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

Abstract

The invention provides a coal mine multi-scale stress field joint monitoring and coupling analysis method, and relates to the technical field of underground engineering dynamic disaster monitoring and early warning. Scale stress fields of the mining area and the mining working face are obtained based on micro-seismic monitoring inversion calculation; electric shock vector monitors are arranged on a stope face and a driving face, and a roadway surrounding rock scale stress field is obtained through calculation according to monitored vector electromagnetic radiation characteristic signals; arranging a stress monitoring system on the wall surface of the roadway, and collecting stress of local points at typical positions of the roadway; simulating or testing results of the stress fields with different scales are integrated, a mine multi-scale fusion stress field is obtained through calculation, and the surrounding rock stress concentration area of the mining area is identified and accurately divided according to distribution characteristics of the multi-scale fusion stress field. The method is beneficial to improving the identification precision and efficiency of the stress field, and has an important application value for monitoring and early warning of dynamic disasters of underground engineering such as a coal mine.

Description

Technical Field

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

[0002] As mining depth increases, underground projects such as coal mines are affected by high stress environments, the complexity of the causes of dynamic disasters increases, and the frequency and intensity of disasters significantly increase, causing huge casualties and property losses, which brings severe challenges to the monitoring and early warning of dynamic disasters. Therefore, accurate and efficient stress monitoring methods play an important role in fully understanding the process of disaster incubation, effectively preventing and controlling deep dynamic disasters, and ensuring safe production.

[0003] Research shows that underground engineering dynamic disasters are mainly affected by three factors: geological structure, stress environment and rock mass properties. On the basis of exploring geological structure and rock mass properties, comprehensive perception of stress environment can effectively realize reliable monitoring of disasters. At present, the visualization technology of underground engineering stress field mainly consists of numerical simulation, vibration wave CT inversion, hydraulic support monitoring and stress monitoring. Numerical simulation can realize large-scale stress field calculation of the whole mine, vibration wave CT technology can use vibration wave velocity field inversion to calculate the stress field of the mining area, hydraulic support can realize direct display of the surrounding rock stress results of the mining area, and stress sensor can monitor the stress of local typical positions of the surrounding rock of the tunnel.

[0004] However, the above different methods have different ranges of stress field inversion, and different scale stress fields have different stress characterization results for the same area. In addition, large-scale stress field inversion often leads to the generalization of local geological structures, and small-scale stress fields cannot fully reflect the evolution of stress field force sources at different operation stages. The above analysis results show that the stress field results of existing underground engineering excavation areas are greatly affected by monitoring results at different scales, and the analysis of stress monitoring data is insufficient, which cannot effectively control the evolution of dynamic disasters. Summary of the invention

[0005] The present invention provides a method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines, which can not only solve the problem of generalization of local geological structures caused by large-scale stress field inversion, but also solve the problem that small-scale stress fields cannot fully reflect the evolution process of stress field force sources in different operation stages.

[0006] In order to achieve the above-mentioned invention object, the technical solution provided by the present invention is as follows:

[0007] A method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines, comprising: step (1), establishing a fine numerical model of the mine, using ground stress testing to obtain stress components of the coal and rock mass in the mine, and simulating the 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 scale stress field σ of the mining area and the mining working face is calculated using the inversion results of the surrounding rock vibration wave velocity field c(x,y,z) Step (3), arrange the seismic vector monitor within a range of about 20m and about 20m intervals at the advanced mining face, or about 20m intervals behind the excavation face, with a total length of not less than 200m, and calculate the tunnel surrounding rock scale stress field σ based on the monitored vector electromagnetic radiation characteristic signal g(x,y,z) ; Step (4), arrange a stress monitoring system on the tunnel wall to collect stress σ at local points at typical locations in the tunnel h ; Step (5), integrating the simulation or test results of stress fields at different scales in steps (1) to (4), and calculating the multi-scale fusion stress field of the mine; Step (6), identifying and accurately dividing the surrounding rock stress concentration area in the mining area according to the distribution characteristics of the multi-scale fusion stress field.

[0008] Exemplarily, in step (1), the simulation obtains the mine-scale stress field σ k(x,y,z) , including: S11, according to the engineering geological data, establish a refined mine model, combine the stress components obtained by the ground stress test, and calculate the simulated stress field of the mine through numerical simulation; S12, use the multivariate linear regression method, take the measured stress components as independent variables, and calculate the stress components as dependent variables, and continuously correct the extrusion and shear boundaries of the numerical model until the error between the numerical simulation results and the measured results meets the actual engineering needs, thereby obtaining the mine-scale stress field σ k(x,y,z) .

[0009] For example, in step (2), the obtained scale stress field σ of the mining area and the mining working face is c(x,y,z) , including: S21, using on-site blasting to obtain the initial velocity V of the surrounding rock in the mining area; S22, counting the microseismic events in the monitoring area within a certain time interval T, so that the microseismic rays generated by the coal and rock mass fractures in the interval T can achieve full coverage of the mining area, and the effective vibration wave signal P wave arrival time is accurately picked up by the AIC criterion, and the simplex-double difference joint positioning method is used to achieve high-precision positioning of the coal and rock fracture source; S23, based on the initial velocity V of the surrounding rock in the mining area obtained in step S21 and step S22 and the absolute arrival time of each microseismic event, the source position 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:

[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, based on the relationship between the vibration wave velocity and the stress function, the scale stress field σ of the mining area and the mining working face is calculated 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 7 days of electromagnetic radiation frequency average value N d With the intensity average 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 electromagnetic radiation signals and 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 characterizes the stress field of tunnel surrounding rock as σ p(x，y，z) The electromagnetic radiation intensity represents 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 includes a three-dimensional stress sensor, and the magnitude and direction of the three-dimensional stresses σ1, σ2, σ3 in the measured area are solved based on the normal stress value, drilling azimuth and inclination of the three-dimensional stress sensor.

[0020] For example, in step (5), obtaining the multi-scale fusion stress field of the mine includes: S71, using the Kriging method to grid the stress field data of different scales according to the difference in discrete spacing of the stress field data of different scales, so as to unify the grids of the data of different scales; S72, using the tunnel surrounding rock scale stress field σ m(x,y,z) The data is used as the calibration benchmark for the mine-scale stress field σ k(x，y，z) and the scale stress field of the mining area and the mining face σ c(x,y,z) Regression analysis is performed to calibrate the reference difference of stress fields at different scales, reducing the local gradient stress changes in the data repetition area and boundary area. k(x，y,z) is A , σ c(x,y,z) is B , σ m(x，y，z) is D , the regression equation is as follows:

[0021]

[0022] Among them, β0, β1, …, β N is the regression equation parameter, estimated using the least squares method, σ εA and σ εB is the random error term between stress fields of different scales; S73, based on the unified grid in step S71 and the unified benchmark difference in step S72, weighted calculation is performed on stress field data of different scales with the principle of reducing the loss of “small scale, high precision” data to obtain the multi-scale fusion stress field σ o(x,y,z) .

[0023] For example, in step S73, let the mine-scale stress field σ k(x,y,z) The weight is k1, the scale stress field of the mining area and the mining face σ c(x，y,z) The weight is k2, and the tunnel surrounding rock scale stress field σ m(x,y,z) The weight is k3, and k3>k2>k1. Based on this, the fusion stress field σ of different scales o(x，y，z) The calculation formula is expressed as follows:

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

[0025] For example, in step (6), the identification and accurate division of the surrounding rock stress concentration zone in the mining area includes S61, according to the surrounding rock failure situation on site, based on the uniaxial compressive strength of the coal rock mass and the critical failure stress σ of the surrounding rock max , determine the critical stress concentration factor k of coal rock failure max , the expression is as follows:

[0026]

[0027] Among them, γ is the average bulk density of coal rock mass, H is the average burial depth of coal rock mass, σ max It is the stress value when the coal rock mass is destroyed; S62, according to the size of the stress concentration coefficient k, different levels of stress concentration zones are divided.

[0028] For example, in step S62, the division of stress concentration zones of different levels includes: k < 1, the coal rock mass is in a decompression state; k > 1, the stress state of the coal rock mass in different regions is determined by the following criteria: k is within (1, 0.25k max ] area, the coal rock mass is in a normal stress state; k is (0.25k max , 0.5k max ] area, the coal rock mass is in a weak stress concentration state; k is in (0.5k max , 0.75k max ] area, the coal rock mass is in a state of medium stress concentration; k is (0.75k max , k max ) area, the coal rock mass is in a state of strong stress concentration.

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

[0030] In the above technical scheme, the data of numerical simulation, microseismic, electromagnetic radiation and stress sensor monitoring systems are deeply mined and analyzed, and the stress fields at the mine scale, mining area and mining face scale and tunnel surrounding rock scale are calculated respectively. The stress fields of different scales are effectively integrated, and finally the multi-scale fusion stress field is calculated. Based on this, the effective identification and accurate division of stress concentration areas in the mining area are carried out, the identification accuracy and efficiency of the surrounding rock stress field are improved, and it plays an important guiding role in mine monitoring, early warning and dynamic disaster prevention and control.

[0031] In the above scheme, by jointly arranging monitoring systems such as microseismic, electromagnetic radiation and stress sensors in the mining area, combined with numerical simulation, the stress fields at the mine scale, mining area and mining face scale, and tunnel surrounding rock scale are calculated respectively. On this basis, according to the distribution characteristics of different scales and the efficiency of characterizing the stress distribution of surrounding rock, the grid and standard deviation of all scale stress field data are unified, and the multi-scale fusion stress field is obtained by weighted calculation; finally, according to the stress distribution in different areas of the mining range of the fusion stress field, the stress concentration area is accurately identified and precisely divided, and the coupling analysis of the stress field is realized, and the surrounding rock stress state is comprehensively portrayed and characterized. This method realizes the complementary advantages of different monitoring methods, supplements the monitoring blind spots of stress fields at different monitoring scales, improves the accuracy of surrounding rock stress monitoring results, and has important guiding significance for the monitoring of dynamic disasters in underground engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 Flow chart of the method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to an embodiment of the present invention;

[0034] Figure 2 The stress field results of the numerical simulation are at the mine scale;

[0035] Figure 3 This is a schematic diagram of the arrangement of the microseismic, electromagnetic radiation and stress monitoring system in the mining area of ​​the present invention;

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

[0037] Figure 5 This is a schematic diagram of the fusion stress field and coupling analysis results of the mining area calculated by the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the common meanings understood by persons with ordinary skills in the field to which the present invention belongs. "Include" or "comprising" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0040] Combination Figure 1 As shown, an embodiment of the present invention provides a method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines, comprising the following steps:

[0041] Step (1) establishes a fine numerical model of the mine, uses the ground stress test to obtain the stress components of the coal and rock mass in the mine, and simulates 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 scale stress field σ of the mining area and the mining working face is calculated using the inversion results of the surrounding rock vibration wave velocity field c(x，y，z) .

[0043] Step (3) arranges seismic vector monitoring instruments within a range of about 20 m at an interval of about 20 m at the advanced mining face, or about 20 m behind the excavation face, with a total length of not less than 200 m, and calculates the tunnel surrounding rock scale stress field σ based on the monitored vector electromagnetic radiation characteristic signal. g(x，y，z) .

[0044] Step (4): arrange a stress monitoring system on the tunnel wall to collect stress σ at local points at typical locations in the tunnel. h .

[0045] Step (5), integrating the simulation or test results of stress fields at different scales in steps (1) to (4), and calculating the multi-scale fusion stress field of the mine.

[0046] Step (6), based on the multi-scale fusion stress field distribution characteristics, identify and accurately divide the surrounding rock stress concentration area in the mining area.

[0047] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. In the present application, steps (1) to (4) have no chronological order and need not be performed in sequence. The order may be changed, one or more of the steps may be performed simultaneously, or all four steps may be performed simultaneously.

[0048] Unless otherwise specified herein, the execution of these steps is not strictly limited in order and may be executed in other orders. Moreover, at least a portion of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and their execution order is not necessarily sequential, but may be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0049] According to the above-mentioned embodiments of the present application, by jointly arranging monitoring systems such as microseismic, electromagnetic radiation and stress sensors in the mining area, combined with numerical simulation, the stress fields at the mine scale, mining area and mining face scale, and tunnel surrounding rock scale are calculated respectively. On this basis, according to the distribution characteristics of different scales and the efficiency of characterizing the stress distribution of the surrounding rock, the grid and standard deviation of all scale stress field data are unified, and weighted calculation is performed to obtain a multi-scale fusion stress field; finally, according to the stress distribution in different areas of the mining range of the fusion stress field, the stress concentration area is accurately identified and precisely divided, and the coupled analysis of the stress field is realized, and the surrounding rock stress state is comprehensively portrayed and characterized. This method realizes the complementary advantages of different monitoring methods, supplements the monitoring blind spots of stress fields at different monitoring scales, improves the accuracy of surrounding rock stress monitoring results, and has important guiding significance for the monitoring of dynamic disasters in underground engineering.

[0050] Exemplarily, in step (1), the simulation obtains the mine-scale stress field σ k( x ,y,z) , including: S11, according to the engineering geological data, establish a refined mine model, combine the stress components obtained by the ground stress test, and calculate the simulated stress field of the mine through numerical simulation; S12, use the multivariate linear regression method, take the measured stress components as independent variables, and calculate the stress components as dependent variables, and continuously correct the extrusion and shear boundaries of the numerical model until the error between the numerical simulation results and the measured results meets the actual engineering needs, thereby obtaining the mine-scale stress field σ k(x,y,z) The results can be referred to Figure 2 shown.

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

[0052] In some embodiments, in step (1), indoor tests, on-site in-situ observations, mathematical statistics and other methods can be used to determine the physical and mechanical property parameters of coal and rock at different strata and different lithologies, determine the magnitude and orientation of the ground stress at some measured points in the mine, perform finite element meshing on the constructed refined geological model, assign the determined corresponding physical and mechanical parameters to different coal-bearing strata in the refined geological model, construct a finite element numerical model, perform boundary differentiation based on the regional tectonic movement law and the source of the tectonic stress in the study area, perform finite element forward calculation and analysis, and use a multi-objective constraint optimization method to construct an optimal inversion model of mine ground stress, that is, establish an objective function composed of the magnitude and orientation of the ground stress at the measured points, determine the optimal boundary constraints and boundary loads, apply the obtained optimal boundary constraints and boundary loads to the finite element numerical analysis model, perform forward calculation and analysis, and simulate the mine-scale stress field σ k(x,y，z) .

[0053] In step (2), the method of obtaining the scale stress field of the mining area and the mining working face may include the following steps:

[0054] Step: S21, using on-site blasting to obtain the initial velocity V of the surrounding rock in the mining area.

[0055] S22, statistics the microseismic events in the monitoring area within a certain time interval T, so that the microseismic rays generated by the coal and rock fractures within the interval T can fully cover the mining area, and the effective shock wave signal P wave is accurately picked up by the AIC criterion. Then, the simplex-double difference joint positioning method is used to realize high-precision positioning of the coal and rock fracture source.

[0056] S23, based on the initial velocity V of the surrounding rock in the mining area obtained in step S21 and step S22 and the absolute arrival time of each microseismic event, the source location and the spatial layout coordinate information of the microseismic sensor, the vibration wave velocity of the coal and rock mass in the monitoring area is continuously iterated and solved using the SIRT algorithm 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:

[0057]

[0058] 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, based on the relationship between the vibration wave velocity and the stress function, the scale stress field σ of the mining area and the mining working face is calculated c(x,y,z) , the expression is as follows:

[0059]

[0060] Where λ and a are mine constant values.

[0061] In some other embodiments, the monitoring area can be determined based on the current mining scope, mining progress and mining plan. The number of microseismic sensors should meet the needs of rock rupture source positioning accuracy in the process of mine ground pressure disaster prevention and control and mining sequence optimization. The sensor layout should cover the monitoring area. The installation location of the sensor should be arranged according to the environmental conditions of the monitoring area, and is generally arranged in the tunnels around the monitoring area. The sensor installation method adopts permanent fixed installation (such as grouting method) or movable installation (such as rock surface fixing method), depending on the monitoring cost and the reliability of signal capture. The signal transmission cable should be as far away as possible from the underground high-power electrical equipment, and the data acquisition and analysis server should be placed in the underground safety chamber, or the data should be transmitted to the surface via optical fiber for collection and analysis.

[0062] In addition, the earthquake source can be accurately located based on the positioning algorithm. Establish a database of different types of signal characteristic parameters (such as frequency, period, signal duration, etc.), use signal time-frequency analysis technology or wavelet analysis technology, production blasting, mechanical vibration, current interference, personnel activity interference signals, and effectively identify rock fracture signals; obtain the velocity field model of the monitoring area through rock wave velocity testing, and use the positioning algorithm suitable for the mining technical conditions of the mine (such as least squares method, Geiger algorithm, simplex algorithm, relative positioning method, etc.) to accurately locate the earthquake source. The method of artificial blasting to generate earthquake sources is used to test the positioning accuracy of the microseismic monitoring system, compare the spatial relationship between the positioning position of the microseismic event and the artificial blasting position, analyze the factors that cause positioning errors, and optimize and adjust the velocity field model of the monitoring area so that the positioning accuracy meets the monitoring purpose.

[0063] In step (3), the tunnel surrounding rock scale stress field σ is obtained m(x，y,z) , including the following steps: S31, statistically analyzing the average value N of the electromagnetic radiation frequency of no less than 10 measuring points in the tunnel surrounding rock for more than 7 days d With the intensity average E d , the monitoring arrangement of the electric seismic vector monitor can refer to Figure 3 As shown, the electromagnetic radiation monitoring results can be referred to Figure 4 shown.

[0064] 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 measurement point σ h .

[0065] S33, based on the positive correlation between the characteristic parameters of electromagnetic radiation signals and surrounding rock stress, establish the surrounding rock stress σ h Respectively with the electromagnetic radiation frequency N d With intensity E dThe functional relationship is as follows:

[0066]

[0067] 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 characterizes the stress field of tunnel surrounding rock as σ p(x，y，z) The electromagnetic radiation intensity represents the stress field of the tunnel surrounding rock as σ n(x,y，z) S34, according to the electromagnetic radiation frequency and intensity, the stress characterization efficiency of coal rock mass is obtained, and the surrounding rock stress field σ of the tunnel is obtained. m(x,y，z) , the expression is as follows:

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

[0069] Among them, l1 and l2 are the frequency and intensity of electromagnetic radiation in σ m(x,y,z) The weight in .

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

[0071] In step (4), the stress monitoring system includes a three-dimensional stress sensor, and the size and direction of the three-dimensional stresses σ1, σ2, and σ3 in the measured area are solved according to the normal stress value, drilling azimuth and inclination of the three-dimensional stress sensor.

[0072] In the above steps, the comprehensive index method can be used to divide and classify the entire mine range to determine the key monitoring areas, or stress monitoring points can be arranged at intervals of about 20m on the tunnel wall to collect stress σ at local points at typical locations in the tunnel. h Dynamic stress field CT inversion and microseismic technology can be used to conduct regional monitoring in key monitoring areas to further determine the local key monitoring range. Electromagnetic radiation method or stress method can also be used to conduct on-site real-time monitoring of the local dangerous range, and a multi-parameter normalized comprehensive early warning model can be established for the monitoring and analysis results.

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

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

[0075] S72, based on the tunnel surrounding rock scale stress field σ m(x,y,z) The data is used as the calibration benchmark for the mine-scale stress field σ k(x,y,z) and the scale stress field of the mining area and the mining face σ c(x,y,z) Regression analysis is performed to calibrate the reference difference of stress fields at different scales, reducing the local gradient stress changes in the data repetition area and boundary area. k(x,y,z) is A , σ c(x，y,z) is B , σ m(x,y,z) is D , the regression equation is as follows:

[0076]

[0077] Among them, β0, β1, …, β N is the regression equation parameter, estimated using the least squares method, σ εA and σ εB is the random error term between stress fields of different scales.

[0078] S73, based on the unified grid in step S71 and the unified benchmark difference in step S72, weighted calculation is performed on stress field data of different scales to obtain the multi-scale fusion stress field σ o(x，y，z) .

[0079] In step S73, let the mine-scale stress field σ k(x,y,z) The weight is k1, the scale stress field of the mining area and the mining face σ c(x，y，z) The weight is k2, and the tunnel surrounding rock scale stress field σ m(x，y,z) The weight is k3, and k3>k2>k1. Based on this, the fusion stress field σ of different scales 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 surrounding rock stress concentration zone in the mining area includes S61, according to the surrounding rock failure situation on site, based on the uniaxial compressive strength of the coal rock mass and the critical failure stress σ max , determine the critical stress concentration factor k of coal rock failure max , the expression is as follows:

[0082]

[0083] Among them, γ is the average bulk density of coal rock mass, H is the average burial depth of coal rock mass, σ max It is the stress value when the coal rock mass is destroyed; S62, according to the size of the stress concentration coefficient k, different levels of stress concentration zones are divided.

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

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

[0086] The final classification results of surrounding rock stress concentration areas in the mining area are as follows: Figure 5 As shown in the figure, based on the comprehensive and accurate identification of stress concentration areas, it can provide important and effective guidance for the monitoring and early warning of dynamic disasters in underground engineering.

[0087] The embodiment of the method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines provided by the present invention conducts in-depth mining and analysis of data from monitoring systems such as numerical simulation and microseismic, electromagnetic radiation and stress sensors, and respectively calculates stress fields at the mine scale, mining area and mining face scale, and tunnel surrounding rock scale, and effectively fuses stress fields of different scales, and finally calculates a multi-scale fused stress field, based on which effective identification and accurate division of stress concentration areas in the mining area are carried out, the identification accuracy and efficiency of the surrounding rock stress field are improved, and an important guiding role is played in mine monitoring, early warning, and dynamic disaster prevention and control work.

[0088] In summary of the above embodiments, microseismic, electromagnetic radiation, stress sensors and other regional and local stress field monitoring systems are arranged in the mining area of ​​the mine, and the stress field distributions of different scales such as the mine, mining area, working face and tunnel surrounding rock are obtained according to numerical simulation and system monitoring data. On this basis, according to the joint monitoring data of stress fields of different scales, the multi-scale fusion stress field is calculated, and the stress concentration area of ​​the mining area is identified and finely divided. The present invention realizes the complementary advantages of "large scale, low precision" and "small scale, high precision" stress field analysis methods of different scales, improves the recognition accuracy and efficiency of the stress field, and has important application value for monitoring and early warning of dynamic disasters in underground engineering such as coal mines.

[0089] There are a few points to note:

[0090] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention, and other structures may refer to the general design.

[0091] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of layers or regions are enlarged or reduced, that is, these drawings are not drawn according to the actual scale.

[0092] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0093] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines, characterized in that: The following steps are involved: Step (1) establishes a fine numerical model of the mine, uses the ground stress test to obtain the stress components of the coal and rock mass in the mine, and simulates the 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 scale stress field σ of the mining area and the mining working face is calculated using the inversion results of the surrounding rock vibration wave velocity field c(x,y,z) ; Step (3) arranges seismic vector monitoring instruments within a range of about 20 m at an interval of about 20 m at the advanced mining face, or about 20 m behind the excavation face, with a total length of not less than 200 m, and calculates the tunnel surrounding rock scale stress field σ based on the monitored vector electromagnetic radiation characteristic signal. g(x,y,z) ; Step (4): arrange a stress monitoring system on the tunnel wall to collect stress σ at local points at typical locations in the tunnel. h ; Step (5), integrating the simulation or test results of stress fields at different scales in steps (1) to (4), and calculating a multi-scale fusion stress field of the mine; Step (6), based on the multi-scale fusion stress field distribution characteristics, identify and accurately divide the surrounding rock stress concentration area in the mining area.

2. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1 is characterized in that: In step (1), the simulation obtains the mine-scale stress field σ k(x,y,z) , including the following steps: S11, based on engineering geological data, establish a refined mine model, combine the magnitude of each stress component obtained by the ground stress test, and calculate the simulated stress field of the mine through numerical simulation; S12, using the multivariate linear regression method, taking the measured stress component as the independent variable and the calculated stress component as the dependent variable, the extrusion and shear boundaries of the numerical model are continuously corrected until the error between the numerical simulation results and the measured results meets the actual engineering requirements, and the mine-scale stress field σ is obtained. k(x,y,z) .

3. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1 is characterized in that: In step (2), the obtained scale stress field σ of the mining area and the mining working face is c(x,y,z) , including the following steps: S21, using on-site blasting to obtain the initial velocity V of the surrounding rock in the mining area; S22, counting microseismic events in the monitoring area within a certain time interval T, so that the microseismic rays generated by the coal-rock fracture within the interval T can achieve full coverage of the mining area, accurately pick up the arrival time of the effective shock wave signal P wave using the AIC criterion, and use the simplex-double difference joint positioning method to achieve high-precision positioning of the coal-rock fracture source; S23, based on the initial velocity V of the surrounding rock in the mining area obtained in step S21 and step S22 and the absolute arrival time of each microseismic event, the source location and the spatial layout coordinate information of the microseismic sensor, the SIRT algorithm is used to iteratively calculate 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 ν is calculated. c(x,y,z) , the iteration process is as follows: 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, based on the relationship between vibration wave velocity and stress function, the scale stress field σ of the mining area and the mining working face is calculated c(x,y,z) : Where λ and a are mine constant values.

4. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1, characterized in that: In step (3), the tunnel surrounding rock scale stress field σ is obtained m(x,y,z) , including the following steps: S31, statistical analysis of the tunnel surrounding rock, no less than 10 measuring points greater than the 7-day average value of electromagnetic radiation frequency N d With the intensity average 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 measurement point σ h ; S33, based on the positive correlation between the characteristic parameters of electromagnetic radiation signals and 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: 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 characterizes the stress field of tunnel surrounding rock as σ p(x,y,z) The electromagnetic radiation intensity represents the stress field of the tunnel surrounding rock as σ n(x,y,z) ; S34, according to the electromagnetic radiation frequency and intensity, the stress characterization efficiency of coal rock mass is obtained, and the surrounding rock stress field σ of the tunnel is obtained. m(x,y,z) , the expression is as follows: s m(x,y,z) =l1σ p(x,y,z) +l2σ n(x,y,z) Among them, l1 and l2 are the frequency and intensity of electromagnetic radiation in σ m(x,y,z) The weight in .

5. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1, characterized in that: In step (4), the stress monitoring system includes a three-dimensional stress sensor, and the size and direction of the three-dimensional stresses σ1, σ2, and σ3 in the measured area are solved according to the normal stress value, drilling azimuth and inclination of the three-dimensional stress sensor.

6. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1, characterized in that: In step (5), obtaining the multi-scale fusion stress field of the mine includes the following steps: S71, in view of the difference in discrete spacing of stress field data of different scales, the Kriging method is used to grid the stress field data of different scales to achieve the unification of grids of data of different scales; S72, based on the tunnel surrounding rock scale stress field σ m(x,y,z) The data is used as the calibration benchmark for the mine-scale stress field σ k(x,y,z) and the scale stress field of the mining area and the mining face σ c(x,y,z) Regression analysis is performed to calibrate the reference difference of stress fields at different scales, reducing the local gradient stress changes in the data repetition area and boundary area. k(x,y,z) is A , σ c(x,y,z) is B , σ m(x,y,z) is D , the regression equation is as follows: Among them, β0, β1, …, β N is the regression equation parameter, estimated using the least squares method, σ εA and σ εB is the random error term between stress fields of different scales; S73, based on the unified grid in step S71 and the unified benchmark difference in step S72, weighted calculation is performed on stress field data of different scales with the principle of reducing the loss of "small scale, high precision" data to obtain the multi-scale fusion stress field σ o(x,y,z) .

7. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 6 is characterized in that: In step S73, let the mine-scale stress field σ k(x,y,z) The weight is k1, the scale stress field of the mining area and the mining face σ c(x,y,z) The weight is k2, and the tunnel surrounding rock scale stress field σ m(x,y,z) The weight is k3, and k3>k2>k1. Based on this, the stress field σ of different scales is fused. o(x,y,z) The calculation formula is expressed as follows: s o(x,y,z) =k1σ k(x,y,z) +k2σ c(x,y,z) +k3σ m(x,y,z) 。 8. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 1, characterized in that: In step (6), the identification and accurate division of the surrounding rock stress concentration zone in the mining area includes the following steps: S61, according to the surrounding rock failure situation on site, based on the uniaxial compressive strength of coal rock mass and the critical failure stress σ of surrounding rock max , determine the critical stress concentration factor k of coal rock failure max , the expression is as follows: Among them, γ is the average bulk density of coal rock mass, H is the average burial depth of coal rock mass, σ max is the stress value when the coal rock mass is destroyed; S62, divide the stress concentration areas into different levels according to the stress concentration coefficient k.

9. The method for joint monitoring and coupling analysis of multi-scale stress fields in coal mines according to claim 8, characterized in that: In step S62, the division of stress concentration areas of different levels includes: If k is less than 1, the coal-rock mass is in a decompression state; k>1, then the stress state of coal and rock mass in different regions is determined by the following criteria: ①k in (1,0.25k max ] area, the coal-rock mass is in a normal stress state; ②k in (0.25k max ,0.5k max ] area, the coal rock mass is in a weak stress concentration state; ③k in (0.5k max ,0.75k max ] area, the coal-rock mass is in a state of medium stress concentration; ④k in (0.75k max ,k max ) area, the coal rock mass is in a state of strong stress concentration.

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