A coal mine multi-scale stress field joint monitoring and coupling analysis method

Abstract

The present application provides a kind of coal mine multiscale stress field joint monitoring and coupling analysis method, it is related to underground engineering dynamic disaster monitoring and early warning technical field, including: numerical simulation obtains mine scale stress field;Based on microseismic monitoring inversion calculation obtains mining area and mining working face scale stress field;In the stoping working face, driving working face is arranged electric shock vector monitor, according to the monitored vector electromagnetic radiation characteristic signal calculation obtains roadway surrounding rock scale stress field;Stress monitoring system is arranged on roadway wall, and the stress of local point in typical position of roadway is collected;The simulation or test results of different scale stress field are integrated, and the mine multiscale fusion stress field is calculated, according to the distribution characteristics of multiscale fusion stress field, the stress concentration area of mining area surrounding rock is identified and accurately divided.The present application is beneficial to improve the identification accuracy and efficiency of stress field, and has important application value for coal mine and other underground engineering dynamic disaster monitoring and early warning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underground engineering dynamic disaster monitoring and early warning, and particularly relates to a coal mine multi-scale stress field joint monitoring and coupling analysis method. BACKGROUND

[0002] With the increase of mining depth, the coal mine and other underground engineering are affected by high stress environment, the complexity of dynamic disaster causes increases, the frequency and intensity of disasters significantly strengthen, causing huge casualties and property losses, which brings severe challenges to the development of dynamic disaster monitoring and early warning. Therefore, an accurate and efficient stress monitoring method plays an important role in comprehensively understanding the disaster incubation process, developing effective prevention and control of deep dynamic disaster and ensuring safety production.

[0003] Research shows that underground engineering dynamic disaster is mainly affected by three factors of geological structure, stress environment and rock mass property. On the basis of proving the geological structure and rock mass property, the comprehensive perception of stress environment can effectively realize the reliability monitoring of disaster. At present, the visualization presentation technology of underground engineering stress field mainly includes numerical simulation, seismic wave CT inversion, hydraulic support monitoring and stress monitoring. Numerical simulation can realize large-scale stress field calculation of the whole mine, seismic wave CT technology can obtain the stress field of the mining area by using seismic wave velocity field inversion calculation, hydraulic support can realize the direct display of the stress results of the surrounding rock of the stope, and stress sensor can monitor the stress of the local typical position of the surrounding rock of the roadway.

[0004] However, the above different methods have different ranges of stress field inversion, and the same area stress characterization results of different scale stress fields have differences, and large-scale stress field inversion often leads to the generalization of local geological structure, and small-scale stress field cannot comprehensively reflect the stress field force source evolution process in different operation stages. The above analysis results show that the existing stress field results of the mining area of underground engineering are greatly affected by different scale monitoring results, the stress monitoring data analysis is insufficient, and the effective control of dynamic disaster evolution cannot be realized. SUMMARY

[0005] The present application provides a coal mine multi-scale stress field joint monitoring and coupling analysis method, which can solve the problem of generalization of local geological structure caused by large-scale stress field inversion, and can solve the problem of inability of small-scale stress field to comprehensively reflect the stress field force source evolution process in different operation stages.

[0006] To achieve the above application purposes, the technical solutions provided by the present application are as follows:

[0007] A coal mine multi-scale stress field joint monitoring and coupling analysis method comprises the following steps: step (1), establishing a mine fine numerical model, obtaining the stress components of the coal and rock mass of the mine by using in-situ stress test, and simulating to obtain the mine scale stress field k(x,y,z); step (2), based on at least 8 non-coplanar microseismic sensors arranged in the mining area, the stress field σ c(x,y,z) ; step (3), arranging an electric seismic vector monitor in a range of about 20m ahead of the working face, at intervals of about 20m, or about 20m behind the driving face, with a total length of not less than 200m, and calculating the stress field σ g(x,y,z) ; step (4), arranging a stress monitoring system on the roadway wall to collect the stress σ h ; step (5), integrating the stress field simulation or test results of steps (1)-(4) to calculate a multi-scale fusion stress field of the mine; step (6), identifying and accurately dividing the stress concentration area of the mining area surrounding rock according to the distribution characteristics of the multi-scale fusion stress field.

[0008] Exemplarily, in step (1), the simulation of the mine-scale stress field σ k(x,y,z) , comprises: S11, establishing a mine fine model according to engineering geological data, and combining with the size of each stress component obtained by the in-situ stress test to calculate the mine simulation stress field by numerical simulation; S12, using a multiple linear regression method, taking the measured stress component as the independent variable and the stress component as the dependent variable, constantly correcting the extrusion and shear boundary of the numerical model until the error between the numerical simulation result and the measured result meets the actual engineering requirement, and thus obtaining the mine-scale stress field σ k(x,y,z) .

[0009] Exemplarily, in step (2), the mining area and mining working face scale stress field σ c(x,y,z) , comprises: S21, obtaining the initial velocity V of the mining area surrounding rock by field blasting; S22, counting the microseismic events in a certain time interval T in the monitoring area, so that the microseismic rays generated by the coal and rock mass rupture in the interval T realize full coverage of the mining area, and the AIC criterion is used to accurately pick up the P-wave arrival time of the effective seismic wave signal, and then the simplex-dual difference joint positioning method is used to realize high-precision positioning of the coal and rock rupture source; S23, based on the initial velocity V of the mining area surrounding rock and the absolute arrival time, source location and microseismic sensor spatial layout coordinate information of each microseismic event obtained by steps S21 and S22, the SIRT algorithm is used to constantly iteratively solve the seismic wave velocity of the coal and rock mass in the monitoring area until the time residual meets the engineering requirement, and the seismic wave velocity field v c(x,y,z) is calculated, and the iteration process is as follows:

[0010]

[0011] In the formula, and is the slowness vector after different iteration times, n is the number of equations, m is the number of parameters, l ij is the distance of the i-th ray in the j-th earthquake source; S24, the scale stress field σ of the mining area and the mining working face is calculated based on the relationship between the vibration wave velocity and the stress function c(x，y,z) , the expression is as follows:

[0012]

[0013] Where λ and a are mine constant values.

[0014] For example, in step (3), the tunnel surrounding rock scale stress field σ is obtained m(x,y，z) , including: S31, statistical analysis of the tunnel surrounding rock at no less than 10 measuring points greater than the 7-day average value of electromagnetic radiation frequency N d With the average intensity E d ; S32, statistical analysis of the average stress value of the surrounding rock measured by the stress sensor at the same position and time range as the electromagnetic radiation measuring point σ h ; S33, based on the positive correlation between the characteristic parameters of the electromagnetic radiation signal and the surrounding rock stress, establish the surrounding rock stress σ h Respectively with the electromagnetic radiation frequency N d With intensity E d The functional relationship is as follows:

[0015]

[0016] Among them, k dp is the correlation coefficient between electromagnetic radiation frequency and stress, k dn is the correlation coefficient between electromagnetic radiation intensity and stress, k dp 、k dn , α and ζ are parameters related to the elastic modulus and strain of coal rock mass, based on which the electromagnetic radiation frequency to characterize the stress field of tunnel surrounding rock is obtained as σ p(x，y，z) The electromagnetic radiation intensity characterizes the stress field of the tunnel surrounding rock as σ n(x，y,z) , S34, according to the electromagnetic radiation frequency and intensity of the coal rock stress characterization effect, the tunnel surrounding rock stress field σ m(x,y，z) , the expression is as follows:

[0017] σ m(x,y,z) =l1σ p(x,y,z) +l2σ n(x,y,z)

[0018] Among them, l1 and l2 are the frequency and intensity of electromagnetic radiation in σ m(x,y,z) The weight in .

[0019] Exemplarily, in step (4), the stress monitoring system comprises a three-way stress sensor, and the three-dimensional stress σ1, σ2, σ3 of the region to be measured is solved according to the normal stress value of the three-way stress sensor, the borehole azimuth angle and the inclination angle.

[0020] Exemplarily, in step (5), the obtained mine multi-scale fusion stress field comprises: S71, in view of the difference in discrete interval of stress field data of different scales, the stress field data of different scales is grid processed by using the Kriging method, so as to realize the unification of different scale data grids; S72, the stress field σ m(x,y,z) of the roadway surrounding rock is taken as the calibration reference, the stress field σ k(x，y，z) of the mining area and the mining working face is taken as the calibration reference, the regression analysis is performed on the stress field σ c(x,y,z) of the mine scale, the local gradient stress change in the repeated data area and the boundary area is reduced, and the stress field σ k(x，y,z) of the mine scale is equal to the stress field σ A of the mining area and the mining working face, that is, σ c(x,y,z) of the mine scale is equal to σ B of the mining area and the mining working face, that is, σ m(x，y，z) of the mine scale is equal to σ D of the mining area and the mining working face, and the regression equation is as follows:

[0021]

[0022] wherein β0, β1, …, β N are regression equation parameters, which are obtained by using the least square method, σ εA and σ εB are random error terms between stress fields of different scales; S73, on the basis of the unified grid in step S71 and the unified reference difference in step S72, the stress field data of different scales is weighted calculated according to the criterion of reducing the loss of “small scale and high precision” data, and the multi-scale fusion stress field σ o(x,y,z) is obtained.

[0023] Exemplarily, in step S73, the stress field σ k(x,y,z) of the mine scale is weighted as k1, the stress field σ c(x，y,z) of the mining area and the mining working face is weighted as k2, the stress field σ m(x,y,z) of the roadway surrounding rock is weighted as k3, and k3>k2>k1 is satisfied, and accordingly, the calculation formula of the multi-scale fusion stress field σ o(x，y，z) is as follows:

[0024] σ o(x，y，z) = k1σ k(x,y,z) + k2σ c(x,y,z) + k3σ m(x,y,z)

[0025] Exemplarily, in step (6), the identifying and accurately dividing the stress concentration zone of the mining area surrounding rock comprises S61, according to the surrounding rock damage situation, based on the uniaxial compressive strength of the coal rock mass and the critical failure stress of the surrounding rock σ max , determining the coal rock mass failure critical stress concentration coefficient k max , the expression is as follows:

[0026]

[0027] Wherein, γ is the average unit weight of the coal rock mass, H is the average buried depth of the coal rock mass, σ max is the stress value when the coal rock mass fails; S62, according to the size of the stress concentration coefficient k, different grades of stress concentration zones are divided.

[0028] Exemplarily, in step S62, the division of the different grades of stress concentration zones comprises: k < 1, the coal rock mass is in a pressure relief state; k > 1, the stress state of the coal rock mass in different regions is determined by the following criteria: k in (1, 0.25k max ] region, the coal rock mass is in a normal stress state; k in (0.25k max , 0.5k max ] region, the coal rock mass is in a weak stress concentration state; k in (0.5k max , 0.75k max ] region, the coal rock mass is in a medium stress concentration state; k in (0.75k max , k max ) region, the coal rock mass is in a strong stress concentration state.

[0029] Compared with the prior art, the above technical solution has at least the following beneficial effects:

[0030] In the above technical solution, the numerical simulation and the monitoring system data such as microseismic, electromagnetic radiation and stress sensor are deeply analyzed, the stress field of the mine scale, the mining area and the mining working face scale and the roadway surrounding rock scale is respectively calculated, the different scale stress fields are effectively fused, the multi-scale fusion stress field is finally calculated, the effective identification and accurate division of the stress concentration zone of the mining area are carried out, the identification accuracy and efficiency of the surrounding rock stress field are improved, and the important guiding role for the mine monitoring and early warning and the dynamic disaster prevention work is played.

[0031] In the above scheme, by jointly arranging microseismic, electromagnetic radiation and stress sensor monitoring systems in the mining area, combined with numerical simulation, the stress field of the mine scale, mining area and mining working face scale and the surrounding rock scale of the roadway is calculated respectively, on this basis, according to the different scale distribution characteristics and the stress distribution representation efficiency of the surrounding rock, the grid and standard deviation of all scale stress field data are unified, and the multi-scale fusion stress field is calculated by weighted calculation; finally, according to the stress distribution of the fusion stress field in different mining areas, the stress concentration area is accurately identified and accurately divided, the coupling analysis of the stress field is realized, and the stress state of the surrounding rock is fully described and represented. The method realizes the complementary advantages of different monitoring methods, supplements the monitoring blind area of the stress field of different monitoring scales, improves the accuracy of the monitoring results of the surrounding rock stress, and has important guiding significance for the monitoring of underground engineering dynamic disasters. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment 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.

[0033] Figure 1 The flow chart of the coal mine multi-scale stress field joint monitoring and coupling analysis method of the embodiments of the present application;

[0034] Figure 2 The numerical simulation stress field result of the mine scale;

[0035] Figure 3 The schematic diagram of the microseismic, electromagnetic radiation and stress monitoring system in the mining area of the present application;

[0036] Figure 4 The electromagnetic radiation intensity and frequency monitoring results in the mining area;

[0037] Figure 5 The fusion stress field and coupling analysis result schematic diagram of the mining area calculated by the present application. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme of the embodiments of the present application will be described clearly and completely in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0039] Unless otherwise defined, technical terms or scientific terms used in the present application shall have the meanings that are commonly understood by a person of ordinary skill in the art to which the present application belongs. The terms "comprising" or "including" or similar words mean that the elements or objects covered by the terms encompass the elements or objects listed after the terms, equivalents thereof, and additional elements or objects. The terms "connected" or "linked" or similar words do not necessarily mean physically or mechanically connected, but can include electrical connection, whether direct or indirect.

[0040] In combination Figure 1 As shown, the embodiment of the present application provides a coal mine multi-scale stress field joint monitoring and coupling analysis method, comprising the following steps:

[0041] Step (1), a mine fine numerical model is established, the stress components borne by the coal and rock mass of the mine are obtained by using the in-situ stress test, and the mine scale stress field σ k(x，y，z) .

[0042] Step (2), based on at least 8 non-coplanar microseismic sensors arranged in the mining area, the mining area and the mining working face scale stress field σ c(x，y，z) .

[0043] Step (3), an electric seismic vector monitor is arranged in a range of about 20m ahead of the recovery working face, at intervals of about 20m, or about 20m behind the driving working face, with a total length of not less than 200m, and the roadway surrounding rock scale stress field σ g(x，y，z) .

[0044] Step (4), a stress monitoring system is arranged on the roadway wall surface, and the stress σ h .

[0045] Step (5), the simulation or test results of the stress fields of different scales in steps (1) to (4) are integrated to obtain a mine multi-scale fusion stress field.

[0046] Step (6), according to the distribution characteristics of the multi-scale fusion stress field, the stress concentration area of the surrounding rock in the mining area is identified and accurately divided.

[0047] It should be understood that although each step in the flowchart of the drawings is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. In the present application, steps (1) to (4) have no sequence and do not have to be executed in sequence, the sequence can be changed, one or more of them can be executed simultaneously, or four steps can be executed simultaneously.

[0048] Unless otherwise explicitly stated herein, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or sub-steps or stages of other steps.

[0049] According to the above embodiment of the present application, by jointly arranging microseismic, electromagnetic radiation and stress sensor monitoring systems in the mining area, combined with numerical simulation, the stress field of the mine scale, the mining area and the mining working face scale and the surrounding rock scale is calculated respectively, and on this basis, according to the different scale distribution characteristics and the stress distribution representation efficiency of the surrounding rock, the grid and the standard deviation of all scale stress field data are unified, and the multi-scale fusion stress field is calculated by weighted calculation; finally, according to the stress distribution of the fusion stress field in different mining areas, the stress concentration area is accurately identified and accurately divided, the coupling analysis of the stress field is realized, and the stress state of the surrounding rock is fully described and represented. This method realizes the complementary advantages of different monitoring methods, supplements the monitoring blind area of different monitoring scale stress field, improves the accuracy of the monitoring results of the surrounding rock stress, and has important guiding significance for underground engineering dynamic disaster monitoring.

[0050] Exemplarily, in step (1), the simulation of the mine scale stress field σ k( x ,y,z) , comprises: S11, establishing a mine fine model according to engineering geological data, combining with the size of each stress component obtained by in-situ stress test, and numerically simulating to obtain a mine simulation stress field; S12, using a multiple linear regression method, taking the measured stress component as the independent variable, and calculating the stress component as the dependent variable, constantly correcting the extrusion and shear boundary of the numerical model until the error between the numerical simulation result and the measured result meets the actual engineering requirement, thereby obtaining the mine scale stress field σ k(x,y,z) , and the result can be referred to as shown in Figure 2 .

[0051] In addition, in step (1), drilling, geophysical prospecting, geochemical prospecting, surveying and mapping, laboratory analysis professional comprehensive analysis method, and geographic information system (GIS) technology, building information modeling (BIM), computer aided design (CAD) software modeling technology can be used to construct the spatial distribution of fine underground mine and rock stratum morphology and characteristics, geological reserves, structure, hydrology, gas, mine pressure, rock or stratum physical property parameters, and automatically access mine geological exposure data and perception data to form a fine dynamic geological model of the mine.

[0052] In some embodiments, in step (1), the physical and mechanical property parameters of coal and rock at different layers and different lithologies can be determined by indoor tests, in-situ observations, mathematical statistics and other methods, the ground stress size and orientation of part of the measured points in the mine are determined, the constructed fine geological model is subjected to finite element mesh division, the different coal measures strata in the fine geological model are endowed with the determined corresponding physical and mechanical parameters, the finite element numerical model is constructed, based on the source of tectonic stress of the research block according to the regional tectonic movement law, the boundary is divided, and the finite element forward calculation and analysis are carried out, the multi-objective constraint optimization method is used to construct the mine ground stress optimization inversion model, that is, the objective function composed of the measured point ground stress size and orientation is established, the optimal boundary constraint and boundary load are determined, the obtained optimal boundary constraint and boundary load are applied to the finite element numerical analysis model, and the forward calculation and analysis are carried out, and the mine scale stress field σ k(x,y，z) .

[0053] In step (2), the obtained mining area and mining working face scale stress field can include the following

[0054] Step: S21, obtaining the initial velocity V of the surrounding rock of the mining area by field blasting.

[0055] S22, statistics of the monitoring area microseismic events within a certain time interval T, so that the microseismic rays generated by the coal and rock mass rupture within the interval T realize full coverage of the mining area, and the AIC criterion is used to accurately pick up the P-wave arrival time of the effective vibration wave signal, then the simplex-dual difference joint positioning method is used to realize high-precision positioning of the coal and rock rupture source.

[0056] S23, based on the initial velocity V of the surrounding rock of the mining area and the absolute arrival time, source location and microseismic sensor spatial layout coordinate information of each microseismic event obtained in steps S21 and S22, the SIRT algorithm is used to iteratively solve the vibration wave velocity of the coal and rock mass in the monitoring area, until the time residual meets the engineering requirements, and the vibration wave velocity field v c(x,y,z) is calculated, and the iteration process is as follows:

[0057]

[0058] In the formula, and are the slowness vectors after different iteration times, n is the number of equations, m is the number of parameters, and l ij is the distance of the i-th ray in the j-th source; S24, based on the relationship between the vibration wave velocity and the stress function, the mining area and mining working face scale stress field σ c(x,y,z) is calculated, and the expression is as follows:

[0059]

[0060] Wherein, λ and a are mine constant values.

[0061] In some other embodiments, the monitoring area can be determined based on the current mining range, mining progress and mining plan, the number of microseismic sensors should meet the needs of rock mass fracture source positioning accuracy in mine pressure disaster prevention and recovery sequence optimization process, the sensor arrangement mode should cover the monitoring area, the installation position of the sensor should be arranged according to the environmental conditions of the monitoring area, and the sensor is generally arranged in the roadway around the monitoring area, the installation mode of the sensor adopts permanent fixed installation (such as grouting mode) or movable installation (such as rock mass surface fixed mode), which is determined according to the monitoring cost and the reliability of signal capture, the signal transmission cable should be far away from the high-power electrical equipment in the mine, and the data acquisition and analysis server should be placed in the safe chamber in the mine, or the data is transmitted to the ground through the optical fiber mode for acquisition and analysis.

[0062] In addition, the position of the seismic source can be accurately positioned based on the positioning algorithm. A database of different types of signal characteristic parameters (such as frequency, period, signal duration, etc.) is established, signal time-frequency analysis technology or wavelet analysis technology is used, and production blasting, mechanical vibration, current interference and personnel activity interference signals are produced to effectively identify rock mass fracture signals; the velocity field model of the monitoring area is obtained through rock mass wave velocity test, and a positioning algorithm suitable for the mining technical conditions of the mine (such as least square method, Geiger algorithm, simplex algorithm, relative positioning method, etc.) is used to accurately position the position of the seismic source. The positioning accuracy of the microseismic monitoring system is tested by using artificial blasting to generate a seismic source, the spatial relationship between the microseismic event positioning position and the artificial blasting position is compared, the factors causing the positioning error are analyzed, and the monitoring area velocity field model is optimized and adjusted to make the positioning accuracy meet the monitoring purpose.

[0063] In step (3), the roadway surrounding rock scale stress field σ m(x，y,z) , comprising the following steps: S31, statistically analyzing the electromagnetic radiation frequency average value N d of more than 10 measuring points of the roadway surrounding rock for more than 7 days d , and the average value E h of the electromagnetic radiation intensity. Figure 3 The electromagnetic radiation monitoring result can refer to FIG. 6. Figure 4

[0064] S32, statistically analyzing the average stress value σ h of the surrounding rock measured by the stress sensor at the same position and in the same time range as the electromagnetic radiation measuring point.

[0065] S33, according to the positive correlation between the electromagnetic radiation signal characteristic parameters and the surrounding rock stress, the surrounding rock stress σ h is respectively established with the electromagnetic radiation frequency N d and the electromagnetic radiation intensity E dThe function relationship is as follows:

[0066]

[0067] wherein k dp is a stress correlation coefficient of electromagnetic radiation frequency, k dn is a stress correlation coefficient of electromagnetic radiation intensity, k dp , k dn , α and ζ are parameters related to the elastic modulus and strain of the coal rock mass, and the stress field represented by the electromagnetic radiation frequency of the roadway surrounding rock is σ p(x，y，z) , and the stress field represented by the electromagnetic radiation intensity of the roadway surrounding rock is σ n(x,y，z) S34, according to the stress representation efficiency of the electromagnetic radiation frequency and intensity of the coal rock mass, the stress field σ m(x,y，z) of the roadway surrounding rock is obtained, and the expression is as follows:

[0068] σ m(x，y，z) = l1σ p(x，y，z) + l2σ n(x，y,z)

[0069] wherein l1 and l2 are the weights of the electromagnetic radiation frequency and intensity in σ m(x,y,z) .

[0070] In some other embodiments, the indicators monitored by the electromagnetic radiation method can include electromagnetic radiation intensity, main frequency and frequency, and the stress indicators monitored by the stress method can be the drilling stress value.

[0071] In step (4), the stress monitoring system includes a three-way stress sensor, and the magnitudes and directions of the three-dimensional stresses σ1, σ2 and σ3 of the region to be measured are solved according to the normal stress value of the three-way stress sensor, the drilling azimuth angle and the inclination angle.

[0072] In the above steps, the comprehensive index method can be used to divide the whole mine range into zones and levels to determine the key monitoring area, or stress monitoring points can be arranged at intervals of about 20m on the roadway wall to collect the stress σ h of the local points at the typical positions of the roadway. The dynamic stress field CT inversion and microseismic technology can be applied to regional monitoring in the key monitoring area to further determine the local key monitoring range, or the electromagnetic radiation method or the stress method can be applied to real-time monitoring on the spot in the local dangerous range, and a multi-parameter normalized comprehensive early warning model is established based on the monitoring and analysis results.

[0073] In step (5), the obtained mine multi-scale fused stress field includes the following steps:

[0074] S71, according to the difference in the discrete spacing of the stress field data of different scales, the Kriging method is used to grid the stress field data of different scales to realize the unification of the data grids of different scales.

[0075] S72, with the roadway surrounding rock scale stress field σ m(x,y,z) Data is the correction reference, with the mine scale stress field σ k(x,y,z) And the mining area and mining face scale stress field σ c(x,y,z) Regression analysis is used to calibrate the different scale stress field reference difference, reduce the local gradient stress change in the repeated data area and the boundary area, and make σ k(x,y,z) σ A , σ c(x，y,z) σ B , σ m(x,y,z) σ D The regression equation is as follows:

[0076]

[0077] Where β0, β1, …, β N are regression equation parameters, estimated by the least square method, σ εA And σ εB are random error terms between different scale stress fields.

[0078] S73, based on the unified grid in step S71 and the unified reference difference in step S72, the different scale stress field data is weighted calculated to reduce the "small scale, high precision" data loss, and the multi-scale fusion stress field σ o(x，y，z) is obtained.

[0079] In step S73, the mine scale stress field σ k(x,y,z) The weight is k1, the mining area and mining face scale stress field σ c(x，y，z) The weight is k2, the roadway surrounding rock scale stress field σ m(x，y,z) The weight is k3, and k3>k2>k1, and accordingly, the different scale fusion stress field σ o(x，y，z) The calculation formula is expressed as follows:

[0080] σ o(x，y，z) =k1σ k(x,y,z) +k2σ c(x,y,z) +k3σ m(x,y,z)

[0081] In step (6), the identification and accurate division of the stress concentration area of the surrounding rock of the mining area include S61, according to the field surrounding rock failure, based on the uniaxial compressive strength of coal and rock mass and the critical failure stress σ max Of the surrounding rock, the coal and rock mass failure critical stress concentration coefficient k max Is determined, and the expression is as follows:

[0082]

[0083] Wherein, γ is the average bulk density of coal rock mass, H is the average buried depth of coal rock mass, σ max is the stress value when the coal rock mass is damaged; S62, according to the size of the stress concentration coefficient k, different grades of stress concentration zones are divided.

[0084] In step S62, the division of the different grades of stress concentration zones includes: k < 1, then the coal rock mass is in a pressure relief state; k > 1, then the stress state of the coal rock mass in different regions is determined by the following criteria.

[0085] k in (1, 0.25k max ) region, the coal rock mass is in a normal stress state; k in (0.25k max , 0.5k max ) region, the coal rock mass is in a weak stress concentration state; k in (0.5k max , 0.75k max ) region, the coal rock mass is in a medium stress concentration state; k in (0.75k max , k max ) region, the coal rock mass is in a strong stress concentration state.

[0086] The final grade division result of the stress concentration zone of the surrounding rock of the mining area is shown in Figure 5 According to the comprehensive and accurate identification of the stress concentration zone, important and effective guidance can be provided for the monitoring and early warning of the dynamic disaster of the underground engineering.

[0087] The embodiment of the coal mine multi-scale stress field joint monitoring and coupling analysis method provided by the application deeply mines and analyzes the numerical simulation and monitoring system data such as microseismic, electromagnetic radiation and stress sensors, respectively calculates the mine scale, mining area and mining working face scale and roadway surrounding rock scale stress field, effectively fuses different scale stress fields, finally calculates a multi-scale fused stress field, and accordingly carries out effective identification and accurate division of the stress concentration zone of the mining area, improves the identification precision and efficiency of the surrounding rock stress field, and plays an important guiding role in the monitoring and early warning of the mine and the prevention and control of dynamic disasters.

[0088] In combination with the above embodiment, the regional and local stress field monitoring system of microseismic, electromagnetic radiation, stress sensors and the like is arranged in the mining area of the mine, different scale stress field distributions of the mine, mining area, working face and roadway surrounding rock and the like are respectively obtained according to numerical simulation and system monitoring data, on this basis, a multi-scale fused stress field is calculated according to the joint monitoring data of different scale stress fields, and the stress concentration zone of the mining area is identified and finely divided. The application realizes the complementary advantages of the "large scale, low precision" and "small scale, high precision" different scale stress field analysis methods, improves the identification precision and efficiency of the stress field, and has important application value for the monitoring and early warning of the dynamic disaster of the underground engineering such as coal mine.

[0089] The following points need to be explained:

[0090] (1) The drawings of the embodiments of the present application only relate to the structures involved in the embodiments of the present application, and other structures can be referred to the general design.

[0091] (2) In the drawings used to describe the embodiments of the present application, the thickness of a layer or region is exaggerated or reduced for clarity, i.e., the drawings are not drawn according to the actual scale.

[0092] (3) In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined to obtain new embodiments.

[0093] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A coal mine multi-scale stress field combined monitoring and coupling analysis method, characterized in that, The method comprises the following steps: Step (1), the establishment of mine fine numerical model, using the stress test to get the stress component of coal and rock mass, simulation of mine scale stress field σ k(x,y,z) ; Step (2), based on at least 8 non-coplanar microseismic sensors arranged in the mining area, the stress field σ of the mining area and the mining working face is calculated by using the inversion results of the wave velocity field of the surrounding rock seismic wave c(x,y,z) ; Step (3), the electric shock vector monitor is arranged in the range of about 20 m in front of the advanced back-caving working face, about 20 m in interval, or about 20 m in interval behind the heading working face, and the total length is not less than 200 m, and the roadway surrounding rock scale stress field σ is calculated according to the monitored vector electromagnetic radiation characteristic signal g(x,y,z) ; Step (4), arranging a stress monitoring system on the roadway wall surface to collect the stress σ of local points at typical positions of the roadway h ; Step (5), synthesizing the stress field simulation or test results of different scales in steps (1)-(4) to obtain a mine multi-scale fusion stress field, wherein the mine multi-scale fusion stress field comprises the following steps: S71, using the Kriging method to grid the different scale stress field data to realize the unification of different scale data grids, in view of the difference in discrete interval of different scale stress field data; S72, with roadway surrounding rock stress field σ m(x,y,z) Data is the correction reference, to the mine scale stress field σ k(x,y,z) And mining area and mining face scale stress field σ c(x,y,z) Regression analysis calibration different scale stress field reference difference, reduce data repeated area and boundary area appeared local gradient stress change, make σ k(x,y,z) For σ A , σ c(x,y,z) For σ B , σ m(x,y,z) For σ D , regression equation is shown as follows: where β0, β1, …, β N are regression equation parameters, estimated by the least square method, and σ εA and σ εB are random error terms between stress fields of different scales. S73, on the basis of the unified grid in step S71 and the unified reference difference in step S72, weighted calculation is performed on the stress field data of different scales to obtain a multi-scale fused stress field σ o(x,y,z) ; Step (6), judging and accurately dividing the stress concentration zone of the mining area surrounding rock according to the distribution characteristics of the multi-scale fusion stress field.

2. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step (1), the simulation obtains a mine-scale stress field σ k(x,y,z) comprising the steps of: S11, establishing a mine fine model according to the engineering geological data, and combining the size of each stress component obtained by the in-situ stress test to obtain a mine simulation stress field by numerical simulation calculation; S12, using the multiple linear regression method, the measured stress component as the independent variable, the stress component as the dependent variable, constantly correct the extrusion and shear boundary of the numerical model, until the error between the numerical simulation results and the measured results meets the actual engineering requirements, according to which the stress field σ k(x,y,z) is obtained.

3. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step (2), the obtained stress field σ c(x,y,z) comprising the steps of: S21, obtaining the initial velocity V of the mining area surrounding rock by using the field blasting; S22, statistically monitoring the microseismic events in a certain time interval T, so that the microseismic rays generated by the coal and rock mass rupture in the interval T realize full coverage of the mining area, the AIC criterion is used to accurately pick up the P-wave arrival time of the effective vibration wave signal, and the simplex-double-difference joint positioning method is used to realize high-precision positioning of the coal and rock rupture source; S23, based on the initial velocity V of the mining area surrounding rock obtained in steps S21 and S22, the absolute arrival time of each microseismic event, the hypocenter location, and the spatial layout coordinate information of the microseismic sensor, the SIRT algorithm is used to continuously iteratively solve the vibration wave velocity of the coal and rock mass in the monitoring area until the time residual meets the engineering requirements, and the vibration wave velocity field v is calculated c(x，y,z) , the iteration process is as follows: wherein with are slowness vectors after different iteration numbers, n is the number of equations, m is the number of parameters, l ij is the distance of the i-th ray in the j-th source. S24, calculating the stress field σ of the mining area and the mining working face based on the relationship between the vibration wave velocity and the stress function c(x,y,z) : In the formula, λ and a are constant values of the mine.

4. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step (3), the roadway surrounding rock scale stress field σ m(x,y,z) comprising the steps of: S31, statistical analysis of the roadway surrounding rock not less than 10 measuring points greater than 7 days electromagnetic radiation frequency average value N d with the average value of intensity E d ; S32, statistically analyze the average stress value σ of the surrounding rock measured by the stress sensor in the same position and time range as the electromagnetic radiation measuring point h ; S33, according to the positive correlation between the electromagnetic radiation signal characteristic parameters and the surrounding rock stress, the surrounding rock stress σ h respectively with electromagnetic radiation frequency N d and intensity E d The function relationship is as follows: wherein k dp is the electromagnetic radiation frequency and stress correlation coefficient, k dn is the electromagnetic radiation intensity and stress correlation coefficient, k dp , k dn , α and ζ are parameters related to the elastic modulus and strain of the coal rock mass, and the electromagnetic radiation frequency stress field of the surrounding rock of the roadway is σ p(x,y,z) , and the electromagnetic radiation intensity stress field of the surrounding rock of the roadway is σ n(x,y,z) ; S34, according to the electromagnetic radiation frequency and intensity of coal and rock stress characterization performance, get roadway stress field σ m(x,y,z) , the expression is as follows: σ m(x,y,z) = l1σ p(x,y,z) + l2σ n(x,y,z) wherein li and l2 are the weights of the electromagnetic radiation frequency and intensity in σ m(x,y,z) , respectively.

5. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step (4), the stress monitoring system comprises a three-way stress sensor, and the three-dimensional stress σ1, σ2, σ3 and direction of the region to be measured are solved according to the normal stress value, borehole azimuth angle and inclination angle of the three-way stress sensor.

6. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step S73, the mine-scale stress field σ k(x,y,z) The weight is k1, the stress field σ c(x,y,z) The weight is k2, the stress field σ m(x,y,z) The weight is k3, and k3>k2>k1 is satisfied, according to which the stress field σ o(x,y,z) The calculation formula is expressed in the following form: σ o(x,y，z) = k1σ k(x，y，z) + k2σ c(x，y，z) + k3σ m(x，y，z) .

7. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 1, characterized in that, In step (6), the judging and accurately dividing the stress concentration zone of the mining area surrounding rock comprises the following steps: S61, according to the field surrounding rock damage, based on coal rock mass uniaxial compressive strength and surrounding rock critical failure stress σ max , determine the coal rock mass failure critical stress concentration coefficient k max , the expression is as follows: wherein γ is the average bulk density of the coal rock mass, H is the average buried depth of the coal rock mass, σ max is the stress value at the time of failure of the coal rock mass; S62, dividing different grade stress concentration zones according to the size of the stress concentration coefficient k.

8. The coal mine multi-scale stress field combined monitoring and coupling analysis method according to claim 7, characterized in that, In step S62, the division of different grade stress concentration zones comprises: k<1, the coal and rock mass is in a pressure relief state; k>1, the stress state of the coal and rock mass in different regions is determined by the following criteria: max ]region, the coal rock mass is in normal stress state;​ ii) k is in the range (0.25k max , 0.5k max ] and the coal rock mass is in a weak stress concentration state; iii) k is in the range of (0.5k max , 0.75k max ] and the coal rock mass is in a medium stress concentration state; (4) k is in the range of (0.75k max , k max ), the coal rock mass is in a state of strong stress concentration.

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