Multi-parameter combined impact coal rock instability failure early warning method

Abstract

The invention relates to the technical field of coal rock failure early warning, in particular to a multi-parameter combined impact coal rock instability failure early warning method, which comprises the following steps of: firstly, carrying out engineering geology investigation on a mine site, collecting a coal rock sample and testing ground stress distribution; secondly, preparing a standard coal rock test piece in a laboratory, and performing nondestructive testing; then, determining a loading and unloading path according to numerical simulation, and designing a graded loading and unloading path of the coal rock test pieces of the roof group and the laneway side group; then, loading and unloading the test piece by using a true triaxial loading testing machine, and synchronously acquiring electromagnetic radiation and acoustic emission data; and finally, by calculating the acoustic emission energy, the fractal dimension and the joint fractal dimension, dividing the grading early warning critical value of each index, and constructing a three-level early warning model for the coal rock impact instability. According to the method, the coal rock impact instability risk can be effectively identified, graded early warning is provided, corresponding safety measures are guided to be taken on site, and safe production of a mine is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of steam sampling equipment, in particular to a multi-parameter combined early warning method for impact coal rock instability and destruction. Background Art

[0002] Rock burst is one of the most difficult dynamic hazards to prevent and control in mining. Its occurrence is instantaneous and highly destructive, posing a serious threat to worker safety and impacting production efficiency. Therefore, rock burst propensity assessment of coal and rock strata in mines is crucial to determine whether they present a risk of rock burst. However, the occurrence of rock burst in actual mining is closely related to the loading and unloading effects on the coal and rock. During tunneling and mining, the roof, overburden, and surrounding rock experience varying loading and unloading effects, resulting in varying risks of coal and rock instability and failure. Rock burst in mining is a process that combines energy accumulation and release, structural damage, and destruction, making its precursors detectable. Early warning of rock burst relies on identifying precursor information and defining thresholds. my country has developed rock burst monitoring over a long period of development, resulting in highly accurate monitoring equipment, mature methods, and indicators. These include electromagnetic radiation monitoring, ground sound monitoring, and microseismic monitoring. While single monitoring equipment can be somewhat unpredictable, combining multiple monitoring devices can provide more accurate monitoring and early warning. In actual engineering situations, it is difficult to quantify the different loading and unloading paths to which coal and rock masses are subjected, and it is difficult to understand the patterns of coal and rock instability and failure. Furthermore, there is a certain degree of blindness in the selection of monitoring and early warning indicators. Therefore, there is a lack of a simple, effective, and highly accurate coal and rock instability early warning method that considers the loading and unloading effects of coal and rock masses in different regions and rationally selects early warning indicators. Summary of the Invention

[0003] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0004] This paper proposes a method for early warning of coal rock instability caused by impact, based on the fusion of multiple parameters such as electromagnetic radiation and acoustic emission, taking into account the loading and unloading paths of coal rock mining disturbances in the roof and roadway. This method considers not only one loading and unloading path, but also two loading and unloading paths for both the roof and roadway coal rock, thus covering a wider range of scenarios. Furthermore, it prioritizes electromagnetic radiation and acoustic emission multi-parameter indicators that can accurately characterize coal rock instability and failure. This multi-parameter early warning system integrates these parameters and constructs a three-level early warning response system, which can comprehensively cover the early warning of coal rock instability caused by mining disturbances in the roof and roadway coal rock impact.

[0005] A multi-parameter combined early warning method for coal rock instability and destruction caused by impact includes the following steps:

[0006] Conduct on-site surveys and drill coal and rock samples to test ground stress:

[0007] Conduct engineering geological surveys in mines with rock burst hazards to collect basic geological data, including the location, lithology, thickness, hardness, and strength of each coal and rock layer; collect complete coal samples without obvious cracks on both sides of the roadway and in front of the working face; and collect rock samples from different layers of the roadway surrounding rock and roof;

[0008] The distribution direction and magnitude of ground stress were tested. Based on the ground stress test results, the vertical stress in the tunnel and stope was calculated as σv=γH, the horizontal stress perpendicular to the axial direction of the tunnel was σh1=λ1γH, and the horizontal stress parallel to the axial direction of the tunnel was σh2=λ2γH.

[0009] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0010] Laboratory preparation of standard coal and rock specimens:

[0011] According to the recommended standards of the International Society of Rock Mechanics (ISRM), coal and rock samples were prepared into standard specimens with a length × width × height of 100 mm × 100 mm × 100 mm using a DME-2 cutting and grinding machine. The coal and rock specimens were divided into roof group and roadway side group.

[0012] Number the prepared standard specimens and record the original data of each specimen, including weight, density, and porosity;

[0013] Use ultrasonic testing equipment to perform non-destructive testing on the specimen to ensure that there are no obvious defects inside the specimen.

[0014] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0015] Numerical simulation to determine the loading and unloading path:

[0016] A numerical model is constructed based on the collected coal and rock geomechanical parameters, and stress and boundary conditions are assigned to the model based on the ground stress test results;

[0017] Excavation was carried out according to the actual situation on site, and the peak vertical stress of the roof overburden during the tunnel excavation process was recorded as σ v1(d) =k 1(d) γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(d) =λ 11(d) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(d) =λ 21(d) γH, record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v1(b) =k 1(b)γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(b) =λ 11(b) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(b) =λ 21(b) γH;

[0018] According to the actual situation on site, the working face is mined and the peak value of the vertical stress of the roof overburden during the mining process is recorded as σ v2(d) =k 2(d) γH, the peak horizontal stress of the vertical roadway axis is σ h12(d) =λ 12(d) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(d) =λ 22(d) γH; record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v2(b) =k 2(b) γH, the peak horizontal stress of the vertical roadway axis is σ h12(b) =λ 12(b) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(b) =λ 22(b) γH;

[0019] Considering the actual loading and unloading conditions of the roof coal and rock during tunneling and working face mining, a graded loading and unloading path for the roof group coal and rock specimens was designed based on the peak stress variation characteristics of the roof during tunneling and working face mining obtained from numerical simulation.

[0020] Considering the actual loading and unloading conditions of the coal and rock on the side of the roadway during tunnel excavation and working face mining, the graded loading and unloading paths and loading and unloading rates of the coal and rock specimens on the side of the roadway are designed based on the peak stress change characteristics of the surrounding rocks on both sides during tunnel excavation and working face mining obtained from numerical simulation.

[0021] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0022] Loading coal and rock specimens and collecting monitoring data:

[0023] Connect electromagnetic radiation and acoustic emission monitoring equipment to the true triaxial loading testing machine, and arrange electromagnetic radiation and acoustic emission sensors;

[0024] The coal and rock specimens of the roof group were loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data were collected simultaneously;

[0025] The coal and rock specimens in the roadway side group were loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data were collected simultaneously;

[0026] During the loading process, the deformation of the specimen is monitored in real time and the stress and strain curves are recorded.

[0027] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0028] Classification and processing of monitoring data:

[0029] The energy-count data is obtained from the acoustic emission monitoring and the acoustic emission energy b is calculated. i The value is as follows:

[0030]

[0031] Where m is the total number of magnitude classes; M i is the magnitude of the ith level; N i is the actual number of events in the i-th magnitude range.

[0032] The relationship between magnitude and energy is as follows:

[0033] Log 10 E=M

[0034] When the acoustic emission b i -b i-1 <0, b i -b i+1 >0, select b i The value is the warning critical value b0; the acoustic emission b value change rate εb is defined i for:

[0035]

[0036] Calculation of acoustic emission fractal dimension D using GP algorithm i(AE) , the calculation formula is as follows:

[0037]

[0038] Where C (r) is the correlation function, r is the given scale;

[0039] Definition of acoustic emission fractal dimension change ΔD i(AE) for:

[0040] ΔD i(AE) =D i(AE) -D i-1(AE)

[0041] Calculation of electromagnetic radiation fractal dimension D using GP algorithm i(EMR) , the calculation formula is as follows:

[0042]

[0043] Define the change in the fractal dimension of electromagnetic radiation ΔD i(EMR) for:

[0044] ΔD i(EMR) =D i(EMR) -D i-1(EMR)

[0045] The combined fractal dimension D is calculated from the fractal dimension of acoustic emission and the fractal dimension of electromagnetic radiation. i , the calculation formula is as follows:

[0046]

[0047] Where D max(AE) is the calculated maximum acoustic emission fractal dimension, D max(EMR) is the calculated maximum fractal dimension of electromagnetic radiation;

[0048] Define the change in joint fractal dimension ΔD i(AE) for:

[0049] ΔD i =D i -D i-1 .

[0050] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0051] Divide each indicator into graded warning critical values:

[0052] Divide the acoustic emission b value change rate εb i The critical values for graded warnings are:

[0053]

[0054] Divide the change of acoustic emission fractal dimension ΔD i(AE) The critical values for graded warnings are:

[0055]

[0056] Divide the change of electromagnetic radiation fractal dimension ΔD i(EMR) The critical values for graded warnings are:

[0057]

[0058] The critical value of the graded warning of the change in the joint fractal dimension ΔDi is:

[0059]

[0060] As a preferred solution of the multi-parameter combined early warning method for impact coal rock instability and destruction, the present invention provides:

[0061] Input the calculated warning values of the four indicators, record no impact risk as X1, weak impact risk as X2, medium impact risk as X3, and strong impact risk as X4, and build a warning model; if all four indicators are zero, the output is safe; if one to three of the four indicators are weak and the rest are zero, the output is a level I warning; if four are weak or one to three are medium and the rest are weak or zero, the output is a level II warning; if four are medium or one or more are strong, the output is a level III warning;

[0062] Corresponding to on-site projects, Level I warning indicates low risk, requiring attention to daily monitoring and recording, safety inspections, and preventive pressure relief measures; Level II warning indicates medium risk, requiring personnel control, limiting the scope of operations, increasing monitoring frequency, and conducting local pressure relief and support; Level III warning indicates high risk, requiring immediate suspension of production and activation of emergency plans, strengthening pressure relief measures, intensifying monitoring and assessment, and rectifying hidden dangers.

[0063] Beneficial effects of the present invention:

[0064] This paper proposes a method for early warning of coal rock instability caused by impact, based on the fusion of multiple parameters such as electromagnetic radiation and acoustic emission, taking into account the loading and unloading paths of coal rock mining disturbances in the roof and roadway. This method considers not only one loading and unloading path, but also two loading and unloading paths for both the roof and roadway coal rock, thus covering a wider range of scenarios. Furthermore, it prioritizes electromagnetic radiation and acoustic emission multi-parameter indicators that can accurately characterize coal rock instability and failure. This multi-parameter early warning system integrates these parameters and constructs a three-level early warning response system, which can comprehensively cover the early warning of coal rock instability caused by mining disturbances in the roof and roadway coal rock impact. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0066] in:

[0067] Figure 1 Schematic diagram of stress in three directions of the roadway;

[0068] Figure 2 Schematic diagram of the peak stress variation characteristics of the roof;

[0069] Figure 3 The intention of the change characteristics of the peak stress of the surrounding rock in the two gangs;

[0070] Figure 4 Schematic diagram of the early warning model. DETAILED DESCRIPTION

[0071] In order to make the purpose, features, and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below 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 making creative work are within the scope of protection of the present invention.

[0072] Example:

[0073] 1. Conduct on-site surveys and drill coal and rock samples to test ground stress:

[0074] 1. Conduct engineering geological surveys in mines with rock burst hazards and collect basic geological data, including the location, lithology, thickness, hardness, and strength of each coal and rock layer. Collect well-developed coal samples without obvious cracks on both sides of the roadway and in front of the working face, and collect rock samples from different layers of the roadway surrounding rock and roof.

[0075] 2. Test the distribution direction and magnitude of ground stress, and calculate the vertical stress in the tunnel and stope as σ based on the ground stress test results. v =γH, the horizontal stress perpendicular to the axial direction of the roadway is σ h1 =λ1γH, the horizontal stress parallel to the axial direction of the roadway is σ h2 =λ2γH. Figure 1 shown.

[0076] 2. Laboratory preparation of standard coal and rock specimens:

[0077] 1. According to the recommended standards of the International Society of Rock Mechanics (ISRM), the coal and rock samples were prepared into standard specimens with a length × width × height of 100 mm × 100 mm × 100 mm using a DME-2 cutting and grinding machine. The coal and rock specimens were divided into roof group and roadway side group.

[0078] 2. Number the prepared standard specimens and record the original data of each specimen, including weight, density, porosity, etc.

[0079] 3. Use ultrasonic testing equipment to conduct non-destructive testing on the specimen to ensure that there are no obvious defects inside the specimen.

[0080] 3. Numerical simulation to determine loading and unloading paths:

[0081] 1. Construct a numerical model based on the collected coal and rock geomechanical parameters, and assign stress and boundary conditions to the model based on the ground stress test results.

[0082] 2. Excavate according to the actual situation on site. Record the peak value of vertical stress of roof overburden during tunnel excavation as σ v1(d) =k 1(d)γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(d) =λ 11(d) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(d) =λ 21(d) γH, record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v1(b) =k 1(b) γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(b) =λ 11(b) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(b) =λ 21(b) γH.

[0083] 3. Mining the working face according to the actual situation on site, and recording the peak value of vertical stress of the roof overburden during the mining process as σ v2(d) =k 2(d) γH, the peak horizontal stress of the vertical roadway axis is σ h12(d) =λ 12(d) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(d) =λ 22(d) γH. Record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v2(b) =k 2(b) γH, the peak horizontal stress of the vertical roadway axis is σ h12(b) =λ 12(b) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(b) =λ 22(b) γH.

[0084] 4. Considering the actual loading and unloading conditions of the roof coal and rock during tunnel excavation and working face mining, the graded loading and unloading paths of the roof group coal and rock specimens are designed based on the peak stress variation characteristics of the roof during tunnel excavation and working face mining obtained by numerical simulation, such as Figure 2 shown.

[0085] 5. Considering the actual loading and unloading conditions of the coal and rock on the roadway side during roadway excavation and working face mining, the graded loading and unloading paths and loading and unloading rates of the coal and rock specimens on the roadway side are designed based on the peak stress variation characteristics of the surrounding rocks on both sides during roadway excavation and working face mining obtained by numerical simulation, such as Figure 3 shown.

[0086] 4. Loading coal and rock specimens and collecting monitoring data:

[0087] 1. Connect the electromagnetic radiation and acoustic emission monitoring equipment to the true triaxial loading testing machine, and arrange the electromagnetic radiation and acoustic emission sensors.

[0088] 2. The coal and rock specimens of the roof group are loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data are collected simultaneously.

[0089] 3. The coal and rock specimens in the roadway group are loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data are collected simultaneously.

[0090] 4. During the loading process, the deformation of the specimen is monitored in real time and the stress and strain curves are recorded.

[0091] V. Classification and processing of monitoring data:

[0092] 1. Obtain energy-count data from acoustic emission monitoring and calculate acoustic emission energy b i The value is as follows:

[0093]

[0094] Where m is the total number of magnitude classes; M i is the magnitude of the ith level; N i is the actual number of events in the i-th magnitude range.

[0095] The relationship between magnitude and energy is as follows:

[0096] Log 10 E=M

[0097] When the acoustic emission b i -b i-1 <0, b i -b i+1 >0, select b i The value is the warning threshold b0. Define the acoustic emission b value change rate εb i for:

[0098]

[0099] 2. Use GP algorithm to calculate the acoustic emission fractal dimension D i(AE) , the calculation formula is as follows:

[0100]

[0101] Where C (r) is the correlation function, and r is the given scale.

[0102] Definition of acoustic emission fractal dimension change ΔD i(AE) for:

[0103] ΔD i(AE) =D i(AE) -D i-1(AE)

[0104] 3. Use GP algorithm to calculate the fractal dimension D of electromagnetic radiation i(EMR) , the calculation formula is as follows:

[0105]

[0106] Define the change in the fractal dimension of electromagnetic radiation ΔD i(EMR) for:

[0107] ΔD i(EMR) =D i(EMR) -D i-1(EMR)

[0108] 4. Calculate the combined fractal dimension D from the acoustic emission fractal dimension and the electromagnetic radiation fractal dimension i , the calculation formula is as follows:

[0109]

[0110] Where D max(AE) is the calculated maximum acoustic emission fractal dimension, D max(EMR) is the calculated maximum fractal dimension of electromagnetic radiation.

[0111] Define the change in joint fractal dimension ΔD i(AE) for:

[0112] ΔD i =D i -D i-1

[0113] 6. Classify the critical values of warning for each indicator:

[0114] 1. Classify the acoustic emission b value change rate εb i The critical values for graded warnings are:

[0115]

[0116] 2. Divide the change of acoustic emission fractal dimension ΔD i(AE) The critical values for graded warnings are:

[0117]

[0118] 3. Divide the change in the fractal dimension of electromagnetic radiation ΔD i(EMR) The critical values for graded warnings are:

[0119]

[0120] 4. Divide the change of joint fractal dimension ΔD i The critical values for graded warnings are:

[0121]

[0122] 7. Construct a three-level early warning model for coal rock impact instability:

[0123] 1. Input the calculated warning values of the four indicators, record no impact risk as X1, weak impact risk as X2, medium impact risk as X3, and strong impact risk as X4, and build a warning model. If all four indicators are negative, the output is safe. If one to three of the four indicators are weak and the rest are negative, the output is level I warning. If four are weak or one to three are medium and the rest are weak or negative, the output is level II warning. If four are medium or one or more are strong, the output is level III warning, as shown below. Figure 4 shown.

[0124] 2. Corresponding to on-site projects, Level I warnings indicate low risk and require daily monitoring and record keeping, safety inspections, and preventative pressure relief measures. Level II warnings indicate moderate risk and require personnel control, restricted work areas, increased monitoring frequency, and localized pressure relief and support. Level III warnings indicate high risk and require immediate production suspension and activation of emergency plans, strengthened pressure relief measures, enhanced monitoring and assessment, and rectification of potential hazards.

[0125] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-parameter combined early warning method for coal rock instability and destruction, characterized by: The following steps are involved: Conduct on-site surveys and drill coal and rock samples to test ground stress: Conduct engineering geological surveys in mines with rock burst hazards to collect basic geological data, including the location, lithology, thickness, hardness, and strength of each coal and rock layer; collect complete coal samples without obvious cracks on both sides of the roadway and in front of the working face; and collect rock samples from different layers of the roadway surrounding rock and roof; The distribution direction and magnitude of ground stress were tested. Based on the ground stress test results, the vertical stress in the tunnel and stope was calculated as σv=γH, the horizontal stress perpendicular to the axial direction of the tunnel was σh1=λ1γH, and the horizontal stress parallel to the axial direction of the tunnel was σh2=λ2γH.

2. The multi-parameter combined early warning method for coal rock instability and destruction as claimed in claim 1, characterized in that: Laboratory preparation of standard coal and rock specimens: According to the recommended standards of the International Society of Rock Mechanics (ISRM), coal and rock samples were prepared into standard specimens with a length × width × height of 100 mm × 100 mm × 100 mm using a DME-2 cutting and grinding machine. The coal and rock specimens were divided into roof group and roadway side group. Number the prepared standard specimens and record the original data of each specimen, including weight, density, and porosity; Use ultrasonic testing equipment to perform non-destructive testing on the specimen to ensure that there are no obvious defects inside the specimen.

3. The multi-parameter combined early warning method for coal rock instability and destruction as claimed in claim 2 is characterized by: Numerical simulation to determine the loading and unloading path: A numerical model is constructed based on the collected coal and rock geomechanical parameters, and stress and boundary conditions are assigned to the model based on the ground stress test results; Excavation was carried out according to the actual situation on site, and the peak vertical stress of the roof overburden during the tunnel excavation process was recorded as σ v1(d) =k 1(d) γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(d) =λ 11(d) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(d) =λ 21(d) γH, record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v1(b) =k 1(b) γH, the peak value of horizontal stress perpendicular to the axial direction of the roadway is σ h11(b) =λ 11(b) γH, the peak value of horizontal stress parallel to the axial direction of the roadway is σ h21(b) =λ 21(b) γH; According to the actual situation on site, the working face is mined and the peak value of the vertical stress of the roof overburden during the mining process is recorded as σ v2(d) =k 2(d) γH, the peak horizontal stress of the vertical roadway axis is σ h12(d) =λ 12(d) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(d) =λ 22(d) γH; record the vertical stress peak value of the surrounding rock on both sides of the tunnel as σ v2(b) =k 2(b) γH, the peak horizontal stress of the vertical roadway axis is σ h12(b) =λ 12(b) γH, the peak horizontal stress parallel to the axial direction of the roadway is σ h22(b) =λ 22(b) γH; Considering the actual loading and unloading conditions of the roof coal and rock during tunneling and working face mining, a graded loading and unloading path for the roof group coal and rock specimens was designed based on the peak stress variation characteristics of the roof during tunneling and working face mining obtained from numerical simulation. Considering the actual loading and unloading conditions of the coal and rock on the side of the roadway during tunnel excavation and working face mining, the graded loading and unloading paths and loading and unloading rates of the coal and rock specimens on the side of the roadway are designed based on the peak stress change characteristics of the surrounding rocks on both sides during tunnel excavation and working face mining obtained from numerical simulation.

4. The multi-parameter combined early warning method for coal rock impact instability and failure as claimed in claim 3 is characterized by: Loading coal and rock specimens and collecting monitoring data: Connect electromagnetic radiation and acoustic emission monitoring equipment to the true triaxial loading testing machine, and arrange electromagnetic radiation and acoustic emission sensors; The coal and rock specimens of the roof group were loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data were collected simultaneously; The coal and rock specimens in the roadway group were loaded and unloaded according to the designed loading and unloading paths, and electromagnetic radiation and acoustic emission data were collected simultaneously; During the loading process, the deformation of the specimen is monitored in real time and the stress and strain curves are recorded.

5. The multi-parameter combined early warning method for coal rock instability and destruction caused by impact as claimed in claim 4 is characterized by: Classification and processing of monitoring data: The energy-count data is obtained from the acoustic emission monitoring and the acoustic emission energy b is calculated. i The value is as follows: Where m is the total number of magnitude classes; M i is the magnitude of the ith level; N i is the actual number of events in the i-th magnitude range. The relationship between magnitude and energy is as follows: Log 10 E=M When the acoustic emission b i -b i-1 <0, b i -b i+1 >0, select b i The value is the warning critical value b0; the acoustic emission b value change rate εb is defined i for: Calculation of acoustic emission fractal dimension D using GP algorithm i(AE) , the calculation formula is as follows: Where C (r) is the correlation function, r is the given scale; Definition of acoustic emission fractal dimension change ΔD i(AE) for: ΔD i(AE) =D i(AE) -D i-1(AE) Calculation of electromagnetic radiation fractal dimension D using GP algorithm i(EMR) , the calculation formula is as follows: Define the change in the fractal dimension of electromagnetic radiation ΔD i(EMR) for: ΔD i(EMR) =D i(EMR) -D i-1(EMR) The combined fractal dimension D is calculated from the fractal dimension of acoustic emission and the fractal dimension of electromagnetic radiation. i , the calculation formula is as follows: Where D max(AE) is the calculated maximum acoustic emission fractal dimension, D max(EMR) is the calculated maximum fractal dimension of electromagnetic radiation; Define the change in joint fractal dimension ΔD i(AE) for: ΔD i =D i -D i-1 。 6. The multi-parameter combined early warning method for coal rock instability and destruction caused by impact as claimed in claim 5, characterized in that: Divide each indicator into graded warning critical values: Divide the acoustic emission b value change rate εb i The critical values for graded warnings are: Divide the change of acoustic emission fractal dimension ΔD i(AE) The critical values for graded warnings are: Divide the change of electromagnetic radiation fractal dimension ΔD i(EMR) The critical values for graded warnings are: Partition joint fractal dimension change ΔD i The critical values for graded warnings are:

7. The multi-parameter combined early warning method for coal rock impact instability and failure as claimed in claim 6, characterized in that: Input the calculated warning values of the four indicators, with no impact risk as X1, weak impact risk as X2, moderate impact risk as X3, and strong impact risk as X4, to build a warning model. If all four indicators are negative, the output is safe. If one to three of the four indicators are weak and the rest are negative, a level I warning is output. If there are four weak or one to three moderate and the rest are weak or none, a Level II warning will be issued; if there are four moderate or one or more strong, a Level III warning will be issued; Corresponding to on-site projects, Level I warning indicates low risk, requiring attention to daily monitoring and recording, safety inspections, and preventive pressure relief measures; Level II warning indicates medium risk, requiring personnel control, limiting the scope of operations, increasing monitoring frequency, and conducting local pressure relief and support; Level III warning indicates high risk, requiring immediate suspension of production and activation of emergency plans, strengthening pressure relief measures, intensifying monitoring and assessment, and rectifying hidden dangers.

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