Test method for deep rock mass fracture mechanism under excavation disturbance

Abstract

The invention relates to the technical field of deep rock mass fracture mechanism test analysis, in particular to a test method for a deep rock mass fracture mechanism under excavation disturbance. Comprising a deep rock sample uniaxial loading test based on high-speed camera shooting, a deep rock sample uniaxial loading test based on acoustic emission monitoring, a seismic source mechanism and a fracture mode of deep rock mass fracture under the action of a uniaxial load, four-dimensional imaging of deep rock mass damage evolution under excavation disturbance and construction of an early warning system of deep rock mass damage instability under excavation disturbance. According to the method, research methods such as theoretical analysis, indoor test and algorithm development are adopted, research is carried out from surface displacement field evolution and internal damage four-dimensional imaging of the loaded rock mass, and the inoculation process of deep rock mass damage instability under excavation disturbance and visualization of the inoculation process are explored; and in combination with surface displacement field evolution, a seismic source mechanism solution of rock mass fracture, internal damage four-dimensional imaging and the like, a deep rock mass damage instability early warning system under excavation disturbance is constructed.

Description

Technical Field

[0001] The invention relates to the technical field of deep rock mass fracture mechanism test analysis, in particular to a test method for deep rock mass fracture mechanism under mining disturbance. Background Art

[0002] Deep rock mass is not only the object of human mining, but also the object of protection and support for safe mining. Its internal bearing state directly determines the stability of deep engineering. Affected by mining disturbance, deep rock mass contains many weak surfaces such as joints and fissures. Some rock masses are affected by stress concentration and are in a state of uneven stress distribution. This state does not meet the uniformity hypothesis of rock mass, further increasing the difficulty of deep rock mass damage monitoring under mining disturbance. In addition, the destructive instability of deep rock mass usually originates from the progressive collapse caused by local damage due to stress concentration, which is not conducive to the early warning of the danger of deep rock mass engineering. Therefore, considering the heterogeneity of the rock mass, mastering the source mechanism of deep rock mass rupture under mining disturbance and four-dimensional imaging of damage evolution, and taking timely emergency measures are of great significance to the stability of deep rock mass engineering. The rupture mode and damage evolution of deep rock mass are crucial to the stability of the mining site. Affected by the heterogeneity and opacity of the rock mass, it is difficult to realize the visualization of internal damage of the rock mass under mining disturbance at the engineering site; real-time grasp of the damage evolution of the rock mass in the mining site affected by mining disturbance is crucial to disaster prevention and control of deep rock mass.

[0003] Clarifying the fracture mechanism of deep rock mass under mining disturbance is the basis for four-dimensional imaging of rock mass damage evolution and instability warning. At present, the fracture mechanism of deep rock mass is mostly based on numerical simulation, theoretical analysis and indoor experiments, which cannot adapt to the complex and changeable deep environment. Although there are methods such as Insar and optics for damage monitoring, they are all based on the surface of the rock mass to infer its internal fracture mechanism. For the study of the fracture mechanism of deep rock mass under load disturbance, there are few studies on the fracture mechanism and fracture mode of rock mass from the inside of the rock column.

[0004] In addition, four-dimensional imaging of deep rock damage evolution is a prerequisite for early warning of deep rock instability under mining disturbance. The particularity of deep rock medium and occurrence environment makes it impossible to monitor the damage inside the rock mass intuitively, and the anisotropy and heterogeneity of the rock mass increase the difficulty of theoretical analysis of fracture instability. At present, the research on four-dimensional imaging of rock damage evolution mainly adopts theoretical analysis combined with field monitoring or indoor similar model experiments. The commonly used method is to graph the monitoring data on the surface of the rock mass or its interior, which has low timeliness and makes it difficult to achieve four-dimensional imaging and instability early warning of deep rock damage evolution under mining disturbance.

[0005] To this end, we proposed an experimental method for the fracture mechanism of deep rock mass under mining disturbance. Summary of the invention

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

[0007] To achieve the above purpose, the present invention is implemented by the following technical scheme: A test method for the fracture mechanism of deep rock mass under mining disturbance comprises the following steps:

[0008] Step 1. Sample acquisition and preparation: Use the in-situ sampling method to obtain rock samples from deep rock mass, ensure that the rock samples are taken from the same project area, and the lithology and mineral composition are roughly consistent. Prepare 30 cubic samples (100mm×100mm×100mm) and 120 cylindrical rock standard cylindrical samples (Φ50mm×h100mm) for rock mechanics tests;

[0009] Step 2: Determination of basic physical and mechanical properties of rock: Measure the longitudinal wave velocity of deep rock samples, and conduct XRD tests on the 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 the deep rock mass, and determine the basic mechanical properties of the rock mass, such as shear strength, compressive strength, dynamic compressive strength and dynamic tensile strength;

[0010] Step 3: Uniaxial loading test of deep rock samples based on high-speed camera: A uniaxial loading test is carried out on deep rock samples. High-speed camera is used to capture the uniaxial loading process 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 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: a uniaxial loading test is carried out on the deep rock samples, and the uniaxial loading process is monitored by acoustic emission to 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, the source location results of the acoustic emission events in the deep rock samples under the load and the original waveform of the acoustic emission are obtained;

[0012] Step 5. Focal mechanism and rupture mode of deep rock mass rupture under uniaxial load: Based on the monitored acoustic emission waveform files of deep rock samples under uniaxial load, perform waveform first arrival correction and acoustic emission event relocation on the acoustic emission events of the rock samples under load, obtain the focal mechanism solution of the deep rock mass under load, and determine the rupture mechanism and rupture mode of the rock mass at different loading stages;

[0013] Step 6. Four-dimensional imaging of damage evolution of deep rock mass under mining disturbance: Process the acoustic emission waveform data after relocation to obtain the seismic catalog of deep rock mass under load, improve the double-difference tomography technology to obtain a time-lapse tomography algorithm suitable for small-scale rock mass, determine the three-dimensional damage evolution in the bedding rock column as the load increases, and perform tomography along the main fracture surface to obtain the sliding process and damage evolution of deep rock mass along the main fracture surface under load, explore the four-dimensional imaging of the whole process of deep rock mass self-load disturbance until destruction and instability, and master the breeding mechanism of deep rock mass destruction and instability;

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

[0015] Preferably, in step 2, by obtaining the maximum principal stress when the rock sample is destroyed under different confining pressures, according to the Mohr-Coulomb strength criterion, the internal friction angle corresponding to the maximum principal stress when the rock sample is destroyed under different confining pressures is calculated according to the formula: NM=arctan[(σ1-σ2) / (σ1+σ2)], wherein σ1 represents different confining pressures, σ2 represents the maximum principal stress, and the cohesion corresponding to the maximum principal stress when the rock sample is destroyed under different confining pressures is calculated according to the formula NJ=(σ1-σ2) / 2-(σ1+σ2) / 2×sinNM;

[0016] By obtaining the maximum axial load when the rock sample is destroyed in the uniaxial compression test, recorded as P, and obtaining the cross-sectional area of ​​the rock sample, recorded as A, the compressive strength of the rock sample is calculated according to the formula KY = P / A;

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

[0018] The load when the rock sample is destroyed in the dynamic splitting test is obtained, recorded as P, and the diameter and thickness of the disc-shaped rock sample are obtained, recorded as D and h respectively, and the dynamic tensile strength of the rock sample is calculated according to the formula KLd=2P / (πDh).

[0019] Preferably, 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 recorded as NM respectively. i , NJ i and KYi , i represents the number of each test period;

[0020] 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 recorded as NM0, NJ0 and KY0 respectively;

[0021] According to the formula:

[0022]

[0023] The comprehensive quality assessment coefficient C of the rock sample corresponding to each test period is calculated, 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] The comprehensive quality assessment coefficient of the rock sample corresponding to the initial test period is obtained, recorded as C1. After a period of time t, the comprehensive quality assessment coefficient of the rock sample corresponding to the test period is obtained again, recorded as C2. The comprehensive quality assessment coefficient of the rock sample corresponding to the test period after a period of time t is compared with the comprehensive quality assessment 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. The comprehensive quality assessment coefficient of the rock sample corresponding to each test period is plotted into a line graph for display. The decline in the overall mechanical properties of the rock sample in each test period is intuitively represented according to the line graph of the comprehensive quality assessment coefficient of the rock sample corresponding to each test period. If the comprehensive quality assessment coefficient continuously decreases by more than 12% in a short period of time, it means that the weathering and deterioration process of the rock sample is accelerated. If the comprehensive quality assessment coefficient decreases by less than 8%, it means that the weathering and deterioration process of the rock sample is relatively slow.

[0025] Preferably, based on the acoustic emission signal characteristics of the loaded deep rock mass and high-speed camera technology, the spatiotemporal evolution of rock mass rupture under load is constructed, the focal mechanism solution in the rock mass under different stress levels is explored, and the rupture mode, rupture mechanism and strain field evolution of the rock mass under different stress levels are mastered.

[0026] Preferably, by selecting in-situ sampling of the target deep rock mass, a uniaxial loading test of the deep rock samples based on high-speed videography and acoustic emission monitoring is carried out indoors, the strain field evolution and destructive instability characteristics of the deep rock mass under mining disturbance are studied, the mechanical characteristics of the deep rock mass and the quantitative relationship between the surface strain field evolution and the stress level are explored, the focal mechanism of the deep rock samples under load is analyzed, the rupture mode and focal mechanism solution of the deep rock mass under different disturbance degrees are mastered, the instability law, rupture mode, focal mechanism solution, the relationship between the strain field evolution and the stress level of the deep rock mass are constructed, the rupture mode and focal mechanism solution of the deep rock mass under mining disturbance are mastered, and the foundation is laid for four-dimensional imaging of the damage evolution of the deep rock mass and instability early warning.

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

[0028] Preferably, the fracture process of deep rock samples under load monitored by acoustic emission is monitored, and the fracture point in the rock column is located by triple difference, so as to grasp the spatiotemporal evolution of fracture in the loaded rock mass and the magnitude of acoustic emission energy. The four-dimensional imaging technology of time-lapse imaging is developed by improving double-difference tomography, which can visualize the damage of rock mass in different load-bearing stages in three dimensions, explore the damage evolution and instability mechanism in deep rock mass, and visualize the sliding process of rock mass fracture along the main crack under load.

[0029] Preferably, a damage and instability early warning system is constructed by constructing a multi-means coordinated by strain field, four-dimensional imaging of damage evolution inside deep rock mass, focal mechanism solution of deep rock mass rupture, etc.

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

[0031] Preferably, four-dimensional imaging under load based on waveform cross-correlation is performed by studying the source locations of acoustic emission events in bedding rock samples under uniaxial loads, and continuously performing near-real-time imaging in three-dimensional space with time as one dimension, so as to grasp the fracture characteristics and spatiotemporal evolution of damage in bedding rock columns over time.

[0032] Compared with the prior art, it has the following beneficial effects:

[0033] 1. In the present invention, by adopting research methods such as theoretical analysis, indoor experiments, and algorithm development, the surface displacement field evolution and internal damage four-dimensional imaging of the loaded rock mass are studied respectively, the incubation process and visualization of deep rock mass failure and instability under mining disturbance are explored, and combined with the surface displacement field evolution, the focal mechanism solution of rock mass rupture, and the four-dimensional imaging of internal damage, an early warning system for deep rock mass failure and instability under mining disturbance is constructed. 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 rupture under mining disturbance, provide theoretical and technical references for stability monitoring and crisis resolution of rock mass under deep complex conditions, construct a failure and instability early warning system coordinated by multiple means such as strain field, four-dimensional imaging of internal damage of rock mass, and focal mechanism solution of rock mass rupture, grasp the visualization of internal damage of deep rock mass under mining disturbance and clarify the focal mechanism of rupture, and provide early warning references for the failure and instability of deep rock mass.

[0034] 2. In the present invention, the internal friction angle, cohesion and compressive strength of the rock sample corresponding to each test period are monitored in real time, and the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample are obtained at the same time, so as to obtain the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample. The monitoring data of each test period and the corresponding initial monitoring data are comprehensively calculated to generate the comprehensive quality assessment coefficient of the rock sample corresponding to each test period. By statistically comparing the comprehensive quality assessment coefficient of the rock sample corresponding to each test period and the comprehensive quality assessment coefficient of the initial test period, the weathering and deterioration process of the rock sample in each test period can be intuitively represented, so as to provide accurate results of the overall mechanical properties of the rock sample for the test of rock mass fracture mechanism.

[0035] Other features and advantages of the present invention will be set forth in the following description, and in part will become apparent from the description, or may be understood through implementation of the present invention. The objects and other advantages of the present invention may be realized and obtained through the structures indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0037] Figure 2 Schematic diagram of event pairs, station pairs and double pairs according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments 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] Embodiment 1:

[0040] See also Figure 1 to Figure 2 As shown in the figure, the test method for the fracture mechanism of deep rock mass under mining disturbance includes the following steps:

[0041] Step 1. Sample acquisition and preparation: Use the in-situ sampling method to obtain rock samples from deep rock mass, ensure that the rock samples are taken from the same project area, and the lithology and mineral composition are roughly consistent. Prepare 30 cubic samples (100mm×100mm×100mm) and 120 cylindrical rock standard cylindrical samples (Φ50mm×h100mm) for rock mechanics tests;

[0042] Step 2: Determination of basic physical and mechanical properties of rock: Measure the longitudinal wave velocity of deep rock samples, and conduct XRD tests on the 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 the deep rock mass, and determine the basic mechanical properties of the rock mass, such as shear strength, compressive strength, dynamic compressive strength and dynamic tensile strength;

[0043] Specifically, by obtaining the maximum principal stress when the rock sample is destroyed under different confining pressures, according to the Mohr-Coulomb strength criterion, the internal friction angle corresponding to the maximum principal stress when the rock sample is destroyed under different confining pressures is calculated according to the formula: NM=arctan[(σ1-σ2) / (σ1+σ2)], where σ1 represents different confining pressures, σ2 represents the maximum principal stress, and the cohesion corresponding to the maximum principal stress when the rock sample is destroyed under different confining pressures is calculated according to the formula NJ=(σ1-σ2) / 2-(σ1+σ2) / 2×sinNM;

[0044] By obtaining the maximum axial load when the rock sample is destroyed in the uniaxial compression test, recorded as P, and obtaining the cross-sectional area of ​​the rock sample, recorded as A, the compressive strength of the rock sample is calculated according to the formula KY = P / A;

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

[0046] By obtaining the load when the rock sample is destroyed in the dynamic splitting test, denoted as P, and 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 50mm and a thickness of 25mm, the load when it is destroyed in the dynamic splitting test is 10kN, and its dynamic tensile strength is calculated as: σtd=2×10000 / (π×0.05×0.025)≈509299Pa≈509.3MPa.

[0047] Step 3: Uniaxial loading test of deep rock samples based on high-speed camera: A uniaxial loading test is carried out on deep rock samples. High-speed camera is used to capture the uniaxial loading process 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 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: a uniaxial loading test is carried out on the deep rock samples, and the uniaxial loading process is monitored by acoustic emission to 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, the source location results of the acoustic emission events in the deep rock samples under the load and the original waveform of the acoustic emission are obtained;

[0049] Step 5. Focal mechanism and rupture mode of deep rock mass rupture under uniaxial load: Based on the monitored acoustic emission waveform files of deep rock samples under uniaxial load, perform waveform first arrival correction and acoustic emission event relocation on the acoustic emission events of the rock samples under load, obtain the focal mechanism solution of the deep rock mass under load, and determine the rupture mechanism and rupture mode of the rock mass at different loading stages;

[0050] It should be noted that, based on the acoustic emission signal characteristics of deep rock mass under load and high-speed camera technology, the spatiotemporal evolution of rock mass rupture under load is constructed, the focal mechanism solution in the rock mass under different stress levels is explored, and the rupture mode, rupture mechanism and strain field evolution of the rock mass under different stress levels are mastered;

[0051] Specifically: by selecting in-situ sampling of target deep rock mass, conducting uniaxial loading tests on deep rock samples based on high-speed video and acoustic emission monitoring indoors, studying the strain field evolution and destructive instability characteristics of deep rock mass under mining disturbance, exploring the mechanical characteristics of deep rock mass and the quantitative relationship between surface strain field evolution and stress level, analyzing the focal mechanism of deep rock samples under load, mastering the rupture mode and focal mechanism solution of deep rock mass under different disturbance degrees, constructing the relationship between the instability law, rupture mode, focal mechanism solution, strain field evolution and stress level of deep rock mass, mastering the rupture mode and focal mechanism solution of deep rock mass under mining disturbance, laying the foundation for four-dimensional imaging of deep rock damage evolution and instability early warning.

[0052] Step 6. Four-dimensional imaging of damage evolution of deep rock mass under mining disturbance: Process the acoustic emission waveform data after relocation to obtain the seismic catalog of deep rock mass under load, improve the double-difference tomography technology to obtain a time-lapse tomography algorithm suitable for small-scale rock mass, determine the three-dimensional damage evolution in the bedding rock column as the load increases, and perform tomography along the main fracture surface to obtain the sliding process and damage evolution of deep rock mass along the main fracture surface under load, explore the four-dimensional imaging of the whole process of deep rock mass self-load disturbance until destruction and instability, and master the breeding mechanism of deep rock mass destruction and instability;

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

[0054] Specifically, the fracture process of deep rock samples under load monitored by acoustic emission is monitored, and the fracture point in the rock column is located by triple difference, so as to grasp the spatiotemporal evolution of fracture in the loaded rock mass and the size of acoustic emission energy. The four-dimensional imaging technology of time-lapse imaging is developed by improving double-difference tomography, which can visualize the damage of rock mass in different load-bearing stages in three dimensions, explore the damage evolution and instability mechanism in deep rock mass, and visualize the sliding process of rock mass fracture along the main crack under load.

[0055] Step 7. Construct an early warning system for the failure and instability of deep rock masses under mining disturbance: Based on the mechanical characteristics of deeply buried rock samples under uniaxial load, the evolution of strain fields, the source mechanism of rupture, the four-dimensional imaging of internal damage and the incubation mechanism of failure and instability, combined with geomechanical parameters and basic physical and mechanical properties of rock masses, explore the indicators and weights of the failure and instability of deep rock masses under mining disturbance, and construct an early warning system for the failure and instability of deep rock masses.

[0056] It should be noted that by constructing a damage and instability early warning system that is coordinated by multiple means, such as strain field, four-dimensional imaging of the internal damage evolution of deep rock mass, and focal mechanism solution of deep rock mass rupture;

[0057] Specifically, based on the actual working conditions of deep rock mass, combined with the rock mass geomechanical parameters, mechanical characteristics, strain field evolution and four-dimensional imaging of damage during loading, the mechanism of deep rock mass failure and instability under mining disturbance is analyzed. The relationship between the surface strain field evolution and the four-dimensional imaging of internal damage and stress level of deep rock mass under load disturbance is quantified, and the failure and instability process of deep rock mass under load disturbance is visualized. At the same time, based on the mechanical mechanism of deep rock mass loading, damage evolution and focal mechanism solution of rupture, the precursor characteristics before rock mass rupture and instability are mastered, and the early warning criteria for deep rock mass failure and instability under mining disturbance are constructed.

[0058] In a specific embodiment, the present invention adopts research methods such as theoretical analysis, indoor experiments, and algorithm development to conduct research from the evolution of the surface displacement field and the four-dimensional imaging of internal damage of the loaded rock mass, explore the incubation process and visualization of deep rock mass failure and instability under mining disturbance, and combine the evolution of the surface displacement field, the focal mechanism solution of rock mass rupture, and the four-dimensional imaging of internal damage to construct an early warning system for deep rock mass failure and instability under mining disturbance. 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 rupture under mining disturbance, provide theoretical and technical references for stability monitoring and crisis resolution of rock mass under deep complex conditions, construct a failure and instability early warning system coordinated by multiple means such as strain field, four-dimensional imaging of internal damage of rock mass, and focal mechanism solution of rock mass rupture, grasp the visualization of internal damage of deep rock mass under mining disturbance and clarify the focal mechanism of rupture, and provide an early warning reference for the failure and instability of deep rock mass.

[0059] Furthermore, for the relocation of deep rock acoustic emission events, a triple difference earthquake positioning method is generated by combining the double difference positioning method of the prior art with the double difference positioning method of the station pair, which improves the absolute and relative positions of earthquakes and improves the positioning accuracy of weak earthquake events;

[0060] The double-difference positioning method uses the first arrival time difference data of the event pair to the same station. The 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 the event pair can eliminate the influence of the velocity model error on the similar ray path outside the source area on the positioning; (2) The high-precision waveform cross-correlation arrival time difference data can greatly improve the relative position of the corresponding events, and the relative position of the event pair with no waveform similarity can be located by the arrival time difference data of the earthquake catalog;

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

[0062] exist Figure 2(a) is a schematic diagram of event pairs, (b) is a schematic diagram of station pairs, (c) is a schematic diagram of double pairs, and (d) is a flowchart for constructing three different arrival time difference data. Gray shadows represent areas near or outside the source area.

[0063] Furthermore, based on the four-dimensional imaging under the action of waveform cross-correlation, the source location of the acoustic emission event of the bedding rock sample under uniaxial load is studied, and near-real-time imaging is continuously performed in three-dimensional space with time as one dimension to grasp the spatiotemporal evolution of the fracture characteristics and damage in the bedding rock column over time. This method is developed on the basis of traditional double-difference seismic tomography and can more reliably determine the temporal changes in the velocity of the bedding rock column.

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

[0065]

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

[0067] In the traditional double-difference seismic tomography algorithm, the two seismic events that constitute the event pair are not far apart and are received by enough stations. These requirements have high data requirements and the accuracy of inversion has room for further improvement. In time-lapse tomography based on waveform cross-correlation, in order to invert the velocity changes in two time periods, the two events that constitute the 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 regional difference of Equation (3) is that the slowness perturbations δμ1 and δμ2 are different for time periods 1 and 2, that is, the two events m and n that constitute the 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 uses travel time difference data to invert velocity changes, while the traditional method only subtracts the velocity models obtained from two different time periods. Therefore, time-lapse tomography can greatly reduce the errors caused by different data distribution.

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

[0071] Embodiment 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 recorded as NM respectively. i , NJ i and KY i , 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 recorded as NM0, NJ0 and KY0 respectively;

[0074] According to the formula:

[0075]

[0076] The comprehensive quality assessment coefficient C of the rock sample corresponding to each test period is calculated. w1, w2 and w3 represent the weight factors corresponding to the internal friction angle, cohesion and compressive strength, respectively, and w1+w2+w3=1. Its size is a custom setting, such as: w1=0.35, w2=0.45, w3=0.2.

[0077] The comprehensive quality assessment coefficient of the rock sample corresponding to the initial test period is obtained, recorded as C1. After a period of time t, the comprehensive quality assessment coefficient of the rock sample corresponding to the test period is obtained again, recorded as C2. The comprehensive quality assessment coefficient of the rock sample corresponding to the test period after a period of time t is compared with the comprehensive quality assessment 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. The comprehensive quality assessment coefficient of the rock sample corresponding to each test period is plotted into a line graph for display. The decline in the overall mechanical properties of the rock sample in each test period is intuitively represented according to the line graph of the comprehensive quality assessment coefficient of the rock sample corresponding to each test period. If the comprehensive quality assessment coefficient continuously decreases by more than 12% in a short period of time, it means that the weathering and deterioration process of the rock sample is accelerated. If the comprehensive quality assessment coefficient decreases by less than 8%, it means that the weathering and deterioration process of the rock sample is relatively slow.

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

[0079] In a specific embodiment, the present invention obtains the internal friction angle, cohesion and compressive strength of the rock sample corresponding to each test period through real-time monitoring, and simultaneously obtains the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample, thereby obtaining the initial internal friction angle, initial cohesion and initial compressive strength of the rock sample, and comprehensively calculates the monitoring data of each test period and the corresponding initial monitoring data to generate a comprehensive quality assessment coefficient of the rock sample corresponding to each test period. By statistically comparing the comprehensive quality assessment coefficient of the rock sample corresponding to each test period and the comprehensive quality assessment coefficient of the initial test period, the weathering and deterioration process of the rock sample in each test period can be intuitively represented, thereby providing accurate results of the overall mechanical properties of the rock sample for the test of the rock mass fracture mechanism.

[0080] Embodiment 3:

[0081] On the basis of Example 1, a uniaxial loading test was carried out on a deep rock sample, and a high-speed camera was used to capture the uniaxial loading process of the rock sample. Specifically,

[0082] Data collection is performed on the surface and side of the sample to obtain surface data and side data, and the data are sent to the server. The server sends the surface data and side data to the data processing end, and the data processing end processes the surface data and side data to obtain roughness values ​​and side sag values, and feeds back to the server; the surface data includes surface scanning data of the sample, and the side data is side scanning data of the sample.

[0083] The server compares the roughness value and the side non-sagging value with the corresponding thresholds respectively. If the roughness value is greater than or equal to the corresponding roughness threshold or the side non-sagging value is greater than or equal to the corresponding non-sagging threshold, a sample unqualified instruction is generated and sent to the corresponding intelligent terminal for display; when the roughness value and the side non-sagging value are both less than the corresponding roughness threshold and non-sagging threshold, the environmental data of the high-speed camera is collected, wherein the environmental data includes temperature, humidity and light intensity; the environmental standard data is set, including the temperature standard range, the humidity standard range and the light intensity standard range; the collected environmental data is compared with the standard data: if the collected temperature does not belong to the temperature standard range or the humidity does not belong to the humidity standard range or the light intensity does not belong to the light intensity standard range, a temperature adjustment instruction or a humidity adjustment instruction or a light intensity adjustment instruction is generated; the server sends the temperature adjustment instruction or the humidity adjustment instruction or the light intensity adjustment instruction to the corresponding intelligent terminal; the control terminal controls the corresponding temperature control equipment, humidity control equipment and lighting equipment to make the environmental data of the high-speed camera in the corresponding environmental standard data, so as to improve the clarity of the high-speed camera, avoid image blur or shadow, and affect the accurate judgment of the rock sample change.

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

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

[0086] The surface scanning data of the sample is parsed 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 distance value of the same size 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 two adjacent outliers is connected to obtain the outlier spacing, all the outliers are compared with the spacing threshold, the outliers that are less than the spacing threshold are marked as outlier spacing, and the outliers that are greater than or equal to the spacing threshold are marked as outlier spacing; the outliers, outliers, and outliers 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 heterogeneous numbers, L j1 is a different spacing, j1 is the number of the different spacing, j1 = 1, 2, ..., n1; L j2is the heterogeneous spacing, j2 is the number of the heterogeneous spacing, j2 = 1, 2, ..., n2; LLj is the average value corresponding to all heterogeneous spacings and heterogeneous spacings; λ1, λ2, λ3, λ4 are all preset weight factors, and λ1>λ3>λ2>λ4>0.5; ηz1, ηz2 are the number thresholds corresponding to the heterogeneous number, and ηz1>ηz2>0. The non-slip values ​​of all surfaces of the sample are summed to obtain the non-smooth value.

[0087] The side data of the sample are analyzed to obtain the distance between several collection points on the side and the scanning electrode, and the side is divided into several columns according to the vertical direction. The distance values ​​of the collection points in each column are averaged to obtain the deviation value, and the distance values ​​of all the collection points are compared with the average value. If the two are inconsistent, the difference between the two is calculated to obtain the deviation difference, and all the deviation differences are summed to obtain the total deviation value of each column; the total deviation values ​​of all columns are summed and multiplied by the corresponding preset conversion factor to obtain the side deviation value.

[0088] By analyzing the surface data and side data of the sample, the roughness value and the side non-sagging value are obtained. The dimensional parameters of the sample are judged by the roughness value and the side non-sagging value to avoid unqualified samples affecting the stress distribution and deformation mode during loading, thereby affecting the image features captured by the camera. Through detailed scanning data analysis and outlier value analysis, it is possible to accurately capture the slight changes on the surface of the sample and improve the accuracy of the analysis. Not only the roughness of the sample surface is taken into account, but also the verticality of the sample is evaluated through side data analysis, providing a comprehensive sample quality assessment. The preset weight factors and quantity thresholds of the present invention can be adjusted according to different sample types and requirements, increasing the flexibility and applicability of the method. Through the non-slip value and side non-sagging value output by the model, the surface quality and verticality of the sample can be intuitively understood.

[0089] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0090] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The experimental method for the fracture mechanism of deep rock mass under mining disturbance is characterized by: The following steps are involved: Step 1: Obtaining and preparing samples; Step 2: Determination of basic physical and mechanical properties of rocks; Step 3: Uniaxial loading test of deep rock samples based on high-speed photography; Step 4: uniaxial loading test of deep rock samples based on acoustic emission monitoring; Step 5: Source mechanism and rupture mode of deep rock mass rupture under uniaxial load; Step 6: Four-dimensional imaging of deep rock damage evolution under mining disturbance; Step 7: Construct an early warning system for deep rock mass damage and instability caused by mining disturbance.

2. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized by: In step 1, the specific process of sample acquisition and preparation is: obtain rock samples from deep rock mass, prepare several cubic samples and standard cylindrical samples, and then conduct rock mechanics tests.

3. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized in that: In step 2, the process of determining the basic physical and mechanical properties of rock is as follows: measuring the longitudinal wave velocity of deep rock samples, and determining the mineral composition of the rock samples through tests on the rock samples; determining the basic mechanical properties of the rock mass through triaxial loading tests under different confining pressures, where the basic mechanical properties include cohesion, internal friction angle, shear strength, compressive strength, dynamic compressive strength and dynamic tensile strength.

4. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 3 is characterized by: The internal friction angle, cohesion and compressive strength are denoted as NM respectively. i , NJ i and KY i , i represents the number of each test period; according to the formula: The comprehensive quality assessment coefficient C of the rock sample corresponding to each test period, the initial internal friction angle, initial cohesion and initial compressive strength of NM0, NJ0 and KY0 are calculated, and w1, w2 and w3 represent the weight factors corresponding to the internal friction angle, cohesion and compressive strength respectively; The comprehensive quality assessment coefficient C1 of the rock sample corresponding to the test period after a period of time is compared with the comprehensive quality assessment coefficient C2 of the rock sample corresponding to the initial test period. If C2<C1, the comprehensive quality assessment coefficients of the rock sample corresponding to each test period are plotted into a line graph for display, and the decline is calculated.

5. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized in that: In step three, the specific process of the uniaxial loading test of deep rock samples based on high-speed camera is as follows: a uniaxial loading test is carried out on the deep rock samples, and the uniaxial loading process of the rock samples is captured by high-speed camera at the same time, the fracture process on the surface of the rock samples is obtained, and digital image processing technology is used to obtain the strain field that evolves continuously with the increase of load and its sensitivity to the stress level.

6. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized by: In step 4, the specific process of the uniaxial loading test of deep rock samples based on acoustic emission monitoring is: a uniaxial loading test is carried out on the deep rock samples, and the uniaxial loading process is monitored by acoustic emission at the same time, to 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 the acoustic emission events in the deep rock samples under the load and the original acoustic emission waveform.

7. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized by: In step five, the specific process of the focal mechanism and rupture mode of deep rock mass under uniaxial load is as follows: according to the monitored acoustic emission waveform file of deep rock samples under uniaxial load, the waveform first arrival correction and acoustic emission event relocation of the acoustic emission events of the rock samples under load are performed to obtain the focal mechanism solution of the deep rock mass under load, and determine the rupture mechanism and rupture mode of the rock mass at different loading stages.

8. The test method for the fracture mechanism of deep rock mass under mining disturbance according to claim 1 is characterized by: In step six, the specific process of four-dimensional imaging of damage evolution of deep rock mass under mining disturbance is as follows: the acoustic emission waveform data after repositioning is processed to obtain the seismic catalog of the deep rock mass under load, the double-difference tomography technology is improved to obtain a time-lapse tomography algorithm suitable for small-scale rock mass, the three-dimensional damage evolution in the bedding rock column as the load increases, and tomography is performed along the main fracture surface at the same time to obtain the sliding process and damage evolution of the deep rock mass along the main fracture surface under load, the four-dimensional imaging of the entire process of deep rock mass self-load disturbance until failure and instability is monitored, and the breeding mechanism of deep rock mass failure and instability is obtained.

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