Experimental Method for the Failure Mechanism of Deep Rock Mass under Mining Disturbance

Abstract

The present invention relates to the technical field of experimental analysis of the deep rock mass fracture mechanism, specifically to an experimental method for the deep rock mass fracture mechanism under mining disturbance, including a uniaxial loading test of deep rock samples based on high-speed photography, a uniaxial loading test of deep rock samples based on acoustic emission monitoring, the focal mechanism and fracture mode of deep rock mass fractures under uniaxial load, four-dimensional imaging of the damage evolution of deep rock masses under mining disturbance, and the construction of an early warning system for the failure and instability of deep rock masses under mining disturbance. By using research methods such as theoretical analysis, laboratory tests, and algorithm development, the present invention conducts research respectively from the evolution of the surface displacement field of the loaded rock mass and the four-dimensional imaging of internal damage, explores the gestation process and visualization of the failure and instability of deep rock masses under mining disturbance, and constructs an early warning system for the failure and instability of deep rock masses under mining disturbance in combination with the evolution of the surface displacement field, the focal mechanism solution of rock mass fractures, and four-dimensional imaging of internal damage.

Description

Technical Field

[0001] The present invention relates to the technical field of experimental analysis of deep rock mass fracture mechanisms, and specifically to an experimental method for the fracture mechanism of deep rock masses under mining disturbances. Background Art

[0002] Deep rock masses serve both as the object of human mining activities and as the object for protecting the support of safe mining. Their internal load-bearing state directly determines the stability of deep engineering projects. Affected by mining disturbances, deep rock masses contain many weak surfaces such as joints and fissures. Some rock masses are in a working condition with uneven stress distribution due to stress concentration, and this state does not satisfy the homogeneity hypothesis of rock masses, further increasing the difficulty of monitoring the damage of deep rock masses under mining disturbances. In addition, the failure and instability of deep rock masses usually stem from the progressive collapse caused by local failures of stress concentration, which is not conducive to the risk warning of deep rock mass engineering. Therefore, considering the inhomogeneity of rock masses, mastering the source mechanism of deep rock mass fractures and the four-dimensional imaging of damage evolution under mining disturbances, and taking timely danger-removing measures are of great significance for the stability of deep rock mass engineering. The fracture mode and damage evolution of deep rock masses are crucial for the stability of the stope. Affected by the inhomogeneity and opacity of rock masses, it is difficult to visualize the internal damage of rock masses under mining disturbances at the engineering site; mastering the damage evolution of stope rock masses affected by mining disturbances in real time is crucial for the disaster prevention and control of deep rock masses.

[0003] Clarifying the fracture mechanism of deep rock masses under mining disturbances is the basis for the four-dimensional imaging of rock mass damage evolution and instability warning; currently, the fracture mechanisms of deep rock masses are mostly based on numerical simulations, theoretical analyses, and laboratory experiments, and cannot adapt to the complex and changeable occurrence environments of deep rock masses. Although there are currently methods such as InSAR and optics for damage monitoring, they all infer the internal fracture mechanism based on the rock mass surface. For the research on the fracture mechanism of deep rock masses under load disturbances, there are few studies starting from within the rock pillar to study the fracture mechanism and fracture mode of rock masses;

[0004] In addition, the four-dimensional imaging of deep rock mass damage evolution is a prerequisite for the instability warning of deep rock masses under mining disturbances; the particularity of deep rock mass media and occurrence environments makes it impossible to directly monitor the damage within the rock mass, and the anisotropy and inhomogeneity of rock masses increase the difficulty of theoretical analysis of fracture instability; currently, the research on the four-dimensional imaging of rock mass damage evolution mainly uses theoretical analysis combined with on-site monitoring or indoor similar model experiments. Its common method is to chart the monitoring data on the rock mass surface or inside it, with low timeliness and it is difficult to achieve the four-dimensional imaging of deep rock mass damage evolution and instability warning under mining disturbances.

[0005] Therefore, we propose an experimental method for the fracture mechanism of deep rock masses under mining disturbances. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention provides an experimental method for the fracture mechanism of deep rock masses under mining disturbances, which is used to solve the above-mentioned technical defects.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: An experimental method for the fracture mechanism of deep rock masses under mining disturbances, comprising the following steps:

[0008] Step 1, acquisition and preparation of specimens: Rock samples are obtained from deep rock masses by in-situ sampling method, ensuring that the rock samples are taken from the same engineering area and have generally the same lithology and mineral composition. 30 cubic specimens (100mm×100mm×100mm) and 120 standard cylindrical rock specimens (Φ50mm×h100mm) are prepared for rock mechanics tests;

[0009] Step 2, determination of basic physical and mechanical property parameters of rocks: Measure the longitudinal wave velocity of deep rock samples, and at the same time conduct XRD tests on the taken rock samples to determine the mineral composition of the rock samples; Conduct triaxial loading tests under different confining pressures to determine the cohesion and internal friction angle of deep rock masses, and determine basic mechanical property parameters such as the shear strength, compressive strength, dynamic compressive strength and dynamic tensile strength of the rock masses;

[0010] Step 3, uniaxial loading test of deep rock samples based on high-speed photography: Conduct uniaxial loading tests on deep rock samples, and at the same time use high-speed photography to capture the process of uniaxial loading of the rock samples, obtain the fracture process on the surface of the rock samples, and use digital image processing technology to obtain the strain field that evolves continuously with the increase of load and its sensitivity to the stress level;

[0011] Step 4, uniaxial loading test of deep rock samples based on acoustic emission monitoring: Conduct uniaxial loading tests on deep rock samples, and at the same time use acoustic emission to monitor the process of uniaxial loading, obtain the stress-strain curve, strength characteristics, wave velocity characteristics and stress-acoustic emission four-parameter diagram during the rock loading process, and at the same time obtain the source location results of acoustic emission events and the original acoustic emission waveforms inside the deep rock samples under the action of load;

[0012] Step 5, source mechanism and fracture mode of deep rock mass fracture under uniaxial load: According to the monitored acoustic emission waveform files of deep rock samples under uniaxial load, perform waveform first arrival correction and acoustic emission event repositioning on the acoustic emission events of the rock samples under load, obtain the source mechanism solution of deep rock masses under load, and determine the fracture mechanism and fracture mode of rock masses at different loading stages;

[0013] Step 6: Four-dimensional imaging of the damage evolution of deep rock mass under mining disturbance: Process the relocated AE waveform data to obtain the seismic catalog of the deep rock mass under load. Improve the double-difference tomography technology to obtain a time-lapse tomography algorithm applicable to small-scale rock masses. Determine the three-dimensional damage evolution within the bedded rock pillar as the load increases. At the same time, perform tomography along the main fracture surface to obtain the process of slip along the main fracture surface and the damage evolution of the deep rock mass under load, and explore the four-dimensional imaging of the entire process of the deep rock mass from being subjected to load disturbance to failure and instability, and master the gestation mechanism of the failure and instability of the deep rock mass;

[0014] Step 7: Construct an early warning system for the failure and instability of deep rock mass under mining disturbance: Based on the mechanical characteristics, strain field evolution, source mechanism of fractures, four-dimensional imaging of internal damage, and gestation mechanism of failure and instability of deeply buried rock samples under uniaxial load, combined with geological mechanics parameters and basic physical and mechanical property parameters of rock masses, etc., explore the indicators and weights of the failure and instability of deep rock mass under mining disturbance, and construct an early warning system for the failure and instability of deep rock mass.

[0015] Preferably, in Step 2, by obtaining the maximum principal stress at the failure of rock samples under different confining pressures, according to the Mohr-Coulomb strength criterion, the internal friction angle corresponding to the maximum principal stress at the failure of rock samples under different confining pressures is calculated according to the formula: NM = arctan[(σ1 - σ2) / (σ1 + σ2)], where σ1 represents different confining pressures and σ2 represents the maximum principal stress. The cohesion corresponding to the maximum principal stress at the failure of rock samples under different confining pressures is calculated according to the formula NJ = (σ1 - σ2) / 2 - (σ1 + σ2) / 2 × sin NM;

[0016] By obtaining the maximum axial load at the failure of rock samples in the uniaxial compression test, denoted as P, and at the same time obtaining the cross-sectional area of the rock samples, denoted as A, the compressive strength of the rock samples is calculated according to the formula KY = P / A;

[0017] By obtaining the strain rate of rock samples in the dynamic loading test, denoted as ε, the dynamic compressive strength of the rock samples is calculated according to the formula KYd = a × ε b where a and b are coefficients obtained by fitting the test data;

[0018] By obtaining the load at the failure of rock samples in the dynamic splitting test, denoted as P, and at the same time obtaining the diameter and thickness of the disk-shaped rock samples, denoted as D and h respectively, the dynamic tensile strength of the rock samples is calculated according to the formula KLd = 2P / (πDh).

[0019] Preferably, by obtaining the internal friction angle, cohesion, and compressive strength of rock samples corresponding to each test period, the internal friction angle, cohesion, and compressive strength of rock samples corresponding to each test period are obtained, denoted as NM i , NJ i and KYi , where \(i\) represents the number of each test period;

[0020] Meanwhile, obtain the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample, and denote the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample as \(NM0\), \(NJ0\) and \(KY0\) respectively;

[0021] According to the formula:

[0022]

[0023] Calculate the comprehensive quality evaluation coefficient \(C\) of the rock sample corresponding to each test period. \(w1\), \(w2\) and \(w3\) represent the weight factors corresponding to the internal friction angle, cohesion and compressive strength respectively, and \(w1 + w2 + w3 = 1\). Specifically, \(w1 = 0.35\), \(w2 = 0.45\), \(w3 = 0.2\);

[0024] Obtain the comprehensive quality evaluation coefficient of the rock sample corresponding to the initial test period, denoted as \(C1\). After a period of time \(t\), obtain the comprehensive quality evaluation coefficient of the rock sample corresponding to the test period again, denoted as \(C2\). Compare the comprehensive quality evaluation coefficient of the rock sample corresponding to the test period after a period of time \(t\) with the comprehensive quality evaluation coefficient of the rock sample corresponding to the initial test period. If \(C2\) is less than \(C1\), it means that the overall mechanical properties of the rock sample have declined. Plot a line graph of the comprehensive quality evaluation coefficient of the rock sample corresponding to each test period for display, and visually represent the decline amplitude of the overall mechanical properties of the rock sample in each test period according to the line graph of the comprehensive quality evaluation coefficient of the rock sample corresponding to each test period. If the continuous decline amplitude of the comprehensive quality evaluation coefficient exceeds 12% within a short period of time, it indicates that the process of weathering and deterioration of the rock sample has accelerated. If the decline amplitude of the comprehensive quality evaluation coefficient is lower than 8%, it indicates that the process of weathering and deterioration of the rock sample is relatively slow.

[0025] Preferably, according to the acoustic emission signal characteristics and high-speed camera technology of the deep rock mass under load, construct the spatio-temporal evolution of rock mass fracture under load, explore the focal mechanism solutions in the rock mass under different stress levels, and master the fracture mode, fracture mechanism and strain field evolution of the rock mass under different stress levels.

[0026] Preferably, by selecting in-situ sampling of target deep rock masses and conducting uniaxial loading tests on deep rock samples based on high-speed photography and acoustic emission monitoring in the laboratory, the strain field evolution and failure instability characteristics of deep rock masses under mining disturbances are studied, the mechanical characteristics of deep rock masses and the quantitative relationship between the evolution of the surface strain field and the stress level are explored, the focal mechanism of deep rock samples under load is analyzed, the fracture modes and focal mechanism solutions of deep rock masses under different disturbance degrees are mastered, the relationships among the instability law, fracture mode, focal mechanism solution, strain field evolution and stress level of deep rock masses are constructed, and the fracture mode and focal mechanism solution of deep rock masses under mining disturbances are mastered, laying a foundation for four-dimensional imaging of deep rock mass damage evolution and instability warning.

[0027] Preferably, by obtaining four-dimensional imaging of damage in deep rock masses under disturbances at different stress levels, the mechanism of failure and instability of deep rock masses under load disturbances is obtained.

[0028] Preferably, based on the fracture process of deep rock samples under load monitored by acoustic emission, the triple-difference method is used to locate the fracture points in the rock pillar, and the spatio-temporal evolution of fractures and the magnitude of acoustic emission energy in the loaded rock mass are mastered. The four-dimensional imaging technology of time-lapse imaging is developed by improving double-difference tomography, the three-dimensional visualization of damage in rock masses at different loading stages is carried out, the damage evolution and instability mechanism in deep rock masses are explored, and the sliding process of rock mass fracture along the main fissure under load is visualized.

[0029] Preferably, a failure and instability warning system is constructed by coordinating multiple means such as strain field, four-dimensional imaging of internal damage evolution of deep rock masses, and focal mechanism solutions of deep rock mass fractures.

[0030] Preferably, based on the actual working conditions of deep rock masses, combined with rock mass geomechanical parameters, mechanical characteristics, strain field evolution and four-dimensional imaging of damage during the loading process, etc., the mechanism of failure and instability of deep rock masses under mining disturbances is analyzed. The relationship between the evolution of the surface strain field of deep rock masses under load disturbances and the four-dimensional imaging of internal damage and the stress level is quantified, and the process of failure and instability of deep rock masses under load disturbances is visualized. At the same time, based on the mechanical mechanism, damage evolution and focal mechanism solution of rock mass fracture under load, the precursor characteristics before rock mass fracture and instability are mastered, and the warning criterion for failure and instability of deep rock masses under mining disturbances is constructed.

[0031] Preferably, based on four-dimensional imaging under load using waveform cross-correlation, by studying the source locations of acoustic emission events in bedded rock samples under uniaxial load and performing near-real-time imaging continuously in three-dimensional space with time as one dimension, the fracture characteristics and spatio-temporal evolution of damage in the bedded rock pillar over time are mastered.

[0032] Compared with the prior art, the following beneficial effects are achieved:

[0033] 1. In the present invention, research methods such as theoretical analysis, laboratory tests, and algorithm development are adopted to conduct research respectively from the evolution of the surface displacement field of the loaded rock mass and the four-dimensional imaging of internal damage, explore the gestation process and visualization of the failure and instability of deep rock masses under mining disturbances, and combine the evolution of the surface displacement field, the focal mechanism solutions of rock mass fractures, and the four-dimensional imaging of internal damage, etc., to construct an early warning system for the failure and instability of deep rock masses under mining disturbances. Therefore, the present invention adopts a method combining multiple means and multiple factors to study the focal mechanism of deep rock mass fractures and the four-dimensional imaging of damage evolution under mining disturbances, provides theoretical and technical references for the stability monitoring and danger elimination of rock masses under complex occurrence conditions in deep mines, constructs an early warning system for failure and instability coordinated by multiple means such as strain fields, four-dimensional imaging of internal damage of rock masses, and focal mechanism solutions of rock mass fractures, masters the visualization of internal damage of deep rock masses and the clarification of the focal mechanism of fractures under mining disturbances, and provides early warning references for the failure and instability of deep rock masses.

[0034] 2. In the present invention, the internal friction angle, cohesion, and compressive strength of the rock sample corresponding to each test period are obtained through real-time monitoring, and at the same time, the initial internal friction angle, initial cohesion, and initial compressive strength of the rock sample are obtained. The initial internal friction angle, initial cohesion, and initial compressive strength of the rock sample are obtained, and the monitoring data of each test period and the corresponding initial monitoring data are comprehensively calculated to generate a comprehensive quality evaluation coefficient for the rock sample corresponding to each test period. By statistically comparing the comprehensive quality evaluation coefficient of the rock sample corresponding to each test period with that of the initial test period, the weathering and deterioration processes of the rock sample in each test period can be intuitively represented, providing accurate results of the overall mechanical properties of the rock sample for the experiment on the rock mass fracture mechanism.

[0035] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures pointed out in the specification and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is the flow chart of the method of the present invention;

[0037] Figure 2 is the schematic diagram of event pairs, station pairs, and double pairs in the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Example 1:

[0040] Please refer to Figures 1 to 2 as shown in the figure, the test method for the deep rock mass fracture mechanism under mining disturbance includes the following steps:

[0041] Step 1. Acquisition and preparation of specimens: Rock samples are obtained from deep rock masses by in-situ sampling method, ensuring that the rock samples are taken from the same engineering area with generally consistent lithology and mineral composition. Prepare 30 cubic specimens (100mm×100mm×100mm) and 120 standard cylindrical rock specimens (Φ50mm×h100mm), and conduct rock mechanics tests;

[0042] Step 2. Determination of basic physical and mechanical property parameters of rocks: Measure the longitudinal wave velocity of deep rock samples, and at the same time conduct XRD tests on the taken rock samples to determine the mineral composition of the rock samples; Conduct triaxial loading tests under different confining pressures to determine the cohesion and internal friction angle of deep rock masses, and determine basic mechanical property parameters such as the shear strength, compressive strength, dynamic compressive strength, and dynamic tensile strength of the rock masses;

[0043] Specifically: By obtaining the maximum principal stress at the time of rock sample failure under different confining pressures, according to the Mohr-Coulomb strength criterion, based on the formula: NM = arctan[(σ1 - σ2) / (σ1 + σ2)], calculate the internal friction angle corresponding to the maximum principal stress at the time of rock sample failure under different confining pressures, where σ1 represents different confining pressures and σ2 represents the maximum principal stress. According to the formula NJ = (σ1 - σ2) / 2 - (σ1 + σ2) / 2×sinNM, calculate the cohesion corresponding to the maximum principal stress at the time of rock sample failure under different confining pressures;

[0044] By obtaining the maximum axial load at the time of rock sample failure in the uniaxial compression test, denoted as P, and at the same time obtaining the cross-sectional area of the rock sample, denoted as A, calculate the compressive strength of the rock sample according to the formula KY = P / A;

[0045] By obtaining the strain rate of the rock sample in the dynamic loading test, denoted as ε, calculate the dynamic compressive strength of the rock sample according to the formula KYd = a×ε b where a and b are coefficients obtained by fitting test data;

[0046] By obtaining the load at the time of rock sample failure in the dynamic splitting test, denoted as P, and simultaneously obtaining the diameter and thickness of the disc-shaped rock sample, denoted as D and h respectively, the dynamic tensile strength of the rock sample is calculated according to the formula KLd = 2P / (πDh). Specifically, for a disc-shaped rock sample with a diameter of 50 mm and a thickness of 25 mm, if the load at failure in the dynamic splitting test is 10 kN, then its dynamic tensile strength is calculated as: σtd = 2×10000 / (π×0.05×0.025) ≈ 509299 Pa ≈ 509.3 MPa.

[0047] Step 3: Uniaxial loading test of deep rock samples based on high-speed photography: Conduct a uniaxial loading test on deep rock samples, and simultaneously use high-speed photography to capture the process of uniaxial loading of the rock samples, obtain the fracture process on the surface of the rock samples, and use digital image processing technology to obtain the strain field that evolves continuously with the increase of load and its sensitivity to the stress level.

[0048] Step 4: Uniaxial loading test of deep rock samples based on acoustic emission monitoring: Conduct a uniaxial loading test on deep rock samples, and simultaneously use acoustic emission to monitor the process of uniaxial loading, obtain the stress-strain curve, strength characteristics, wave velocity characteristics, and stress-acoustic emission four-parameter diagram during the rock loading process, and simultaneously obtain the source location results of acoustic emission events and the original acoustic emission waveforms inside the deep rock samples under the action of load.

[0049] Step 5: Source mechanism and fracture mode of deep rock mass fracture under uniaxial load: According to the acoustic emission waveform file of deep rock samples under uniaxial load monitoring, perform waveform first arrival correction and acoustic emission event repositioning on the acoustic emission events of the rock samples under load, obtain the source mechanism solution of the deep rock mass under load, and determine the fracture mechanism and fracture mode of the rock mass at different loading stages.

[0050] It should be noted that according to the acoustic emission signal characteristics and high-speed photography technology of the loaded deep rock mass, construct the spatio-temporal evolution of rock mass fracture under load, explore the source mechanism solutions inside the rock mass at different stress levels, and master the fracture mode, fracture mechanism, and strain field evolution of the rock mass at different stress levels.

[0051] Specifically: By selecting in-situ sampling of target deep rock masses, conducting uniaxial loading tests on deep rock samples based on high-speed photography and acoustic emission monitoring in the laboratory, studying the strain field evolution and failure instability characteristics of deep rock masses under mining disturbances, exploring the quantitative relationship between the mechanical characteristics and surface strain field evolution of deep rock masses and stress levels, analyzing the focal mechanism of deep rock samples under load, mastering the fracture modes and focal mechanism solutions of deep rock masses under different disturbance degrees, constructing the relationship between the instability law, fracture mode, focal mechanism solution, strain field evolution and stress level of deep rock masses, and mastering the fracture mode and focal mechanism solution of deep rock masses under mining disturbances, laying a foundation for four-dimensional imaging and instability warning of deep rock mass damage evolution.

[0052] Step 6: Four-dimensional imaging of deep rock mass damage evolution under mining disturbances: Process the relocated acoustic emission waveform data to obtain the seismic catalog of deep rock masses under load, improve the double-difference tomography technology to obtain a time-lapse tomography algorithm applicable to small-scale rock masses, determine the three-dimensional damage evolution in the bedding rock pillar as the load increases, and at the same time perform tomography along the main fracture surface to obtain the process of slip along the main fracture surface and damage evolution of deep rock masses under load, explore the four-dimensional imaging of the whole process of deep rock masses from being loaded and disturbed to failure and instability, and master the breeding mechanism of deep rock mass failure and instability;

[0053] It should be noted that by obtaining the four-dimensional imaging of damage in deep rock masses under disturbances at different stress levels, the mechanism of deep rock mass failure and instability under load disturbances is obtained;

[0054] Specifically: Based on the fracture process of deep rock samples under load monitored by acoustic emission, use triple-difference positioning to locate the fracture points in the rock pillar, and master the spatio-temporal evolution of fractures and the magnitude of acoustic emission energy in the loaded rock mass. Improve the double-difference tomography to develop a four-dimensional imaging technology for time-lapse imaging, visualize the three-dimensional damage of rock masses at different bearing stages, explore the damage evolution and instability mechanism in deep rock masses, and visualize the slip process of rock mass fractures along the main fracture under load.

[0055] Step 7: Construct an early warning system for deep rock mass failure and instability under mining disturbances: According to the mechanical characteristics, strain field evolution, focal mechanism of fractures, four-dimensional imaging of internal damage and the breeding mechanism of failure and instability of deep buried rock samples under uniaxial load, combined with geological mechanics parameters and basic physical and mechanical property parameters of rock masses, etc., explore the indicators and weights of deep rock mass failure and instability under mining disturbances, and construct an early warning system for deep rock mass failure and instability.

[0056] It should be noted that by constructing an early warning system for failure and instability that coordinates multiple means such as the strain field, four-dimensional imaging of deep rock mass internal damage evolution, and focal mechanism solutions of deep rock mass fractures;

[0057] Specifically: Based on the actual working conditions of deep rock masses, combined with rock mass geomechanical parameters, mechanical characteristics, four-dimensional imaging of strain field evolution and damage during the loading process, etc., analyze the mechanism of failure and instability of deep rock masses under mining disturbances. Quantify the relationship between the evolution of the surface strain field of deep rock masses under loading disturbances, four-dimensional imaging of internal damage, and the stress level, visualize the process of failure and instability of deep rock masses under load disturbances. At the same time, based on the mechanical mechanism of deep rock masses under load, damage evolution, and focal mechanism solutions of fractures, master the precursor characteristics before rock mass fracture and instability, and construct an early warning criterion for the failure and instability of deep rock masses under mining disturbances.

[0058] In a specific embodiment, in the present invention, research methods such as theoretical analysis, laboratory tests, and algorithm development are adopted to conduct research respectively from the evolution of the surface displacement field of the loaded rock mass and four-dimensional imaging of internal damage, explore the gestation process and visualization of the failure and instability of deep rock masses under mining disturbances, and combine the evolution of the surface displacement field, focal mechanism solutions of rock mass fractures, four-dimensional imaging of internal damage, etc. to construct an early warning system for the failure and instability of deep rock masses under mining disturbances. Therefore, the present invention adopts a method combining multiple means and multiple factors to study the focal mechanism and four-dimensional imaging of damage evolution of deep rock mass fractures under mining disturbances, provides theoretical and technical references for the stability monitoring and hazard elimination of rock masses under complex occurrence conditions in deep mines, constructs an early warning system for failure and instability coordinated by multiple means such as strain field, four-dimensional imaging of internal damage of rock masses, and focal mechanism solutions of rock mass fractures, masters the visualization of internal damage of deep rock masses and the clarification of the focal mechanism of fractures under mining disturbances, and provides an early warning reference for the failure and instability of deep rock masses.

[0059] Furthermore, for the relocation of acoustic emission events in deep rock masses, by combining the double-difference location method of the existing technology and the station pair double-difference location method to generate a triple-difference seismic location method, while improving the absolute and relative positions of earthquakes, the location accuracy of weak seismic events is improved;

[0060] Among them, the double-difference location method utilizes the first arrival time difference data of event pairs to the same station. This arrival time difference data can be constructed from the absolute arrival time data in the earthquake catalog or extracted using waveform cross-correlation technology; the main advantages of this method are: (1) The arrival time difference data of event pairs can eliminate the influence of velocity model errors on location along similar ray paths outside the source area; (2) High-precision waveform cross-correlation arrival time difference data can greatly improve the relative positions of corresponding events, and the relative positions of event pairs without waveform similarity can be located using the arrival time difference data in the earthquake catalog;

[0061] The station pair double-difference location method means that the travel time difference data of the same seismic event to two stations can also be used for location; therefore, the double pair data refers to the arrival time difference of an earthquake pair to a station pair.

[0062] In Figure 2Figure (a) shows a schematic diagram of event pairs, (b) shows a schematic diagram of station pairs, (c) shows a schematic diagram of double pairs, (d) shows a flowchart for constructing three different time difference data, and the gray shading represents the area near or outside the source area.

[0063] Furthermore, for four-dimensional imaging under load based on waveform cross-correlation, by studying the source locations of acoustic emission events in laminated rock samples under uniaxial load and performing near-real-time imaging continuously in three-dimensional space with time as one dimension, the fracture characteristics and spatio-temporal evolution of damage within the laminated rock column over time can be grasped. This method is developed based on traditional double-difference seismic tomography and can more reliably determine the temporal variation of the velocity of the laminated rock column.

[0064] The traditional double-difference seismic tomography algorithm is represented by the following equation:

[0065]

[0066] In the formula, represents the travel-time residual from seismic event m to station s, Δτ m is the onset time of the source m, μ is the ray slowness field vector, is the difference in travel-time residuals, represents the perturbation of the seismic location, p = 1, 2, 3; δμ represents the slowness perturbation;

[0067] In the traditional double-difference seismic tomography algorithm, the two seismic events that form an event pair are not far apart and are received by a sufficient number of stations. These requirements are relatively high for the data, and there is room for further improvement in the inversion accuracy. In time-lapse tomography based on waveform cross-correlation, in order to invert the velocity change between two time periods, the two events that form an event pair come from different time periods, as shown in the following formula:

[0068]

[0069] Compared with the traditional double-difference seismic tomography (Equation (2)), the biggest difference in Equation (3) lies in that the slowness perturbations δμ1 and δμ2 for time period 1 and time period 2 are different, that is, the two events m and n that form an event pair come from different time periods. It can be seen that the main difference between the two imaging methods is that time-lapse tomography directly inverses the velocity change using travel-time difference data, while the traditional method only subtracts the velocity models obtained from two different time periods. Therefore, time-lapse tomography can greatly reduce the error caused by different data distributions.

[0070] In the field of four-dimensional imaging of damage evolution and failure instability warning of deep rock masses, the acoustic emission source data set and location are updated in real time through acoustic emission signals continuously triggered as the load disturbance increases, and the velocity structure imaging in the deep rock mass under load disturbance is continuously updated by time-lapse tomography.

[0071] Example 2:

[0072] On the basis of Example 1, the internal friction angle, cohesion, and compressive strength of the rock sample corresponding to each test period are obtained, and the internal friction angle, cohesion, and compressive strength of the rock sample corresponding to each test period are obtained, which are respectively denoted as NM i , NJ i and KY i , where i represents the number of each test period;

[0073] At the same time, the initial internal friction angle, initial cohesion, and initial compressive strength of the rock sample are obtained, and the initial internal friction angle, initial cohesion, and initial compressive strength of the rock sample are obtained, which are respectively denoted as NM0, NJ0, and KY0;

[0074] According to the formula:

[0075]

[0076] The comprehensive quality evaluation coefficient C of the rock sample corresponding to each test period is calculated. w1, w2, and w3 respectively represent the weight factors corresponding to the internal friction angle, cohesion, and compressive strength, and w1 + w2 + w3 = 1, and its magnitude is set customarily. Specifically, for example: w1 = 0.35, w2 = 0.45, w3 = 0.2.

[0077] The comprehensive quality evaluation coefficient corresponding to the initial test period of the rock sample is obtained, denoted as C1. After a period of time t, the comprehensive quality evaluation coefficient corresponding to the test period of the rock sample is obtained again, denoted as C2. The comprehensive quality evaluation coefficient of the rock sample corresponding to the test period after a period of time t is compared with the comprehensive quality evaluation coefficient corresponding to the initial test period of the rock sample. If C2 is less than C1, it means that the overall mechanical properties of the rock sample have declined. The comprehensive quality evaluation coefficients corresponding to each test period of the rock sample are plotted as a line graph for display, and the decline amplitude of the overall mechanical properties of the rock sample in each test period is visually represented according to the line graph of the comprehensive quality evaluation coefficients corresponding to each test period of the rock sample. If the continuous decline amplitude of the comprehensive quality evaluation coefficient exceeds 12% within a short period of time, it indicates that the process of weathering and deterioration of the rock sample has accelerated. If the decline amplitude of the comprehensive quality evaluation coefficient is lower than 8%, it indicates that the process of weathering and deterioration of the rock sample is relatively slow.

[0078] Specifically, the initial compressive strength is 100 MPa, the internal friction angle is 30°, and the cohesion is 20 MPa. Through formula calculation, the comprehensive coefficient C1 = 80 is obtained. After a period of time t, due to weathering, the compressive strength is reduced to 80 MPa, the internal friction angle is reduced to 25°, and the cohesion is reduced to 15 MPa. By recalculating, the comprehensive coefficient C2 = 60 is obtained. Since 60 < 80, it can be judged that the rock sample has undergone obvious weathering and deterioration during this period.

[0079] In a specific embodiment, in the present invention, the internal friction angle, cohesion, and compressive strength of the rock sample corresponding to each test period are obtained through real-time monitoring, and at the same time, the initial internal friction angle, initial cohesion, and initial compressive strength of the rock sample are obtained. By comprehensively calculating the monitoring data of each test period and the corresponding initial monitoring data, a comprehensive quality evaluation coefficient of the rock sample corresponding to each test period is generated. By statistically comparing the comprehensive quality evaluation coefficient of the rock sample corresponding to each test period with that of the initial test period, the weathering and deterioration process of the rock sample in each test period can be intuitively represented, providing accurate results of the overall mechanical properties of the rock sample for the experiment on the rock mass fracture mechanism.

[0080] Example 3:

[0081] On the basis of Example 1, a uniaxial loading test is carried out on the deep rock sample, and at the same time, high-speed photography is used to capture the process of uniaxial loading of the rock sample. Specifically:

[0082] Data of the surface and side of the specimen are collected to obtain surface data and side data, and they are sent to the server. The server sends the surface data and side data to the data processing end. The data processing end processes the surface data and side data to obtain the non-smooth value and the non-vertical value of the side, and feeds them back to the server; among them, the surface data includes the surface scanning data of the specimen, and the side data is the side scanning data of the specimen.

[0083] The server compares the roughness value and the side droop value with the corresponding thresholds respectively. If the roughness value is greater than or equal to the corresponding roughness threshold or the side droop value is greater than or equal to the corresponding droop threshold, a sample failure instruction is generated and sent to the corresponding intelligent terminal for display. When the roughness value and the side droop value are both less than the corresponding roughness threshold and droop threshold, environmental data of the high-speed camera is collected, where the environmental data includes temperature, humidity and light intensity. Environmental standard data is set, including a temperature standard range, a humidity standard range and a light intensity standard range. The collected environmental data is compared with the standard data. If the collected temperature does not fall within the temperature standard range, the humidity does not fall within the humidity standard range or the light intensity does not fall within the light intensity standard range, a temperature adjustment instruction, a humidity adjustment instruction or a light intensity adjustment instruction is generated. The server sends the temperature adjustment instruction, the humidity adjustment instruction or the light intensity adjustment instruction to the corresponding intelligent terminal. The control terminal controls the corresponding temperature control equipment, the humidity control equipment and the lighting equipment to ensure that the environmental data of the high-speed camera is within the corresponding environmental standard data, so as to improve the clarity of the high-speed camera and avoid image blur or shadows that affect the accurate judgment of rock sample changes.

[0084] The data processing terminal is a computer device that communicates with the server and is authorized or has data processing capabilities; and has a built-in sample processing program;

[0085] The specific operation method of the sample processing program includes the following steps:

[0086] The surface scanning data of the sample is analyzed to obtain the distance values of several collection points on the sample surface from the scanning point, the distance values of the same surface are obtained, the number of times the same size distance value appears is counted, the distance value with the most number of times is marked as the majority value, all the distance values of the same surface are compared with the majority value, if the two are inconsistent, the distance value is marked as the outlier value; the number of outliers is counted to obtain the number of outliers; the position of the outlier value is obtained, the position of the two adjacent outliers is connected to obtain the outlier spacing, all the outlier spacings are compared with the spacing threshold, the outlier spacing that is less than the spacing threshold is marked as outlier spacing, and the outlier spacing that is greater than or equal to the spacing threshold is marked as outlier spacing; the outlier number, outlier spacing, and outlier spacing are normalized and their values are taken, and substituted into the non-slip analysis model to output the non-slip value; the non-slip analysis model is BH represents the non-slip value of a single surface, Yz is the number of different numbers, L j1 is a different spacing, j1 is the number of the different spacing, j1=1,2,……,n1; L j2Let \(j_1\) be the different first spacing, \(j_2\) be the number of the different second spacing, and \(j_2 = 1, 2,\cdots, n_2\); \(LL_j\) is the average value corresponding to all different first spacings and different second spacings; \(\lambda_1\), \(\lambda_2\), \(\lambda_3\), \(\lambda_4\) are all preset weight factors, and \(\lambda_1>\lambda_3>\lambda_2>\lambda_4 > 0.5\); \(\eta_{z1}\), \(\eta_{z2}\) are the quantity thresholds corresponding to the different mode quantity, and \(\eta_{z1}>\eta_{z2}>0\). The sum of the non-slip values of all surfaces of the specimen is obtained to get the non-smooth value.

[0087] Analyze the side data of the specimen to obtain the distances from several acquisition points on the side to the scanning electron microscope. Divide several acquisition points on the side into several columns in the vertical direction, calculate the average value of the distance values of each column of acquisition points to obtain the anomaly value. Compare the distance values of all acquisition points with the average value. If the two are inconsistent, calculate the difference between the two to obtain the anomaly difference value. Sum all the anomaly difference values to obtain the total anomaly value of each column; Sum the total anomaly values of all columns and multiply by the corresponding preset conversion factor to obtain the side non-vertical value.

[0088] By analyzing the surface data and side data of the specimen, the non-smooth value and the side non-vertical value are obtained. The size parameters of the specimen are judged by the non-smooth value and the side non-vertical value, so as to avoid unqualified specimens from affecting the stress distribution and deformation mode during the loading process, thereby affecting the image features captured by the camera. Through detailed scanning data analysis and different mode value analysis, the minute changes on the surface of the specimen can be accurately captured, improving the accuracy of the analysis. Not only the non-smoothness of the specimen surface is considered, but also the perpendicularity of the specimen is evaluated through side data analysis, providing a comprehensive evaluation of the specimen quality. The preset weight factors and quantity thresholds of the present invention can be adjusted according to different specimen types and requirements, increasing the flexibility and applicability of the method. Through the non-slip value and the side non-vertical value output by the model, the surface quality and perpendicularity of the specimen can be intuitively understood.

[0089] At the same time, the content not described in detail in this specification belongs to the prior art well known to those skilled in the art.

[0090] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Experimental method for the fracture mechanism of deep rock mass under mining disturbance, characterized in that, Including the following steps: Step 1: Acquisition and preparation of specimens; Step 2: Determination of basic physical and mechanical property parameters of rocks; The process of determining the basic physical and mechanical property parameters of rocks is as follows: measure the longitudinal wave velocity of deep rock samples, and at the same time determine the mineral composition of the taken rock samples through tests; determine the basic mechanical property parameters of the rock mass through triaxial loading tests under different confining pressures, where the basic mechanical property parameters include cohesion, internal friction angle, shear strength, compressive strength, as well as dynamic compressive strength and dynamic tensile strength; Let the angle of internal friction, cohesion and compressive strength be denoted as NM i , NJ i and KY i , where i represents the number of each test period; According to the formula: Calculate the comprehensive quality evaluation coefficient C of the rock sample corresponding to each test period, NM0, NJ0 and KY0 are the initial angle of internal friction, initial cohesion and initial compressive strength, and w1, w2 and w3 respectively represent the weight factors corresponding to the angle of internal friction, cohesion and compressive strength; Compare the comprehensive quality evaluation coefficient C1 of the rock sample corresponding to a certain period of time with the comprehensive quality evaluation coefficient C2 of the rock sample corresponding to the initial test period. If C2 < C1, then plot the comprehensive quality evaluation coefficients of the rock sample corresponding to each test period as a line graph for display, and calculate the decline amplitude; Step 3: Uniaxial loading test of deep rock samples based on high-speed photography; The specific process of the uniaxial loading test of deep rock samples based on high-speed photography is as follows: conduct a uniaxial loading test on deep rock samples, and at the same time use high-speed photography to capture the process of uniaxial loading of the rock samples, obtain the fracture process on the surface of the rock samples, and use digital image processing technology to obtain the strain field evolving with the increase of load and its sensitivity to the stress level; Step 4: Uniaxial loading test of deep rock samples based on acoustic emission monitoring; The specific process of the uniaxial loading test of deep rock samples based on acoustic emission monitoring is as follows: conduct a uniaxial loading test on deep rock samples, and at the same time use acoustic emission to monitor the uniaxial loading process, obtain the stress-strain curve, strength characteristics, wave velocity characteristics, and stress-acoustic emission four-parameter diagram during the rock loading process, and at the same time obtain the source location results of acoustic emission events and the original acoustic emission waveforms inside the deep rock samples under the action of load; Step 5: Source mechanism and fracture mode of deep rock mass fracture under uniaxial load; The specific process of the source mechanism and fracture mode of deep rock mass fracture under uniaxial load is as follows: according to the monitored acoustic emission waveform file of deep rock samples under uniaxial load, perform waveform first arrival correction and acoustic emission event repositioning on the acoustic emission events of the rock samples under load, obtain the source mechanism solution of the deep rock mass under load, and determine the fracture mechanism and fracture mode of the rock mass at different loading stages; Step 6: Four-dimensional imaging of damage evolution of deep rock mass under mining disturbance; The specific process of the four-dimensional imaging of damage evolution of deep rock mass under mining disturbance is as follows: process the repositioned acoustic emission waveform data to obtain the seismic catalog of the deep rock mass under load, improve the double-difference tomography technology to obtain a time-lapse tomography algorithm applicable to small-scale rock masses, determine the three-dimensional damage evolution in the bedded rock pillar with the increase of load, and at the same time perform tomography along the main fracture surface to obtain the process of slip along the main fracture surface and damage evolution of the deep rock mass under load, monitor the four-dimensional imaging of the whole process of the deep rock mass from being loaded and disturbed to failure and instability, and obtain the breeding mechanism of the failure and instability of the deep rock mass; Step 7: Construct an early warning system for the failure and instability of deep rock mass under mining disturbance.

2. The test method for the deep rock mass fracture mechanism under mining disturbance according to claim 1, characterized in that: In Step 1, the specific process of obtaining and preparing the specimens is as follows: obtain rock samples from deep rock masses, prepare several cubic specimens and standard cylindrical specimens, and then conduct rock mechanics tests.

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