Mine filling mechanical property detection method and system

Abstract

The present invention relates to the field of mechanical property detection technology, specifically to a method and system for detecting the mechanical properties of mine filling bodies, comprising the following steps: obtaining data measured by multiple groups of displacement sensors and strain gauges in the filling body, detecting the sensor output values ​​of multiple measuring points under initial loading, screening the measuring points with complete response signals and judging the loading response trend, and generating a group of loading response change curves. In the present invention, the stability and representativeness of the measuring point signals are ensured by screening and trend analysis of multiple groups of response data, the heterogeneous areas are located based on the response deviations between the measuring points, spatial difference identification is achieved, the displacement slope, loading rate and strain rate are extracted to calculate the local compressive factor, and a strength distribution map is formed. During the unloading stage, strain recovery characteristics are collected to quantify the elastic performance, low elasticity areas are screened and combined with the compressive factor, and the performance synchronous degradation points are identified. By calculating the difference between data, spatial mapping and multi-parameter superposition, quantitative, visual and trend identification of mechanical properties is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical performance detection, and in particular to a method and system for detecting the mechanical performance of mine filling bodies. Background Art

[0002] The field of mechanical performance testing technology includes a technical system for testing, analyzing and evaluating the physical responses of various materials or structures under stress conditions. The core content of this field is to obtain the performance parameters of materials in different mechanical environments through stress-strain testing, destructive strength analysis, elastic modulus measurement and other means, so as to evaluate their applicability and safety. Mechanical performance testing is widely used in civil engineering, mining, metallurgy, building materials, aerospace and other fields, and the test objects include metal materials, non-metallic materials, composite materials and consolidated structures. According to the purpose of testing and the difference in environment, the entire technical field has developed a variety of means such as indoor static loading tests, in-situ testing technology, non-destructive testing technology and strain monitoring to meet the actual needs of engineering safety assessment and material selection.

[0003] Among them, the mechanical property testing method of mine filling refers to the testing method for the strength, stability and mechanical response of artificial filling used in mine goaf. The technical matters involved in this topic mainly include using a loading device to perform axial or triaxial loading tests on the filling after it is formed, combining a stress and strain measuring device to record the data during the deformation process, and analyzing its compressive strength and deformation modulus based on the deformation and failure behavior during the loading process. The testing method usually collects response parameters through instruments such as pressure sensors, displacement meters or strain gauges installed on the filling samples in the mine recovery tunnel or laboratory, and then calculates and records the mechanical parameters in combination with the sample geometric parameters and loading method, thereby completing the comprehensive testing and evaluation of the mechanical properties of the filling.

[0004] Existing technologies rely on analyzing a single response at a fixed measurement point, lacking in-depth analysis of response variations between measurement points and making it difficult to fully demonstrate internal structural differences. In fillings with significant structural heterogeneity, conventional methods struggle to identify localized abnormal areas, which can easily lead to assessment bias. The unloading phase fails to fully utilize the strain recovery process, focusing solely on the loading response and lacking effective assessment of later deformation capacity. In practical applications, potential degradation areas are easily missed, potentially leading to localized stability risks and compromising operational safety and structural reliability. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for detecting the mechanical properties of mine filling bodies.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a method for detecting the mechanical properties of a mine filling body, comprising the following steps:

[0007] S1: Acquire data measured by multiple sets of displacement sensors and strain gauges within the filling body, detect the sensor output value of each measuring point under initial loading, select measuring points with complete response signals, determine their loading response trends, and generate a set of loading response change curves;

[0008] S2: Based on the loading response change curve group, calling the displacement change values ​​and strain values ​​of adjacent measuring points, calculating the average response deviation rate and locating the spatial area where the deviation exceeds the threshold, and generating a spatial distribution map of the heterogeneous area;

[0009] S3: extracting the displacement slope, loading rate, and strain rate of the target measuring point based on the spatial distribution map of the heterogeneous region, multiplying the loading rate by the displacement slope to obtain the loading stress value, and then dividing the result by the strain rate to obtain the local compressive factor, summarizing the relationship between the local compressive factor and the measuring point position, and generating a local compressive strength distribution map;

[0010] S4: calling the low-strength measurement point in the local compressive strength distribution map, obtaining the unloading strain recovery amplitude and the initial slope, calculating the recovery ratio and multiplying it by the slope to obtain the deformation recovery index, and generating the unloading deformation elastic performance set.

[0011] As a further solution of the present invention, the loading response change curve group includes response trend type, change amplitude distribution, and curve continuity characteristics; the spatial distribution map of the heterogeneous region includes regional boundary morphology, deviation concentration area, and abnormal gradient distribution; the local compressive strength distribution map is specifically a graded distribution of compressive stress values, strain response level, and spatial coordinate mapping; the unloading deformation elastic performance set includes recovery rate distribution, initial response characteristics, and elasticity level labels.

[0012] As a further solution of the present invention, the step of obtaining the loading response change curve group is specifically as follows:

[0013] S101: Based on the displacement sensor output value and the strain gauge data, the initial loading response of the measuring point is detected, the data without abnormal fluctuation is screened and the response increment is calculated to obtain a complete set of response measuring point numbers;

[0014] S102: calling the complete response measuring point number set, extracting the displacement and strain increment sequences of the corresponding measuring points, and determining the continuous growth direction and growth rate to obtain a continuous growth response measuring point list;

[0015] S103: Based on the continuous growth response measurement point list, jointly process the growth rate, amplitude and slope changes of the displacement response and the strain response, using the formula:

[0016] ;

[0017] Obtain the load response change intensity value of each measuring point by calculation, analyze its time series curve distribution and obtain the load response change curve group;

[0018] in, Representative The loading response change intensity value corresponding to each measuring point is: Representative The measuring point is The displacement response increment at each time point, Representative The measuring point is The strain response value at each time point, Representative The measuring point is Unit growth rate of the loading phase at each time point, is the loading amplitude growth offset rate adjustment factor, For the The measuring point is The cumulative response slope at each time point, is the total number of time nodes in the loading phase.

[0019] As a further solution of the present invention, the steps of obtaining the spatial distribution map of the heterogeneous region are specifically as follows:

[0020] S201: Based on the loading response change curve group, calling the displacement change values ​​and strain values ​​of adjacent measuring points, calculating the response deviation rate of each pair of measuring points, and generating a response deviation rate sequence group;

[0021] S202: Divide the regional grid according to the response deviation rate sequence group, call the response deviation rates of the measurement points in multiple units at the same time, calculate the mean and introduce the offset stabilization term, using the formula:

[0022] ;

[0023] The average response deviation rate value of each unit is obtained by calculation, and after comparison with the spatial response deviation threshold, abnormal areas are screened to generate a set of high deviation response areas;

[0024] in, represent The average response deviation rate value of the grid cells, is the number of measurement point pairs within the unit, For the The displacement deviation value of the measuring point, For the Strain deviation value of the measuring point;

[0025] S203: Extracting spatial coordinate information based on the high deviation response area set, combining the measurement points with the grid distribution, constructing a three-dimensional boundary graph, and generating a spatial distribution map of the heterogeneous area.

[0026] As a further solution of the present invention, the steps for obtaining the local compressive strength distribution map are specifically as follows:

[0027] S301: Based on the spatial distribution map of the heterogeneous region, extract the displacement data of the measuring points, the load variation and the strain measurement sequence, calculate the displacement slope, the loading rate and the strain rate, and obtain a slope rate measurement value group;

[0028] S302: Call the slope rate measurement group, calculate the product of the loading rate and the displacement slope, obtain the time derivative of the slope and the strain rate, and construct a response relationship based on the slope change and the strain fluctuation using the formula:

[0029] ;

[0030] Calculate and obtain the local compressive strength factor value at the measuring point, and summarize the parameters by measuring point to obtain the compressive strength calculation set of the measuring point;

[0031] in, Representative The local compressive strength factor at the measuring point, Representative The loading rate at each measuring point, For the The displacement slope of each measuring point, For the The strain rate at each measuring point, is the time derivative of the slope, is the time derivative of strain rate;

[0032] S303: extracting the measuring point location information according to the measuring point compressive strength calculation set, integrating the compressive strength factor value and the spatial coordinate, constructing a distribution relationship map, and obtaining a local compressive strength distribution map.

[0033] As a further solution of the present invention, the step of obtaining the unloading deformation elastic performance set is specifically:

[0034] S401: calling the low-strength measurement point in the local compressive strength distribution map, detecting the stress and strain values ​​at the initial unloading point, calculating the unloading slope, and comparing the strain amplitudes before and after unloading to obtain a deformation recovery ratio value;

[0035] S402: Based on the deformation recovery ratio value and the unloading initial slope value, the stress difference and unloading strain increment of multiple measuring points are called, and after integrating the data of multiple measuring points, a composite operation of product, addition, square root and absolute value is performed, using the formula:

[0036] ;

[0037] The multi-parameter coupled deformation recovery strength value is obtained by calculation and combined with the unloading stage characteristics to generate the deformation recovery index value;

[0038] in, represents the deformation recovery index value, is the deformation recovery ratio value, is the initial slope value of unloading, Indicates the Strain increment at the measuring point, is the stress difference, is the mean stress difference, is the total number of measurement points involved in the unloading analysis;

[0039] S403: performing a sorting and aggregation operation according to the deformation recovery index value, screening representative measuring points and constructing a multi-measurement point recovery performance distribution set to obtain an unloading deformation elastic performance set.

[0040] As a further embodiment of the present invention, the method further comprises:

[0041] S5: Based on the unloading deformation elastic performance set, screening low elastic capacity measurement points, and comparing them with the corresponding compressive capacity in the local compressive strength distribution map, counting the simultaneous degradation measurement points and calculating the distribution density, and generating a local performance degradation warning area map;

[0042] The local performance degradation warning area map specifically refers to the spatial density of degradation measurement points, performance degradation levels, and potential instability areas.

[0043] As a further solution of the present invention, the steps of obtaining the local performance degradation warning area map are specifically as follows:

[0044] S501: extracting residual elastic displacement values ​​and peak elastic recovery rates based on the elastic response data of the unloading deformation elastic performance set, performing difference judgment according to an elastic capacity threshold, screening measurement points with insufficient elastic capacity, and obtaining a low-elasticity measurement point set;

[0045] S502: Calling the measurement point number of the low-elasticity measurement point concentration, corresponding to the compressive capacity value in the local compressive strength distribution map, calculating the elasticity-compression ratio and screening the measurement points with a ratio less than 1 to generate a simultaneous degradation measurement point sequence;

[0046] S503: According to the coordinate information and spatial distribution of the simultaneously degraded measuring point sequence, the number of measuring points in the unit area is counted and grouped using the formula:

[0047] ;

[0048] Obtain degradation density values ​​through calculations, map regional grids, and establish a local performance degradation warning area map;

[0049] in, represents the degradation density value of region r, For the Elastic residual value of each measuring point, For the The pressure resistance of each measuring point, For the The shortest spatial distance between a measuring point and its adjacent measuring points, For the region The number of measurement points within is the total number of measurement points in region r.

[0050] A mine filling body mechanical property detection system, which is used to perform the above-mentioned mine filling body mechanical property detection method, and the system includes:

[0051] The response identification module obtains multiple sets of displacement sensor output values ​​and strain gauge output values, selects response measurement points with consistent loading trends, calls time series response data, compares the change direction and extracts continuous response change values, and generates a set of loading response change curves;

[0052] a deviation positioning module, which, based on the loading response change curve group, calls the displacement change values ​​and strain change values ​​of adjacent measuring points, calculates the average response deviation rate, determines whether it exceeds the response deviation threshold, locates the spatial coordinates of the abnormal measuring points, and generates a spatial distribution map of the heterogeneous area;

[0053] A strength extraction module obtains a displacement slope sequence, a loading rate value, and a strain rate value of a target measuring point based on the spatial distribution map of the heterogeneous region, multiplies the displacement slope sequence by the loading rate value to obtain a loading compressive stress value sequence, and then divides the result by the strain rate value to obtain a local compressive factor value. The coordinates of the measuring points and the local compressive factor values ​​are summarized to generate a local compressive strength distribution map;

[0054] The elastic identification module calls the low-strength measurement point in the local compressive strength distribution map, collects the strain recovery amplitude value and the unloading starting slope value thereof, calculates the recovery ratio and multiplies it by the unloading starting slope value to obtain the deformation recovery index value, and generates the unloading deformation elastic performance set;

[0055] The degradation warning module selects measurement points with low deformation recovery index values ​​based on the unloading deformation elasticity performance set, compares the values ​​with the local compressive strength factor values, selects simultaneous degradation measurement points, calculates spatial density values, and generates a local performance degradation warning area map.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] In the present invention, the stability and representativeness of the measurement point signals are ensured and the quality of basic data is improved by screening and trend analysis of multiple groups of response data. The heterogeneous areas are located based on the response deviation between the measuring points to achieve accurate identification of spatial differences. The displacement slope, loading rate and strain rate are extracted to calculate the local compressive factor, form a strength distribution map, and clarify the mechanical performance of each area. During the unloading stage, the strain recovery characteristics are collected to quantify the elastic performance, and the low elasticity areas are screened and combined with the compressive factor to identify the points of synchronous performance degradation and form an early warning map. Through the calculation of differences between data, spatial mapping and multi-parameter superposition, the quantitative, visual and trend identification of mechanical properties is achieved, and the ability to discriminate complex structural changes is enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0059] Figure 2 A flow chart showing the steps for obtaining a response change curve group loaded in the present invention;

[0060] Figure 3 Flowchart of the steps for obtaining the spatial distribution map of the heterogeneous region according to the present invention;

[0061] Figure 4 Flowchart of the steps for obtaining the local compressive strength distribution map of the present invention;

[0062] Figure 5 Flowchart of the steps for obtaining the unloading deformation elasticity performance set of the present invention;

[0063] Figure 6 This is a flow chart of the steps for obtaining the local performance degradation warning area map of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0065] See also Figure 1 The present invention provides a technical solution: a method for detecting the mechanical properties of a mine filling body, comprising the following steps:

[0066] S1: Acquire data measured by multiple sets of displacement sensors and strain gauges within the filling body, detect the sensor output value of each measuring point under initial loading, select measuring points with complete response signals, determine their loading response trends, and generate a set of loading response change curves;

[0067] S2: Based on the loading response change curve group, the displacement change values ​​and strain values ​​of adjacent measuring points are called, the average response deviation rate is calculated, and the spatial area where the deviation exceeds the threshold is located to generate a spatial distribution map of the heterogeneous area;

[0068] S3: Based on the spatial distribution map of the heterogeneous area, the displacement slope, loading rate, and strain rate of the target measuring point are extracted. The loading pressure stress value is obtained by multiplying the loading rate and the displacement slope, and then divided by the strain rate to obtain the local compressive factor. The relationship between the local compressive factor and the measuring point position is summarized to generate a local compressive strength distribution map;

[0069] S4: Call the low-strength measurement point in the local compressive strength distribution map, obtain the unloading strain recovery amplitude and the initial slope, calculate the recovery ratio and multiply it by the slope to obtain the deformation recovery index, and generate the unloading deformation elastic performance set;

[0070] S5: Based on the unloading deformation elastic performance set, screen the measurement points with low elastic capacity and compare them with the corresponding compressive capacity in the local compressive strength distribution map. Count the simultaneous degradation measurement points and calculate the distribution density to generate a local performance degradation warning area map.

[0071] The loading response change curve group includes the response trend type, change amplitude distribution, and curve continuity characteristics. The spatial distribution map of the heterogeneous area includes the regional boundary shape, deviation concentration area, and abnormal gradient distribution. The local compressive strength distribution map specifically includes the graded distribution of compressive stress values, strain response level, and spatial coordinate mapping. The unloading deformation elastic performance set includes the recovery rate distribution, initial response characteristics, and elasticity level label. The local performance degradation warning area map specifically refers to the spatial density of degradation measurement points, performance degradation level, and potential instability area.

[0072] See also Figure 2 , the specific steps for obtaining the loading response change curve group are:

[0073] S101: Based on the displacement sensor output value and the strain gauge data, the initial loading response of the measuring point is detected, the data without abnormal fluctuation is screened and the response increment is calculated to obtain a complete set of response measuring point numbers;

[0074] First, the original output data of each measuring point in the initial loading stage is called, and the initial displacement value and strain value of the corresponding measuring point are extracted one by one. The collected data are time-series aligned to establish the initial numerical matrix of displacement and strain to ensure that the displacement and strain data points correspond one to one. The specific processing action is to call the initial displacement data measured by the sensor (such as the initial displacement data example shown in Table 1) and the initial strain data measured by the strain gauge, and calculate the incremental change of the measured values ​​at adjacent moments by traversing point by point (that is, the displacement or strain value at the next moment is subtracted from the corresponding value at the previous moment), record the absolute value of the incremental change, and use the numerical fluctuation thresholds of 0.02mm and 0.005με as the judgment criteria. The measuring points with an absolute value of quantization less than 0.02 mm and an absolute value of strain change less than 0.005 με are defined as having no abnormal fluctuation. This is used to determine whether abnormal fluctuations occur at each measuring point and to screen out data sequences without abnormal fluctuations. For example, the displacements of measuring point P5 at two consecutive initial sampling points are 0.120 mm and 0.132 mm, and the strains are 1.250 με and 1.260 με, respectively. The calculated displacement increment is 0.012 mm and the strain increment is 0.010 με. Since both increments are below the threshold, it is determined that this measuring point has no abnormal fluctuation and is included in the complete response measuring point number set. Finally, the complete measuring point number set for the initial loading response is determined to be {P1, P2, P5, P7, P9, P10}.

[0075] Table 1: Example data of displacement and strain of measuring points in the initial loading stage

[0076]

[0077] As shown in Table 1, the above initial data are collected in real time by sensors and strain gauges and recorded in matrix form to screen out the measurement point data without abnormal fluctuations.

[0078] S102: calling the complete response measurement point number set, extracting the displacement and strain increment sequence of the corresponding measurement points, and determining the continuous growth direction and growth rate to obtain a continuous growth response measurement point list;

[0079] Call the determined complete response measurement point number set {P1, P2, P5, P7, P9, P10}, and extract the displacement response increment sequence and strain increment sequence generated by the corresponding measurement point as the loading stage continues. Specifically, the time series data sequence is established by sampling the displacement and strain data every 1 second, and the displacement and strain increments of each adjacent data point are calculated. Based on the continuous growth judgment of more than three consecutive sampling points, the specific parameters are called point by point for inspection. If the displacement increment and strain increment of three consecutive moments are all positive, the measurement point is judged to be a continuous growth response. For example, if the displacement increments of measuring point P1 at three consecutive moments are 0.010 mm, 0.012 mm, and 0.015 mm, and the strain increments are 0.007 με, 0.009 με, and 0.012 με, then the measuring point is included in the continuous growth response measuring point list because the increments are continuously positive. If any increment in the continuous growth becomes negative or zero, then the measuring point is determined to not meet the continuous growth condition and is therefore not included in the continuous growth response measuring point list. The final determined continuous growth response measuring point list is, for example, {P1, P5, P7, P9}.

[0080] S103: Based on the continuous growth response measurement point list, jointly process the growth rate, amplitude and slope changes of displacement response and strain response, using the formula:

[0081] ;

[0082] Obtain the load response change intensity value of each measuring point by calculation, analyze its time series curve distribution and obtain the load response change curve group;

[0083] in, Representative The loading response change intensity value corresponding to each measuring point is: Representative The measuring point is The displacement response increment at each time point, Representative The measuring point is The strain response value at each time point, Representative The measuring point is Unit growth rate of the loading phase at each time point, is the loading amplitude growth offset rate adjustment factor, For the The measuring point is The cumulative response slope at each time point, is the total number of time nodes in the loading phase.

[0084] Combine the displacement and strain responses of the measurement points {P1, P5, P7, P9} in the continuous growth response measurement point list to calculate the loading response change intensity value Taking measuring point P1 as an example, the specific execution process is as follows: First, extract the displacement response increment , strain response value , Unit load growth rate , cumulative response slope Specific measurement data are as follows: at a certain moment t1, the displacement response increment is 0.015mm, the strain response value is 1.320με, the unit load growth amplitude is 0.005mm / s, and the cumulative response slope is 0.002; the cumulative response slope at the previous moment (t1-1) is 0.0018, and the loading amplitude growth offset rate adjustment factor is Set it to 0.01 (based on historical monitoring data analysis, the reasonable range is 0.005~0.02); then substitute it into the formula:

[0085] ;

[0086] For measuring point P1, take n1=3 during the loading period and calculate the specific value:

[0087] Time t1:

[0088] ;

[0089] At time t2, the displacement increment is 0.017 mm, the strain response is 1.332 με, the unit load increase is 0.006 mm / s, and the cumulative slope is 0.0022. Calculate:

[0090] ;

[0091] At time t3: take the displacement increment as 0.019 mm, the strain response as 1.345 με, the unit load increase as 0.007 mm / s, and the cumulative slope as 0.0024, and calculate:

[0092] ;

[0093] Combining the above three-moment data, we can calculate the loading response change intensity of measuring point P1:

[0094] ;

[0095] The results show that the loading response change intensity of measuring point P1 is 1.349. Similarly, by calculating other measuring points one by one and analyzing their time series curve distribution, a group of loading response change curves can be obtained. The benefit of the formula is that it comprehensively reflects the fine response characteristics of the measuring point during the loading process through the joint processing of displacement increment, strain amplitude and slope change.

[0096] See also Figure 3 , the specific steps for obtaining the spatial distribution map of heterogeneous areas are:

[0097] S201: Based on the loading response change curve group, call the displacement change values ​​and strain values ​​of adjacent measuring points, calculate the response deviation rate of each pair of measuring points, and generate a response deviation rate sequence group;

[0098] First, the data of adjacent measuring points under the same loading conditions are selected for comparison, and the difference between the displacement change value and the strain change value of the adjacent measuring points is selected for preliminary analysis. For example, assuming there is a measuring point pair (measuring point A, measuring point B), the displacement change of measuring point A is 0.025mm, the strain change is 120με, the displacement change of measuring point B is 0.030mm, and the strain change is 125με. The data of measuring point B is subtracted from the data of measuring point A to obtain the displacement deviation value. for , strain deviation value for Repeat the above operation for all pairs of measuring points. After obtaining the displacement deviation value and strain deviation value of each pair of measuring points, calculate the response deviation rate of each pair of measuring points by dividing the displacement deviation value by the strain deviation value. For example, the response deviation rate of the measuring point pair is For actual application scenarios, such as in the monitoring of the beam span structure of a bridge, taking 20 measuring points as an example, the response deviation rates of 19 measuring point pairs are calculated according to the loading response curve, that is, a response deviation rate sequence group is formed, thereby providing a complete data basis for the next step of processing.

[0099] S202: Divide the regional grid according to the response deviation rate sequence group, call the response deviation rates of the measurement points in multiple units at the same time, calculate the mean and introduce the offset stabilization term, using the formula:

[0100] ;

[0101] The average response deviation rate value of each unit is obtained by calculation, and after comparison with the spatial response deviation threshold, abnormal areas are screened to generate a set of high deviation response areas;

[0102] in, represent The average response deviation rate value of the grid cells, is the number of measurement point pairs within the unit, For the The displacement deviation value of the measuring point, For the Strain deviation value of the measuring point;

[0103] By dividing the grid based on the spatial size of the monitoring area, for example, a monitoring area with a bridge beam length of 20m and a width of 5m is divided into multiple unit grids. The size of each unit can be set to 2m×1m, and there are 50 grid units in total. Each grid unit contains a different number of measuring point pairs. The response deviation rate of the measuring point pairs in each unit is called and summarized for calculation. First, the average response deviation rate of all measuring point pairs in the unit is calculated. Then, the offset stability term is introduced according to the actual calculation needs, and the calculation is performed using the formula:

[0104] In the formula Indicates the The average response deviation rate value of the grid cells, is the number of pairs of measuring points in the unit. For example, there are 4 pairs of measuring points in the (2,3) unit. The specific data are shown in Table 2:

[0105] Table 2: Response deviation rate data of measurement points within the unit

[0106]

[0107] As shown in Table 2, call the data of each measuring point and put it into the formula to calculate:

[0108] ;

[0109] ;

[0110] ;

[0111] ;

[0112] Then average the above four values ​​and take the absolute value:

[0113] ;

[0114] Repeat the above calculation process for all grid cells to obtain the average response deviation rate value of each cell. Compare with the spatial response deviation threshold, which can be set based on past experience or historical monitoring data. For example, if the threshold is set to 2.0, the judgment and screening will be performed. If the value exceeds the threshold of 2.0, the grid cell is identified as an abnormal response area. For example, in this example, 2.141>2.0 for the (2,3) grid is an abnormal area and is added to the high deviation response area set. All cells above this threshold are included in the high deviation response area set.

[0115] S203: Extracting spatial coordinate information based on the high deviation response area set, combining the measurement points with the grid distribution, constructing a three-dimensional boundary graph, and generating a spatial distribution map of the heterogeneous area.

[0116] Each grid cell is located by its four corner coordinates. For example, the coordinate position of the (2,3) grid cell is determined by the coordinates of the four vertices of the cell. The coordinate information of all high-deviation grid cells (such as (4m, 3m, 0m), (6m, 3m, 0m), (4m, 4m, 0m), and (6m, 4m, 0m)) is determined, and the coordinate data of all high-deviation grid cells are called and summarized into a high-deviation area spatial coordinate dataset. Then, combined with the specific layout of the measuring points, for example, measuring points S4 and S5 are installed in the grid with coordinates of (4.5m, 3.5m, 0m) and (5.5m, 3.5m, 0m) respectively, a three-dimensional boundary graph is constructed with each grid cell and the actual layout coordinates of the measuring points. The spatial coordinates of all adjacent cells in the three-dimensional boundary graph are connected, and a complete spatial distribution map of the heterogeneous area is gradually constructed, thus fully presenting the high-deviation response area.

[0117] See also Figure 4 , the specific steps for obtaining the local compressive strength distribution map are:

[0118] S301: Based on the spatial distribution map of the heterogeneous region, extract the displacement data of the measuring points, the load variation and the strain measurement sequence, calculate the displacement slope, the loading rate and the strain rate, and obtain a slope rate measurement value group;

[0119] During the implementation process, we first extract the displacement data, load variation, and strain measurement sequence from the spatial distribution map of the heterogeneous region. Then we need to calculate the relevant parameters of these data: displacement slope, loading rate, and strain rate. The key to these data extraction and calculation processes is to ensure the accuracy and continuity of the measurement. Assume that we collect the displacement data sequence at a certain measuring point (i1) as , then the displacement slope The formula is obtained by differential operation of displacement data:

[0120] ;

[0121] in, and represent the initial and final displacement values ​​of the measurement data sequence, respectively, and is the corresponding time point. In the calculation of the loading rate, it is necessary to calculate according to the load change at each time step. If the load data is , the loading rate The calculation method is:

[0122] ;

[0123] Similarly, the strain rate It is obtained by differential calculation of strain data. Assume that the strain data is , the strain rate calculation formula is:

[0124] ;

[0125] For example, suppose we are at the moment of measuring point i_1 and The displacement data is obtained as , the strain data is , the load data is . Then the displacement slope is:

[0126] ;

[0127] The loading rate is:

[0128] ;

[0129] The strain rate is:

[0130] ;

[0131] These calculation results are the basic data required for this step. Next, these data will be used for further analysis and calculation to obtain the slope rate measurement set.

[0132] S302: Call the slope rate measurement group, calculate the product of the loading rate and the displacement slope, obtain the time derivative of the slope and strain rate, and construct a response relationship based on the slope change and strain fluctuation using the formula:

[0133] ;

[0134] Calculate and obtain the local compressive strength factor value at the measuring point, and summarize the parameters by measuring point to obtain the compressive strength calculation set of the measuring point;

[0135] in, Representative The local compressive strength factor at the measuring point, Representative The loading rate at each measuring point, For the The displacement slope of each measuring point, For the The strain rate at each measuring point, is the time derivative of the slope, is the time derivative of strain rate;

[0136] The specific calculation process is: first calculate the product of loading rate and displacement slope, that is , and then calculate the time derivative of the slope and strain rate: , the time derivative is calculated by calculating the rate of change of the slope and strain rate. Assume that the data at the moment of measuring point i_2 is mm / s, mm / s, the time interval is , then the slope time derivative is calculated as:

[0137] ;

[0138] Similarly, for the calculation of the time derivative of strain rate, assuming the strain rate is and , then the time derivative of strain rate is:

[0139] ;

[0140] Substitute these values ​​into the formula to calculate the local compressive strength factor:

[0141] ;

[0142] Assume the loading rate is , the displacement slope is , the strain rate is ,but:

[0143] ;

[0144] The calculated result is the local compressive strength factor, which represents the local compressive strength at the measuring point. This value will be used as a data point in the compression calculation set and further used in the subsequent compression distribution map construction.

[0145] S303: According to the compressive strength calculation set of the measuring points, the measuring point location information is extracted, the compressive strength factor value and the spatial coordinate are integrated, a distribution relationship map is constructed, and a local compressive strength distribution map is obtained.

[0146] At this stage, by integrating the various data points from the compressive calculation set, we can obtain the measurement point location information and the corresponding local compressive factor values. This data is used to construct a distribution relationship map, thereby obtaining a local compressive strength distribution map. The compressive factor value of each measurement point is then associated with its spatial coordinates, and the trend of compressive strength over spatial distribution is plotted, ultimately forming a spatial distribution map of local compressive strength.

[0147] Table 3: Calculation data of compression factor at measuring points

[0148]

[0149]

[0150] As shown in Table 3, the compressive strength factors of the measuring points vary with their locations. These data can help construct a more accurate local compressive strength distribution map.

[0151] See also Figure 5 , the steps for obtaining the unloading deformation elasticity performance set are as follows:

[0152] S401: calling the low-strength measurement point in the local compressive strength distribution map, detecting the stress and strain values ​​at the initial unloading point, calculating the unloading slope, and comparing the strain amplitudes before and after unloading to obtain the deformation recovery ratio value;

[0153] Specifically, the measuring points whose strength values ​​are below 20% of the total strength distribution of the measuring points in the concrete compression test are selected. Assuming that a total of 3 measuring points are selected, the stress values ​​of the measuring points are 、 、 ; Then, unloading tests are carried out one by one at these three measuring points, and stress reduction is achieved by step-by-step loading. Assuming that the stress drops to 80% of the total loading stress at the initial unloading point (i.e., the rebound point), unloading begins. The corresponding stress value is set to 0.8 times the original stress of each measuring point. For example, the stress value of the initial unloading point of the first measuring point is: , and so on, the initial unloading stress values ​​of the three measuring points are obtained as follows: 16MPa, 17.6MPa, and 15.2MPa; at the same time, the strain gauges installed on the surface of the specimen are used to record the corresponding initial strain values. It is assumed that the initial unloading strain values ​​recorded by the strain gauges at each measuring point are 、 、 Then continue to reduce the load step by step until it is completely unloaded. The strain gauge records the strain at the end of unloading as follows: 、 、 By calculating the stress and strain differences during the unloading process at the three measuring points, the unloading slope is obtained. , for example, the unloading slope of the first measuring point is calculated as: , and the other measuring points are calculated in the same way; then the strain amplitude difference before and after unloading is calculated for each measuring point, for example, the strain difference before and after unloading of measuring point 1 is , perform the same operation on other measuring points to obtain the deformation recovery ratio value as the ratio of the strain difference after unloading to the initial strain of unloading. For example, the deformation recovery ratio value of the first measuring point is: , the deformation recovery ratio calculation of each measuring point is completed one by one, and finally the deformation recovery ratio value of each measuring point is obtained. S402: Based on the deformation recovery ratio value and the unloading initial slope value, the stress difference and unloading strain increment of multiple measuring points are called, and after integrating the data of multiple measuring points, a composite operation of product, addition, square root and absolute value is performed, using the formula:

[0154] ;

[0155] The multi-parameter coupled deformation recovery strength value is obtained by calculation and combined with the unloading stage characteristics to generate the deformation recovery index value;

[0156] in, represents the deformation recovery index value, is the deformation recovery ratio value, is the initial slope value of unloading, Indicates the Strain increment at the measuring point, is the stress difference, is the mean stress difference, is the total number of measurement points involved in the unloading analysis;

[0157] Based on the deformation recovery ratio and unloading initial slope obtained in the previous section, multiple measuring points are selected to calculate the stress difference and unloading strain increment; specifically, the stress difference The difference between the initial stress of the measuring point and the stress of the initial unloading point. For example, the stress difference of measuring point 1 is ; Unloading strain increment It is the difference between the initial strain at unloading and the final strain after complete unloading. For example, the unloading strain increment at measuring point 1 is 150με. Assume that there are three measuring points involved in the analysis, as listed below:

[0158] Table 4: Stress and strain parameters of measuring points

[0159]

[0160] Table 4 shows the test data of the embodiment. The data is then substituted into the deformation recovery index formula, where is the average stress difference of the three measuring points, that is: (4+4.4+3.8) / 3=4.067MPa; calculate the product term of each measuring point one by one and take the square root, for example, measuring point 1: Calculate the other measuring points similarly; add the square root results of all measuring points: 24.495+26.533+23.874=74.902; add the mean deformation recovery ratio of the measuring points (assuming the average of the three measuring points is 0.236), and the numerator is 75.138; then use the mean initial slope of unloading (take 0.1060MPa / με) minus the mean stress difference 4.067 to get the denominator: 0.1060-4.067=-3.961; the deformation recovery index value is Calculated as: The results show that the deformation recovery index obtained by integrating the stress difference and strain increment of multiple measuring points can quantify the degree of deformation elasticity of the measuring points.

[0161] S403: performing a sorting and aggregation operation based on the deformation recovery index value, screening representative measuring points and constructing a multi-measurement point recovery performance distribution set to obtain an unloading deformation elastic performance set.

[0162] Based on the deformation recovery index value obtained above , the deformation recovery index values ​​calculated from multiple measuring points are sorted from large to small, and the top 30% representative measuring points are screened out by sorting aggregation. Assume that measuring point 2 and measuring point 1 are selected as representative measuring points after sorting, and their corresponding deformation recovery index values ​​are 2.120 and 2.010, respectively; then a multi-measuring point recovery performance distribution set is constructed, and the selected measuring points are formed into a recovery performance set, for example, it is expressed in set form as {measuring point 2, measuring point 1}, and the strain recovery characteristics corresponding to the measuring points in the set (such as the initial unloading strain, the end-of-unloading strain, the strain increment and the corresponding deformation recovery ratio, etc.) are concentrated into a multi-measuring point elastic performance distribution set to obtain the final unloading deformation elastic performance set.

[0163] See also Figure 6 ,The steps for obtaining the local performance degradation warning area map are as follows:

[0164] S501: Based on the elastic response data of the unloading deformation elastic performance set, the residual elastic displacement value and the peak elastic recovery rate are extracted, and the difference judgment is performed according to the elastic capacity threshold to screen the measuring points with insufficient elastic capacity to obtain the low elasticity measuring point set;

[0165] The unloading deformation elasticity performance set uses the load elasticity test of a bridge structure as an example. It contains the elastic response data of each measuring point during the unloading phase of the static load test, such as the residual elastic displacement and peak elastic recovery rate at key measuring points on the bridge deck. Taking the data from five measuring points in a specific area of ​​the bridge deck as an example, Table 5 shows the actual elastic response data:

[0166] Table 5: Elastic response data of measuring points

[0167]

[0168] In actual implementation, the elastic residual displacement values ​​recorded at each measuring point are first retrieved. For example, the residual displacement value of measuring point M1 is 0.25mm. Then, the elastic capacity threshold of 0.30mm is used to perform a difference check. Using 0.30mm as the criterion, the residual displacement values ​​of each measuring point are numerically compared with this threshold. Using 0.30mm as the cutoff, if the residual displacement value is greater than or equal to 0.30mm, the measuring point is considered to have insufficient elastic capacity; otherwise, it is considered to have passed, completing the screening process. For example, if the residual displacement value of M2 is 0.35mm, compared to the threshold of 0.30mm, the value is larger, indicating insufficient elastic capacity. Similarly, the residual displacement value of M4, 0.45mm, is also greater than 0.30mm, indicating insufficient elastic capacity. However, the residual displacement values ​​of M1, M3, and M5 are all below 0.30mm, indicating passing. This results in a set of measuring points with insufficient elastic capacity, namely, the low-elasticity measuring point set {M2, M4}.

[0169] S502: Call the concentrated measurement point number of the low-elasticity measurement point, correspond to the compressive capacity value in the local compressive strength distribution map, calculate the elasticity-compression ratio, and select the measurement points with a ratio less than 1 to generate a simultaneous degradation measurement point sequence;

[0170] Based on the low-elasticity measuring point set {M2, M4} obtained in the previous stage, the local compressive strength distribution map corresponding to each measuring point number is retrieved to obtain the corresponding compressive capacity values. Assuming the actual data for the compressive capacity measuring points is as follows: the compressive capacity value of measuring point M2 is 0.40 MPa, and the compressive capacity value of measuring point M4 is 0.55 MPa. The elastic residual displacement values ​​of these measuring points, 0.35 mm for M2 and 0.45 mm for M4, are used to calculate the elasticity-to-compressive capacity ratio. For measuring point M2, the elastic residual displacement value of 0.35 divided by the compressive capacity value of 0.40 yields a ratio of 0.875, which is less than 1. The elastic residual displacement value of measuring point M4, 0.45 divided by the compressive capacity value of 0.55 yields a ratio of 0.818, which is also less than 1. Therefore, after the ratio comparison operation, the degenerate measuring point sequence with a ratio less than 1 is {M2, M4}.

[0171] S503: Based on the coordinate information and spatial distribution of the simultaneously degraded measuring point sequence, the number of measuring points in the unit area is counted and grouped using the formula:

[0172] ;

[0173] Obtain degradation density values ​​through calculations, map regional grids, and establish a local performance degradation warning area map;

[0174] in, represents the degradation density value of region r, For the Elastic residual value of each measuring point, For the The pressure resistance of each measuring point, For the The shortest spatial distance between a measuring point and its adjacent measuring points, For the region The number of measurement points within is the total number of measurement points in region r.

[0175] In the coordinate space of the bridge deck area, based on the spatial coordinate positions involved in the simultaneous degenerate measuring point sequence {M2, M4}, the number of measuring points in the unit area is counted and grouped. For example, the total number of measuring points in this area is , the number of simultaneous degradation measurement points The shortest spatial distance is calculated by collecting the actual coordinate positions of the measuring points. For example, if the distance between measuring point M2 and the nearest measuring point M3 is 2.5m, and the distance between measuring point M4 and the nearest measuring point M5 is 3.0m, then the corresponding 2.5m and 3.0m respectively.

[0176] Give specific instructions for the formula parameters: The degenerate density value of , elastic residual displacement value Take 0.35mm of measuring point M2 and 0.45mm of measuring point M4 respectively, and the compressive strength value Take 0.40MPa at measuring point M2 and 0.55MPa at measuring point M4 respectively, the shortest space distance The values ​​are 2.5m and 3.0m respectively. The above data are obtained by on-site measurement to clarify the data value acquisition process.

[0177] Substitute the formula for calculation and derivation:

[0178]

[0179] After calculation, we finally get the area The degradation density value is 0.0557. By setting 0.05 as the degradation warning reference value for numerical comparison, it is determined that the calculated 0.0557 has exceeded the degradation warning reference value. The numerical judgment area The performance within the area is in a state of local degradation, and this result is mapped to the regional grid to draw a local performance degradation warning area map.

[0180] A mine filling body mechanical property detection system is used to perform the above-mentioned mine filling body mechanical property detection method. The system includes:

[0181] The response identification module obtains multiple sets of displacement sensor output values ​​and strain gauge output values, selects response measurement points with consistent loading trends, calls time series response data, compares the change direction and extracts continuous response change values, and generates a set of loading response change curves;

[0182] The deviation positioning module, based on the load response change curve group, calls the displacement change values ​​and strain change values ​​of adjacent measuring points, calculates the average response deviation rate and determines whether it exceeds the response deviation threshold, locates the spatial coordinates of abnormal measuring points, and generates a spatial distribution map of the heterogeneous area;

[0183] The strength extraction module obtains the displacement slope sequence, loading rate value, and strain rate value of the target measuring point based on the spatial distribution map of the heterogeneous area. The displacement slope sequence is multiplied by the loading rate value to obtain the loading pressure stress value sequence, which is then divided by the strain rate value to obtain the local compressive factor value. The measuring point coordinates and local compressive factor values ​​are summarized to generate a local compressive strength distribution map.

[0184] The elastic identification module calls the low-strength measurement point in the local compressive strength distribution map, collects its strain recovery amplitude value and unloading initial slope value, calculates the recovery ratio and multiplies it by the unloading initial slope value to obtain the deformation recovery index value, and generates the unloading deformation elastic performance set;

[0185] The degradation warning module, based on the unloading deformation elastic performance set, screens the measurement points with low deformation recovery index values, compares them with the local compressive factor values, screens the degradation measurement points at the same time and calculates the spatial density values ​​to generate a local performance degradation warning area map.

[0186] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for detecting mechanical properties of mine fillings, characterized in that: The following steps are involved: S1: Acquire data measured by multiple sets of displacement sensors and strain gauges within the filling body, detect sensor output values ​​at multiple measuring points under initial loading, select measuring points with complete response signals, determine loading response trends, and generate a set of loading response change curves; S2: Based on the loading response change curve group, calling the displacement change values ​​and strain values ​​of adjacent measuring points, calculating the average response deviation rate and locating the spatial area where the deviation exceeds the threshold, and generating a spatial distribution map of the heterogeneous area; S3: extracting the displacement slope, loading rate, and strain rate of the target measuring point based on the spatial distribution map of the heterogeneous region, multiplying the loading rate by the displacement slope to obtain the loading stress value, and then dividing the result by the strain rate to obtain the local compressive factor, summarizing the relationship between the local compressive factor and the measuring point position, and generating a local compressive strength distribution map; S4: calling the low-strength measurement point in the local compressive strength distribution map, obtaining the unloading strain recovery amplitude and the initial slope, calculating the recovery ratio and multiplying it by the slope to obtain the deformation recovery index, and generating the unloading deformation elastic performance set.

2. The method for detecting mechanical properties of mine filling according to claim 1, characterized in that: The loading response change curve group includes the response trend type, change amplitude distribution, and curve continuity characteristics. The spatial distribution map of the heterogeneous region includes the regional boundary morphology, deviation concentration area, and abnormal gradient distribution. The local compressive strength distribution map specifically includes the compressive stress value grade distribution, strain response level, and spatial coordinate mapping. The unloading deformation elastic performance set includes the recovery rate distribution, initial response characteristics, and elasticity level label.

3. The method for detecting mechanical properties of mine filling according to claim 2, characterized in that: The steps for obtaining the loading response change curve group are specifically as follows: S101: Based on the displacement sensor output value and the strain gauge data, the initial loading response of the measuring point is detected, the data without abnormal fluctuation is screened and the response increment is calculated to obtain a complete set of response measuring point numbers; S102: calling the complete response measuring point number set, extracting the displacement and strain increment sequences of the corresponding measuring points, and determining the continuous growth direction and growth rate to obtain a continuous growth response measuring point list; S103: Based on the continuous growth response measurement point list, jointly process the growth rate, amplitude and slope changes of the displacement response and the strain response, using the formula: ； Obtain the load response change intensity value of each measuring point by calculation, analyze its time series curve distribution and obtain the load response change curve group; in, Representative The loading response change intensity value corresponding to each measuring point is: Representative The measuring point is The displacement response increment at each time point, Representative The measuring point is The strain response value at each time point, Representative The measuring point is Unit growth rate of the loading phase at each time point, is the loading amplitude growth offset rate adjustment factor, For the The measuring point is The cumulative response slope at each time point, is the total number of time nodes in the loading phase.

4. The method for detecting mechanical properties of mine filling according to claim 3, characterized in that: The steps for obtaining the spatial distribution map of the heterogeneous region are specifically as follows: S201: Based on the loading response change curve group, calling the displacement change values ​​and strain values ​​of adjacent measuring points, calculating the response deviation rate of each pair of measuring points, and generating a response deviation rate sequence group; S202: Divide the regional grid according to the response deviation rate sequence group, call the response deviation rates of the measurement points in multiple units at the same time, calculate the mean and introduce the offset stabilization term, using the formula: ； The average response deviation rate value of each unit is obtained by calculation, and after comparison with the spatial response deviation threshold, abnormal areas are screened to generate a set of high deviation response areas; in, represent The average response deviation rate value of the grid cells, is the number of measurement point pairs within the unit, For the The displacement deviation value of the measuring point, For the Strain deviation value of the measuring point; S203: Extracting spatial coordinate information based on the high deviation response area set, combining the measurement points with the grid distribution, constructing a three-dimensional boundary graph, and generating a spatial distribution map of the heterogeneous area.

5. The method for detecting mechanical properties of mine filling according to claim 4, characterized in that: The steps for obtaining the local compressive strength distribution map are specifically as follows: S301: Based on the spatial distribution map of the heterogeneous region, extract the displacement data of the measuring points, the load variation and the strain measurement sequence, calculate the displacement slope, the loading rate and the strain rate, and obtain a slope rate measurement value group; S302: Call the slope rate measurement group, calculate the product of the loading rate and the displacement slope, obtain the time derivative of the slope and the strain rate, and construct a response relationship based on the slope change and the strain fluctuation using the formula: ； Calculate and obtain the local compressive strength factor value at the measuring point, and summarize the parameters by measuring point to obtain the measuring point compressive strength calculation set; in, Representative The local compressive strength factor at the measuring point, Representative The loading rate at each measuring point, For the The displacement slope of each measuring point, For the The strain rate at each measuring point, is the time derivative of the slope, is the time derivative of strain rate; S303: extracting the measuring point location information according to the measuring point compressive strength calculation set, integrating the compressive strength factor value and the spatial coordinate, constructing a distribution relationship map, and obtaining a local compressive strength distribution map.

6. The method for detecting mechanical properties of mine filling according to claim 5, characterized in that: The steps for obtaining the unloading deformation elasticity performance set are specifically as follows: S401: calling the low-strength measurement point in the local compressive strength distribution map, detecting the stress and strain values ​​at the initial unloading point, calculating the unloading slope, and comparing the strain amplitudes before and after unloading to obtain a deformation recovery ratio value; S402: Based on the deformation recovery ratio value and the unloading initial slope value, the stress difference and unloading strain increment of multiple measuring points are called, and after integrating the data of multiple measuring points, a composite operation of product, addition, square root and absolute value is performed, using the formula: ； The multi-parameter coupled deformation recovery strength value is obtained by calculation and combined with the unloading stage characteristics to generate the deformation recovery index value; in, represents the deformation recovery index value, is the deformation recovery ratio value, is the initial slope value of unloading, Indicates the Strain increment at the measuring point, is the stress difference, is the mean stress difference, is the total number of measurement points involved in the unloading analysis; S403: performing a sorting and aggregation operation according to the deformation recovery index value, screening representative measuring points and constructing a multi-measurement point recovery performance distribution set to obtain an unloading deformation elastic performance set.

7. The method for detecting mechanical properties of mine filling according to claim 6, characterized in that: The method further comprises: S5: Based on the unloading deformation elastic performance set, screening measurement points with low elastic capacity, and comparing them with the corresponding compressive capacity in the local compressive strength distribution map, counting the simultaneous degradation measurement points and calculating the distribution density, and generating a local performance degradation warning area map; The local performance degradation warning area map specifically refers to the spatial density of degradation measurement points, performance degradation levels, and potential instability areas.

8. The method for detecting mechanical properties of mine filling according to claim 7, characterized in that: The steps for obtaining the local performance degradation warning area map are specifically as follows: S501: extracting residual elastic displacement values ​​and peak elastic recovery rates based on the elastic response data of the unloading deformation elastic performance set, performing difference judgment according to an elastic capacity threshold, screening measurement points with insufficient elastic capacity, and obtaining a low-elasticity measurement point set; S502: Calling the measurement point number of the low-elasticity measurement point concentration, corresponding to the compressive capacity value in the local compressive strength distribution map, calculating the elasticity-to-compressive ratio and screening the measurement points with a ratio less than 1 to generate a simultaneous degradation measurement point sequence; S503: According to the coordinate information and spatial distribution of the simultaneously degraded measuring point sequence, the number of measuring points in the unit area is counted and grouped using the formula: ； Obtain degradation density values ​​through calculations, map regional grids, and establish a local performance degradation warning area map; in, represents the degradation density value of region r, For the Elastic residual value of each measuring point, For the The pressure resistance of each measuring point, For the The shortest spatial distance between a measuring point and its adjacent measuring points, For the region The number of measurement points within is the total number of measurement points in region r.

9. A mine filling body mechanical property detection system, based on the mine filling body mechanical property detection method according to any one of claims 1 to 8, characterized in that: The system comprises: The response identification module obtains multiple sets of displacement sensor output values ​​and strain gauge output values, selects response measurement points with consistent loading trends, calls time series response data, compares the change direction and extracts continuous response change values, and generates a group of loading response change curves; a deviation positioning module, which, based on the loading response change curve group, calls the displacement change values ​​and strain change values ​​of adjacent measuring points, calculates the average response deviation rate, determines whether it exceeds the response deviation threshold, locates the spatial coordinates of the abnormal measuring points, and generates a spatial distribution map of the heterogeneous area; A strength extraction module obtains a displacement slope sequence, a loading rate value, and a strain rate value of a target measuring point based on the spatial distribution map of the heterogeneous region, multiplies the displacement slope sequence by the loading rate value to obtain a loading compressive stress value sequence, and then divides the result by the strain rate value to obtain a local compressive factor value. The coordinates of the measuring points and the local compressive factor values ​​are summarized to generate a local compressive strength distribution map; The elastic identification module calls the low-strength measurement point in the local compressive strength distribution map, collects the strain recovery amplitude value and the unloading starting slope value thereof, calculates the recovery ratio and multiplies it by the unloading starting slope value to obtain the deformation recovery index value, and generates the unloading deformation elastic performance set; The degradation warning module selects measurement points with low deformation recovery index values ​​based on the unloading deformation elasticity performance set, compares the values ​​with the local compressive strength factor values, selects simultaneous degradation measurement points, calculates spatial density values, and generates a local performance degradation warning area map.

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