and integrate them into a sequence to obtain the surrounding rock stress sequence and the support load sequence. Calculate the average values ​​of the surrounding rock stress sequence and the support load sequence respectively; calculate the deviation between each sampling point and the average value; obtain the covariance by calculating the product of the deviations of the two sequences. Calculate the sum of squares of the deviations from the surrounding rock stress sequence and the support load sequence respectively to obtain the sum of variances of the surrounding rock stress and the support load; then use the formula... Calculate the correlation coefficient between the surrounding rock stress curve and the support load curve; among which, Represents the sum of covariances; This represents the sum of the variances of the surrounding rock stress. This represents the sum of the variances of the support loads; This represents the standardized function.

[0049] Example: The tunnel uses anchor bolts + steel strip support, with anchor bolts of 22mm diameter and a spacing of 1.0m; Support data: Anchor bolt axial force = 120kN (design 150kN, bearing capacity 80%); Support pressure = 0.8MPa; Surface convergence rate = 1.5mm / d; Stress data: Stress during the stabilization period before pressure relief = 25 MPa; Stress fluctuation during the period of severe stress adjustment (0-3 days) = 18-22 MPa; Stress during the stabilization period (after 7 days) = 18 MPa; Time period division: Stabilization period (T0): -7 days to 0 days; Adjustment period (T1): 0-3 days; Stabilization period (T2): 7-14 days; The real-time axial force of the first anchor rod is 110kN, and the design load is 150kN. The calculated instantaneous load rate of the first support unit is 0.733. Similarly, the instantaneous load rates of all support units of the support structure are calculated. Result analysis: The load rates of some anchor rods exceed 80%, and the anchoring quality needs to be checked.

[0050] Will The value was set to 1.0; the coefficient of variation of support load was calculated to be -8.45; the results showed that the support load was negatively correlated with the stress reduction, indicating that the support system effectively suppressed the deformation of the surrounding rock.

[0051] The calculated average real-time axial force is 115 kN, with a standard deviation of 10 kN. The uniformity index of the support load is 0.913. The results show that the load distribution is relatively uniform with no local stress concentration.

[0052] Curve fitting: Surrounding rock stress σ(t) = 25e^(-0.1t) + 18; Support load F(t) = 150e^(-0.05t) + 110 (kN); Correlation coefficient R = 0.95 (strong positive correlation); Lag time = 2 days (support response lags behind stress change); Result analysis: The initial stiffness of the support system needs to be increased to shorten the lag time.

[0053] Status diagnosis database matching: The overall classification is "sub-healthy", requiring enhanced monitoring and localized reinforcement of anchor bolts.

[0054] Based on the above steps, the support structure data and surrounding rock stress data are synchronously matched in time and space to eliminate misjudgments caused by data misalignment and ensure that the analysis results truly reflect the interaction between the support and the surrounding rock. By dividing the period into the pre-decompression construction stabilization period, the period of severe stress adjustment, and the period of stress redistribution stabilization, the dynamic response characteristics of the support structure at different stages are captured, providing a basis for phased intervention. The instantaneous load rate directly reflects the ratio of the current load of the support unit to the design bearing capacity, quickly identifying the risk of overload. The synergistic variation coefficient is used to quantify the synergy between the support load and the surrounding rock stress changes, revealing the coupling strength between the support system and the surrounding rock. The uniformity distribution index assesses the uniformity of stress on the support structure by the ratio of the load standard deviation to the mean. The stress response sensitivity analysis determines the lag of the support load change relative to the surrounding rock stress change, judging the response speed of the support system to the deformation of the surrounding rock. By fitting the surrounding rock stress curve and the support load curve, the correlation between their changing trends is revealed. Multiple indicators are integrated into an evaluation vector, matched with the condition diagnosis library, and output the condition classification of the support structure. This can be directly associated with maintenance strategies, avoiding over-maintenance or under-maintenance and reducing the total life cycle cost.

[0055] In one possible implementation of the embodiments of this application, combined with Figure 1 ,like Figure 4 As shown, the above S104-S105 can be specifically implemented through the following S401-S403, which are explained in detail below: S401. Retrieve real-time environmental data; integrate the real-time environmental data within the set time period, the comprehensive classification of the support structure's bearing status, and the score of the pressure relief construction into a dynamic feedback sequence according to the collection time.

[0056] The real-time environmental data includes: ground sound data and tunnel deformation data; the ground sound data includes: extracted event rate, energy accumulation and event concentration; the tunnel deformation data includes: roof delamination increment, delamination rate and surface convergence rate.

[0057] S402. Call the dynamic feedback model; input the dynamic feedback sequence into the dynamic feedback model to obtain the corresponding feedback label.

[0058] The feedback label is set to a positive integer; the dynamic feedback model is built based on an artificial intelligence model.

[0059] In one possible implementation, the dynamic feedback model is built upon an artificial intelligence model, including: Select models and deep learning frameworks from the artificial intelligence model library; build intelligent models based on the deep learning frameworks; Obtain the standard dataset; the standard dataset includes standard input data consistent with the content attributes of the dynamic feedback sequence; and standard output data consistent with the content attributes of the feedback labels; The standard dataset is divided into a training set, a validation set, and a test set according to a set ratio; the intelligent model is trained using the training set; the internal parameters of the intelligent model are adjusted using the validation set; and the intelligent model is tested using the test set to obtain test metrics. Obtain the indicator threshold; compare the test indicator with the indicator threshold; if all test indicators are greater than the indicator threshold, mark the intelligent model as a dynamic feedback model; otherwise, rebuild and retrain the dynamic feedback model.

[0060] S403. Obtain the collaborative adjustment library; retrieve feedback tags; match the feedback tags with the collaborative adjustment library to obtain the corresponding collaborative adjustment measures; send the collaborative adjustment measures to the corresponding technical personnel to perform collaborative adjustment on the pressure relief support system.

[0061] For example, real-time environmental data within a set time period, comprehensive classification of the support structure's bearing state, and scores of pressure relief construction are integrated into a dynamic feedback sequence according to the collection time; the dynamic feedback sequence is input into the dynamic feedback model, and the corresponding feedback label is 3. Retrieve the measures corresponding to tag=3 from the collaborative adjustment library: reduce the blast hole spacing from 3m to 2.5m; increase the anchor bolt preload to 120kN; increase the monitoring frequency to once per hour.

[0062] Based on the above steps, the ground sound data and tunnel deformation data are integrated synchronously in a time series to eliminate the limitations of a single data source. Ground sound data can detect micro-fractures in the surrounding rock in advance and reflect potential instability risks. Tunnel deformation data directly quantifies the degree of deformation of the support structure and verifies the reliability of ground sound early warning. Combining the comprehensive classification of the support structure and the pressure relief construction score, a three-dimensional correlation data chain of "environment-support-construction" is formed to provide comprehensive input for model analysis. The collaborative adjustment library has preset standardized response plans for different feedback labels to avoid the subjectivity of human decision-making.

[0063] Referring to Figure 5 The second aspect of the application provides a monitoring and coordinating device suitable for mine pressure relief support, comprising a data acquisition unit, a state evaluation unit and a feedback adjustment unit. The data acquisition unit is configured to acquire pressure relief construction data, surrounding rock stress state data, support structure data and real-time environmental data. The state evaluation unit is configured to score the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data, and evaluate the bearing state of the support structure according to the support structure data and the surrounding rock stress state data. The feedback adjustment unit is configured to dynamically feedback the pressure relief support system according to the real-time environmental data, and cooperatively adjust the pressure relief support system based on the dynamic feedback result.

[0064] The third aspect of the application provides a computer readable storage medium, which stores instructions for executing the method steps in any possible implementation manner of the first aspect.

[0065] Some data in the above formula is calculated by removing the dimension and taking the numerical value, the formula is obtained by software simulation of a large amount of collected data to obtain a formula closest to the real situation; the preset parameters and the preset threshold in the formula are set by a person skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0066] The working principle of the application is as follows: the application acquires pressure relief construction data, surrounding rock stress state data, support structure data and real-time environmental data; scores the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; evaluates the bearing state of the support structure according to the support structure data and the surrounding rock stress state data; dynamically feedbacks the pressure relief support system according to the real-time environmental data; cooperatively adjusts the pressure relief support system based on the dynamic feedback result.

[0067] The above embodiments are only used to illustrate the technical method of the application and not to limit it. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the application.

Claims

1. A monitoring synergic method suitable for mine pressure relief support, characterized in that, The method comprises the following steps: acquiring pressure relief construction data, surrounding rock stress state data, support structure data, and real-time environmental data; scoring the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; evaluating the bearing state of the support structure according to the support structure data and the surrounding rock stress state data; performing dynamic feedback on the pressure relief support system according to the real-time environmental data; performing collaborative adjustment on the pressure relief support system based on the dynamic feedback result.

2. The monitoring and coordinating method suitable for mine pressure relief support of claim 1, characterized in that, The scoring of the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data comprises the following steps: retrieving the pressure relief construction data and the surrounding rock stress data; wherein the pressure relief construction data comprises the actual depth, the actual angle, the actual position, and the average drilling speed and the average torque at the target layer; and the surrounding rock stress state data comprises the surrounding rock stress size and direction before and after pressure relief; A pressure relief construction score function is constructed: A pressure relief construction score is calculated according to the pressure relief construction score function; wherein, and are weight coefficients greater than 0; represents the stress of the surrounding rock before pressure relief construction; represents the stress of the surrounding rock after pressure relief construction; represents the stress background value of the surrounding rock not directly affected by pressure relief; represents the stress influence range score.

3. The monitoring and coordinating method suitable for mine pressure relief support of claim 2, characterized in that, The stress influence range score is obtained in the following manner: predicting the influence area where the stress is significantly reduced according to the pressure relief construction data to obtain a predicted area; after the pressure relief is completed, the stress reduction amplitudes of the predicted area and the adjacent area outside the predicted area are respectively counted; constructing a stress influence range fitness function: calculating the stress influence range fitness after pressure relief according to the stress influence range fitness function; wherein, represents the average value of stress drop in the prediction area; represents the average value of adjacent stress drop outside the prediction area; represents a minimum constant; an agreement threshold is obtained; the stress influence range agreement is compared with the agreement threshold; when the stress influence range agreement is not less than the first-level agreement threshold, the stress influence range score is 100; otherwise, the stress influence range agreement is compared with the second-level agreement threshold; wherein the agreement threshold comprises the first-level agreement threshold and the second-level agreement threshold; the first-level agreement threshold is greater than the second-level agreement threshold; When the stress impact range goodness of fit is less than the secondary goodness of fit threshold, then the expression for the stress impact range score is: ; otherwise, the expression for the stress impact range score is: .

4. The monitoring and coordinating method suitable for mine pressure relief support of claim 1, characterized in that, The evaluation of the bearing state of the support structure according to the support structure data and the surrounding rock stress state data comprises the following steps: retrieving the support structure data and obtaining a state diagnosis library; wherein the support structure data comprises the anchor rod axial force, the support pressure, and the surface convergence; analyzing and calculating the evaluation indexes of the support structure according to the support structure data and the surrounding rock stress state data; matching the evaluation indexes with the state diagnosis library to obtain the comprehensive classification of the bearing state of the support structure; wherein the evaluation indexes comprise the support unit instantaneous load rate, the support load collaborative change coefficient, the support load uniform distribution index, and the stress response sensitivity.

5. A monitoring and coordinating method suitable for mine pressure relief support according to claim 4, characterized in that, The analysis and calculation of the evaluation indexes of the support structure according to the support structure data and the surrounding rock stress state data comprise the following steps: retrieving the support structure data and the surrounding rock stress data; matching the time and space of the support structure data and the surrounding rock stress data to obtain a plurality of sets of analysis data; dividing the plurality of sets of analysis data according to a preset time period; wherein the preset time period comprises a stable period before pressure relief construction, a stress intense adjustment period after pressure relief construction, and a stress redistribution stable period; constructing a support unit instant load rate analysis function: ; calculating the support unit instant load rate according to the support unit instant load rate analysis function; wherein, represents the real-time measured load of the i th support unit; represents the preset load borne by the i th support unit; A support load cooperative change coefficient analysis function is constructed: ; a support load cooperative change coefficient of the support structure is calculated according to the support load cooperative change coefficient analysis function; wherein, is a stress redistribution stable period; is a stable period before pressure relief construction; represents a conversion coefficient of the area or volume of the surrounding rock controlled by the support structure; ; represents a surrounding rock stress drop value; calculating the average value and the standard deviation of the real-time measured load of the support structure in the stress redistribution stable period; calculating the support load uniform distribution index by the formula calculating the average value and the standard deviation of the real-time measured load of the support structure in the stress redistribution stable period; calculating the support load uniform distribution index by the formula is the average value of the real-time measured load; is the standard deviation of the real-time measured load; fitting the real-time measured load of the support structure and the surrounding rock stress size from the stable period before pressure relief construction to the stress redistribution stable period to obtain a surrounding rock stress curve σ(t) and a support load curve F(t); calculating the correlation coefficient of the surrounding rock stress curve and the support load curve; analyzing the lag time of the support load curve relative to the surrounding rock stress curve.

6. The monitoring and coordinating method suitable for mine pressure relief support of claim 5, wherein, The calculation of the correlation coefficient of the surrounding rock stress curve and the support load curve comprises the following steps: Call the surrounding rock stress curve and the support load curve; respectively, the values of the collection points are selected from the surrounding rock stress curve and the support load curve and integrated into sequences to obtain the surrounding rock stress sequence and the support load sequence; The average values of the surrounding rock stress sequence and the support load sequence are calculated respectively; the deviations between each collection point and the average value are calculated; the covariance sum is obtained by calculating the product of the deviations of the two sequences; Calculate the square sum of the bias of the surrounding rock stress sequence and the supporting load sequence respectively to obtain the surrounding rock stress variance sum and the supporting load variance sum; calculate the correlation coefficient of the surrounding rock stress curve and the supporting load curve through the formula wherein, denotes the covariance sum; denotes the surrounding rock stress variance sum; denotes the supporting load variance sum; denotes the standardization function.

7. The monitoring and coordinating method suitable for mine pressure relief support of claim 1, wherein, The dynamic feedback of the pressure relief support system according to the real-time environmental data comprises: Call the real-time environmental data; wherein, the real-time environmental data comprises: ground sound data and roadway deformation data; the ground sound data comprises: extraction event rate, energy accumulation and event concentration; the roadway deformation data comprises: roof separation increment, separation rate and surface convergence rate; The real-time environmental data in the set time period, the comprehensive classification of the bearing state of the support structure and the score of the pressure relief construction are integrated into a dynamic feedback sequence according to the collection time; a dynamic feedback model is called; the dynamic feedback sequence is input into the dynamic feedback model to obtain the corresponding feedback label; wherein, the feedback label is set to a positive integer; the dynamic feedback model is constructed based on an artificial intelligence model.

8. The monitoring and coordinating method suitable for mine pressure relief support of claim 7, characterized in that, The dynamic feedback model is constructed based on an artificial intelligence model, comprising: Select a model and a deep learning framework from an artificial intelligence model library; the model is constructed based on the deep learning framework to obtain an intelligent model; Obtain a standard data set; wherein, the standard data set comprises standard input data consistent with the content attributes of the dynamic feedback sequence; and standard output data consistent with the content attributes of the feedback label; Divide the standard data set into a training set, a validation set and a test set according to a set proportion; train the intelligent model using the training set; adjust the internal parameters of the intelligent model using the validation set; test the intelligent model using the test set to obtain a test index; Obtain an index threshold; compare the test index with the index threshold; when the test index is greater than the index threshold, mark the intelligent model as a dynamic feedback model; otherwise, re-construct and train the dynamic feedback model.

9. The monitoring and coordinating method suitable for mine pressure relief support of claim 1, wherein, The collaborative adjustment of the pressure relief support system based on the dynamic feedback result comprises: Obtain a collaborative adjustment library; call the feedback label; match the feedback label with the collaborative adjustment library to obtain the corresponding collaborative adjustment measures; Send the collaborative adjustment measures to the corresponding technical personnel to collaboratively adjust the pressure relief support system.

10. A monitoring and coordinating device suitable for mine pressure relief support, applied to the monitoring and coordinating method suitable for mine pressure relief support according to any one of claims 1-9, characterized in that, Comprise: Data acquisition unit, state evaluation unit and feedback adjustment unit; The data acquisition unit is used to acquire pressure relief construction data, surrounding rock stress state data, support structure data and real-time environmental data; The state evaluation unit is used to score the pressure relief construction according to the pressure relief construction data and the surrounding rock stress state data; The bearing state of the support structure is evaluated according to the support structure data and the surrounding rock stress state data; The feedback adjustment unit is used to dynamically feedback the pressure relief support system according to the real-time environmental data; Collaboratively adjust the pressure relief support system based on the dynamic feedback result.

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