Jointed rock mass vibration wave propagation monitoring analysis and prediction method based on virtual wave source

Abstract

The application provides a joint rock mass vibration wave propagation monitoring analysis and prediction method based on a virtual wave source, relates to the technical field of geotechnical engineering, and comprises the following steps: selecting a position on the blast-approaching side of a joint rock mass as a virtual wave source point and placing a vibration velocity monitor at the virtual wave source point; selecting a plurality of monitoring points away from the blast-approaching side direction behind the virtual wave source point of the joint rock mass and placing vibration velocity monitors at the monitoring points; obtaining X, Y and Z direction vibration velocities measured by each vibration velocity monitor and selecting the maximum vibration velocities in the three directions; analyzing the joint rock mass vibration wave propagation law according to the maximum vibration velocities measured by each vibration velocity monitor and the distances from the monitoring points to the virtual wave source point; constructing a joint rock mass vibration wave propagation prediction model based on the joint rock mass vibration wave propagation law and fitting the model parameters; and predicting the maximum vibration velocities at different positions of the joint rock mass by using the joint rock mass vibration wave propagation prediction model.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering technology, and in particular to a method for monitoring, analyzing and predicting the propagation of vibration waves in jointed rock masses based on virtual wave sources. Background Technology

[0002] The propagation of vibration waves caused by blasting, earthquakes, missile explosions, mine tremors, etc. in jointed rock masses is the main cause of dynamic disasters such as rock bursts, rockfalls, instability and collapses in rock tunnels, roadways, and civil defense projects. Monitoring the propagation law of vibration waves in rock masses with different geological joints and establishing prediction models are essential for the prediction and prevention of the above-mentioned dynamic disasters.

[0003] Currently, monitoring and predicting the propagation patterns of vibration waves in jointed rock masses requires knowledge of the source energy (such as the amount of explosives used in blasting). However, the source energy of earthquakes, missile explosions, and mine tremors is difficult to obtain, making it challenging to predict the propagation characteristics of these vibration waves. This hinders the prevention and control of underground rock mass engineering disasters. Furthermore, some existing vibration wave propagation prediction models do not consider the influence of geological characteristics, have limited site applicability, and thus have low engineering applicability.

[0004] Therefore, establishing a method for monitoring, analyzing, and predicting the propagation of vibration waves in rock masses with different geological joints based on virtual wave sources has significant engineering value. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on virtual wave sources, comprising the following steps:

[0006] Step 1: Select a location on the explosion-facing side of the jointed rock mass as a virtual wave source point, and place a vibration velocity monitoring instrument at the virtual wave source point.

[0007] Step 2: Select several monitoring points behind the virtual wave source point of the jointed rock mass, away from the blast-facing side, and place vibration velocity monitoring instruments at the monitoring points.

[0008] Step 3: Obtain the vibration velocities in the X, Y, and Z directions measured by each vibration velocity monitor and select the maximum vibration velocity in the three directions.

[0009] Step 4: Analyze the propagation law of vibration waves in jointed rock mass based on the maximum vibration velocity measured by each vibration velocity monitor and the distance from each monitoring point to the virtual wave source point.

[0010] Step 5: Construct a prediction model for the propagation of vibration waves in jointed rock masses based on the propagation law of vibration waves in jointed rock masses and fit the model parameters.

[0011] Step 6: Use the jointed rock mass vibration wave propagation prediction model to predict the maximum vibration velocity at different locations in the jointed rock mass.

[0012] Optionally, step 2 specifically includes:

[0013] Several monitoring points with equal spacing and located on the same straight line are selected behind the virtual wave source point of the jointed rock mass, away from the blast-facing side.

[0014] Alternatively, several monitoring points can be selected in a straight line with gradually increasing spacing, located behind the virtual wave source point of the jointed rock mass and away from the blast-facing side.

[0015] Optionally, step 4 specifically includes:

[0016] Plot a graph showing the relationship between the maximum vibration velocity of each monitoring point and the distance from each monitoring point to the virtual wave source point, with the distance from each monitoring point to the virtual wave source point as the x-axis and the maximum vibration velocity of each monitoring point as the y-axis.

[0017] By analyzing the relationship between the maximum vibration velocity at each monitoring point and the distance from each monitoring point to the virtual wave source, it was determined that the vibration velocity at the jointed rock mass location decreases exponentially as the distance from the jointed rock mass location to the virtual wave source increases.

[0018] Optionally, step 5 specifically includes:

[0019] Based on the principle that the vibration velocity at monitoring points in jointed rock masses decreases exponentially with increasing distance from the monitoring point to the virtual wave source, a vibration wave propagation prediction model for jointed rock masses is constructed, as follows:

[0020] V max-i =ξ(D 0-i / V max-0 ) -η .

[0021] Among them, V max-i D is the predicted maximum vibration velocity value at the monitoring point. 0-i V represents the distance from the monitoring point to the virtual wave source. max-0 Let ξ be the maximum vibration velocity at the virtual wave source point, and η be the model parameters.

[0022] Based on regression fitting analysis, the correlation between ξ and η and the geological index BQ of jointed rock masses was established as follows:

[0023] ξ=a*(BQ) b +c.

[0024] η=de* (BQ).

[0025] Where a, b, c, d, and e are fitting constants;

[0026] The geological index BQ of the jointed rock mass is calculated as follows:

[0027] BQ = 100 + 3R C +250K V.

[0028] Among them, R C To measure the saturated uniaxial compressive strength of the rock mass, K V This is the rock mass integrity index.

[0029] The prediction model for vibration wave propagation in jointed rock mass containing BQ parameters is expressed as follows:

[0030] V max-i =[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] .

[0031] Optionally, when there is no condition to measure the rock mass integrity index K V At that time, based on the unit joint volume number The calculations are as follows:

[0032] when When the value is between 3 and 35, according to =L k +(H k -L k )*[1-(Jv-L J ) / (H J -L J )] to perform the calculation, where L k represent The lower limit value, H k represent The upper limit value, L J represent The lower limit value, H J represent The upper limit value, where, when When it is between 3 and 10, L k and H k They are 0.55 and 0.75 respectively, when When L is between 10 and 20, k and H k They are 0.35 and 0.55 respectively, when When L is between 20 and 35, k and H k The values ​​are 0.15 and 0.35, respectively.

[0033] when When <3, according to =0.75+[3 / (1+ )]*0.1 is used for calculation.

[0034] when When ≥35, according to =0.15*(35 / ) to perform calculations.

[0035] Optionally, the method further includes:

[0036] If the blast-facing side of the jointed rock mass is uncertain, select several monitoring points located on the same straight line with equal spacing or several monitoring points located on the same straight line with gradually increasing spacing in the jointed rock mass, and place vibration velocity monitoring instruments at the monitoring points.

[0037] Using the line connecting the two foremost monitoring points as the center line, extend the line to the left and right sides by a preset angle. Set up a preset number of virtual wave source points in front of the first monitoring point along the center line and the angles extended to the left and right sides, and place vibration velocity monitoring instruments at the virtual wave source points.

[0038] After adopting the above technical solution, the beneficial effects of the present invention are as follows:

[0039] (1) This invention provides a monitoring and analysis method for the propagation of vibration waves in rock masses with different geological joints based on virtual wave sources. It proposes a method for selecting and determining virtual wave source points, which overcomes the drawback that monitoring and predicting the propagation law of vibration waves in jointed rock masses requires knowledge of the source energy and is difficult to obtain. It provides a good method for predicting and forecasting the vibration law of engineering rock masses.

[0040] (2) This invention provides a prediction model for the propagation of vibration waves in rock masses with different geological joints based on virtual wave sources. This model overcomes the influence of the source location and geological conditions on the propagation law of vibration waves and has stronger engineering adaptability.

[0041] (3) This invention provides a corrected calculation method for the geological index BQ of rock mass, namely K V The method for determining the value of J is as follows: V Even when the difference is not significant, it still maintains good accuracy and reliability. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 The flowchart illustrates a method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on a virtual wave source, as provided in an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram showing the arrangement of virtual wave sources and monitoring points behind them when the blast-facing side of a jointed rock mass is uncertain.

[0045] Figure 3 This is a photograph of the actual rock mass used in the experiment.

[0046] Figure 4 This is a picture of the actual experimental instrument.

[0047] Figure 5 The waveform diagram of the virtual wave source point used in the experiment.

[0048] Figure 6 This is a graph showing the relationship between the maximum vibration velocity at each monitoring point of 10 yellow sandstone blocks and the distance from each monitoring point to the virtual wave source.

[0049] Figure 7 Prediction model V for vibration wave propagation of 10 blocks of yellow sandstone max-i =ξ(D 0-i / V max-0 ) -η The verification analysis diagram.

[0050] Figure 8 The model parameters for 10 blocks of yellow sandstone are ξ = a*(BQ). b Verification analysis diagram of +c.

[0051] Figure 9 The verification analysis diagram shows the model parameter η=de*(BQ) for 10 blocks of yellow sandstone.

[0052] Figure 10 Vibration wave propagation prediction model with BQ parameters for 10 blocks of yellow sandstone. max-i =[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] The verification analysis diagram.

[0053] Figure 11 This is a test diagram of a subway tunnel.

[0054] Figure 12 V is a prediction model for vibration wave propagation in jointed rock mass of a subway tunnel. max-i =ξ(D 0-i / V max-0 ) -η The verification analysis diagram. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Protection against blasting, earthquakes, missile explosions, and mine tremors is crucial, but the propagation of vibration waves generated by these events within joints is a major cause of dynamic disasters such as rock bursts, rockfalls, and instability collapses in tunnels and civil defense projects. Monitoring the propagation patterns of vibration waves in rock masses with different geological joints and establishing wave propagation prediction models are of significant engineering importance. Currently, monitoring and predicting the propagation patterns of vibration waves in jointed rock masses requires knowledge of the seismic source energy. However, the source energy of earthquakes, missile explosions, and mine tremors is difficult to obtain, and the propagation path of vibration waves is uncontrollable, hindering the prevention and control of dynamic disasters in underground rock mass engineering. Furthermore, some existing vibration wave propagation prediction models do not consider the influence of geological characteristics, and different geological structures have varying effects on vibration wave propagation, resulting in low engineering applicability of existing prediction models.

[0057] After research, the inventors proposed a monitoring and analysis method and prediction model for vibration wave propagation in jointed rock masses with different geological joints based on virtual wave sources. This method can predict the vibration velocity of jointed rock masses without considering the specific location of the seismic source, while also taking into account the influence of different geological conditions. The model parameters are simple and the model has strong engineering applicability.

[0058] like Figure 1 As shown in the figure, this invention provides a method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on virtual wave sources, comprising the following steps:

[0059] Step 1: Select a location M0 on the blast-facing side of the jointed rock mass as the virtual wave source point, and place a vibration velocity monitoring instrument at the virtual wave source point.

[0060] In this embodiment, as Figure 2 As shown, if the lateral orientation of the jointed rock mass facing the blast is uncertain, then n monitoring points M1, M2, M3, ..., M2, M3, ..., M4, located on the same straight line and with equal spacing, are first selected within the jointed rock mass. n Alternatively, select n monitoring points M1, M2, M3, ..., Mn located on the same straight line with gradually increasing spacing. n Vibration velocity monitors are placed at the monitoring points. Then, using the line connecting the two foremost monitoring points M1 and M2 as the center line, 5-7 virtual wave source points M1 are arranged in front of the first monitoring point M1, extending 20-30° to the left and right sides along the center line and the extension angle to the left and right. 01 M 02 M 07 A vibration velocity monitoring device was placed at the virtual wave source point.

[0061] Step 2: Select n monitoring points M1, M2, M3, ..., M0 behind the virtual wave source point M0 of the jointed rock mass, away from the blast-facing side. n Vibration velocity monitoring instruments were placed at the monitoring points.

[0062] In this embodiment, after determining the virtual wave source point M0, n monitoring points M1, M2, M3, ..., M2, M3, ..., M4, located on the same straight line and with equal spacing, can be selected behind the virtual wave source point M0 of the jointed rock mass in a direction away from the blast-facing side. n Alternatively, n monitoring points M1, M2, M3, ..., M can be selected behind the virtual wave source point M0 of the jointed rock mass, in a direction away from the blast-facing side, located on the same straight line with gradually increasing spacing. n .

[0063] Step 3: Obtain the vibration velocities in the X, Y, and Z directions measured by each vibration velocity monitor and select the maximum vibration velocity V in the three directions. max-i .

[0064] Step 4: Analyze the propagation law of vibration waves in jointed rock mass based on the maximum vibration velocity measured by each vibration velocity monitor and the distance from each monitoring point to the virtual wave source point.

[0065] In this embodiment, the distance D from each monitoring point to the virtual wave source point is used. 0-i The x-axis represents the maximum vibration velocity V at each monitoring point. max-i Plot the maximum vibration velocity V at each monitoring point on the vertical axis. max-i The distance D from each monitoring point to the virtual wave source point 0-i The relationship diagram, through analysis of the maximum vibration velocity V at each monitoring point, max-i The distance D from each monitoring point to the virtual wave source point 0-i The relationship diagram shows that the vibration velocity at the jointed rock mass location decreases exponentially with the increase of the distance from the jointed rock mass location to the virtual wave source.

[0066] Step 5: Construct a prediction model for the propagation of vibration waves in jointed rock masses based on the propagation law of vibration waves in jointed rock masses and fit the model parameters.

[0067] In this embodiment, based on the fact that the vibration velocity at the monitoring point of the jointed rock mass decreases exponentially with the increase of the distance from the monitoring point to the virtual wave source, a vibration wave propagation prediction model for the jointed rock mass is constructed, as follows:

[0068] V max-i =ξ(D 0-i / V max-0 ) -η .

[0069] Among them, V max-i D is the predicted maximum vibration velocity value at the monitoring point. 0-i V represents the distance from the monitoring point to the virtual wave source. max-0 Let ξ be the maximum vibration velocity at the virtual wave source point, and η be the model parameters.

[0070] Based on regression fitting analysis, the correlation between ξ and η and the geological index BQ of jointed rock masses was established as follows:

[0071] ξ=a*(BQ) b +c.

[0072] η=de* (BQ).

[0073] Where a, b, c, d, and e are fitting constants.

[0074] The geological index BQ of the jointed rock mass is calculated as follows:

[0075] BQ = 100 + 3R C +250K V .

[0076] Among them, R C To measure the saturated uniaxial compressive strength of the rock mass, K V This is the rock mass integrity index.

[0077] The prediction model for vibration wave propagation in jointed rock mass containing BQ parameters is expressed as follows:

[0078] V max-i =[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] .

[0079] When the rock mass integrity index K is unconditionally measured V At that time, based on the unit joint volume number The calculations are as follows:

[0080] when When the value is between 3 and 35, it can be followed =L k +(H k -L k )*[1-(Jv-L J ) / (H J -L J The calculation is performed to obtain L, where L is the value of L. k represent The lower limit value, H k represent The upper limit value, L J represent The lower limit value, H J represent The upper limit value, where, when When it is between 3 and 10, L k and H k They are 0.55 and 0.75 respectively, when When L is between 10 and 20, k and H k They are 0.35 and 0.55 respectively, when When L is between 20 and 35, k and H k The values ​​are 0.15 and 0.35, respectively.

[0081] when When <3, it can be followed =0.75+[3 / (1+ )]*0.1 is used for calculation.

[0082] when When ≥35, it can be followed =0.15*(35 / ) to perform calculations.

[0083] Step 6: Use the jointed rock mass vibration wave propagation prediction model to predict the maximum vibration velocity at different locations behind the virtual wave source point of the jointed rock mass.

[0084] To verify the feasibility and effectiveness of the above-mentioned method for monitoring, analyzing and predicting the propagation of vibration waves in jointed rock masses based on virtual wave sources, an experimental system was built for modeling and analysis.

[0085] (1) Selection of test rock mass

[0086] Vibration wave propagation tests were conducted on red sandstone, yellow sandstone, and granite with different mechanical properties and joint properties. The selected red sandstone, yellow sandstone, and granite with different mechanical properties and joint properties are as follows: Figure 3 As shown, the total length of the sample is 1m, representing a simulated 1m rock mass. The rock mass within 1m contains different numbers of fractures, representing different geological conditions. The saturated uniaxial compressive strength Rc of the three rock masses is also different. According to the equation BQ=100+3R C +250K V and the invention proposed The BQ values ​​of the test rock mass were adjusted according to the calculation relationship and are shown in Table 1.

[0087] Table 1 BQ values ​​of the test rock mass

[0088]

[0089] (2) Vibration wave propagation test

[0090] Test equipment such as Figure 4 As shown, an experiment was conducted by exciting vibration waves using a vibrator. The excited vibration waves originated from on-site blasting vibration monitoring data, and the waveform is as follows. Figure 5As shown. It is worth noting that this data is not from the explosion source (wave source), but rather data obtained from monitoring at a distance of approximately 20m from the explosion source (wave source). Therefore, it can be used as virtual wave source point data for analysis. Monitoring points were selected as described in the above embodiment. During the experiment, waveform and vibration velocity data at each monitoring point were acquired using wave vibration sensors.

[0091] (3) Analysis of the propagation law of vibration waves

[0092] Taking 10 blocks of yellow sandstone as an example, three sets of vibration monitoring data were obtained, and a graph showing the relationship between the maximum vibration velocity at each monitoring point and the distance from each monitoring point to the virtual wave source was plotted. Figure 6 As shown in the figure, the maximum vibration velocity V at each monitoring point behind the virtual wave source point is... max-i Both are less than the maximum vibration velocity V of the virtual wave source point M0. max-0 Furthermore, as the actual distance between the monitoring point and the virtual wave source increases, the maximum vibration velocity V at the monitoring point also increases. max-i It exhibits an approximately exponential decay. Taking the data from test group 3 as an example, the maximum vibration velocity V at the virtual wave source point... max-0 The maximum vibration velocity V at monitoring point M1, which is 4.17 cm / s and located 0.05 m from the virtual wave source M0, is 4.17 cm / s. max-1 The maximum vibration velocity V at monitoring point M2, which is 2.38 cm / s and located 0.15 m from the virtual wave source M0, is 2.38 cm / s. max-2 The maximum vibration velocity V at monitoring point M6, which is 1.76 cm / s and located 0.85 m from the virtual wave source M0, is 1.76 cm / s. max-6 The velocity was 0.96 cm / s. Simultaneously, the maximum vibration velocity V at the virtual wave source point M0 was also found. max-0 The larger the value, the more monitoring points M1, M2, M3, ..., M behind it. n Maximum vibration velocity V max-i It is also relatively larger.

[0093] (4) Vibration wave propagation prediction model

[0094] Taking 10 blocks of yellow sandstone as an example, the vibration wave propagation prediction model V was analyzed. max-i =ξ(D 0-i / V max-0 ) -η Numerical fitting was performed to obtain the vibration wave propagation prediction model V. max-i =0.529(D 0-i / V max-0 ) -0.324 The vibration wave propagation prediction model was validated and analyzed using actual data, and the results are as follows: Figure 7 As shown, the R value of the vibration wave propagation prediction model can be seen. 2 =0.936, indicating that the vibration wave propagation prediction model V proposed in this invention is adopted. max-i =ξ(D 0-i / V max-0 ) -η It has good practical value in engineering.

[0095] Furthermore, regarding the model parameters ξ=a*(BQ) b Numerical fitting of +c and η=de* (BQ) yields the model parameters ξ=1.745*(BQ). -3.39 +0.227 and η=0.583-6.67e-4*(BQ), the model parameters were validated and analyzed using actual data, and the results are as follows. Figure 8 and Figure 9 As shown, the R values ​​of the model parameters ξ and η are known. 2 =0.955, R 2 =0.982, indicating that the model parameter ξ = 1.745*(BQ) -3.39 +0.227 and η=0.583-6.67e-4*(BQ) are strongly correlated with the rock mass in which the vibration wave propagates.

[0096] Set the model parameter ξ = 1.745*(BQ) -3.39 Substituting +0.227 and η=0.583-6.67e-4*(BQ) into V max-i =ξ(D 0-i / V max-0 ) -η The vibration wave propagation prediction model V containing BQ parameters is obtained. max-i =[1.745e8*(BQ) -3.39 +0.227](D 0-i / V max-0 ) -[0.583-6.67e-4*(BQ)] To compare the vibration wave propagation prediction model V max-i =0.529(D 0-i / V max-0 ) -0.324 Vibration wave propagation prediction model V with BQ parameters max-i =[1.745e8*(BQ) -3.39 +0.227](D 0-i / V max-0 ) -[0.583-6.67e-4*(BQ)] To compare the accuracy differences between the two vibration wave propagation prediction models, taking 10 pieces of yellow sandstone as an example, the accuracy of the two models is compared. Figure 10 It can be seen that the vibration wave propagation prediction model V, which includes BQ parameters, is used. max-i =[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] Although the prediction accuracy is slightly reduced, it still has good accuracy, while the vibration wave propagation prediction model V containing BQ parameters... max-i=[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] The advantages are significant, particularly in saving data from monitoring points; the vibration velocity V behind the virtual wave source can be determined solely based on the geological index BQ of the jointed rock mass. max-i Making predictions is of great engineering and economic significance for cost savings in the early stages of project construction and for long-term monitoring.

[0097] To further illustrate the effects of the embodiments of the present invention, blasting vibrations in a subway tunnel were collected and analyzed. The on-site test setup was as follows: Figure 11 As shown, the first measuring point at the distance from the explosion source is taken as the virtual wave source point, and the vibration wave propagation prediction model V is based on field test data. max-i =ξ(D 0-i / V max-0 ) -η The calculation was performed, and the result is as follows: Figure 12 As shown, the R value of the vibration wave propagation prediction model can be seen. 2 The value of 0.944 indicates that the vibration wave propagation prediction model V max-i =ξ(D 0-i / V max-0 ) -η The prediction accuracy is high.

[0098] Although the present invention has been disclosed above with reference to embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications and refinements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on virtual wave sources, characterized in that, Includes the following steps: Step 1: Select a location on the blast-facing side of the jointed rock mass as a virtual wave source point, and place a vibration velocity monitoring instrument at the virtual wave source point; Step 2: Select several monitoring points behind the virtual wave source point of the jointed rock mass, away from the blast-facing side, and place vibration velocity monitoring instruments at the monitoring points; Step 3: Obtain the vibration velocities in the X, Y, and Z directions measured by each vibration velocity monitor and select the maximum vibration velocity in the three directions; Step 4: Analyze the propagation law of vibration waves in jointed rock mass based on the maximum vibration velocity measured by each vibration velocity monitor and the distance from each monitoring point to the virtual wave source point; Step 5: Construct a vibration wave propagation prediction model for jointed rock masses based on the propagation law of jointed rock masses and fit the model parameters; Specifically, it includes: Based on the principle that the vibration velocity at monitoring points in jointed rock masses decreases exponentially with increasing distance from the monitoring point to the virtual wave source, a vibration wave propagation prediction model for jointed rock masses is constructed, as follows: V max-i =ξ(D 0-i / V max-0 ) -η ; Among them, V max-i D is the predicted maximum vibration velocity value at the monitoring point. 0-i V represents the distance from the monitoring point to the virtual wave source. max-0 ξ represents the maximum vibration velocity at the virtual wave source point, and η represents the model parameters. Based on regression fitting analysis, the correlation between ξ and η and the geological index BQ of jointed rock masses was established as follows: ξ=a*(BQ) b +c; η=de* (BQ); Where a, b, c, d, and e are fitting constants; The geological index BQ of the jointed rock mass is calculated as follows: BQ=100+3R C +250K V ; Among them, R C To measure the saturated uniaxial compressive strength of the rock mass, K V This is the measured rock mass integrity index; The prediction model for vibration wave propagation in jointed rock mass containing BQ parameters is expressed as follows: V max-i =[a*(BQ) b +c](D 0-i / V max-0 ) -[d-e*(BQ)] ; Step 6: Use the jointed rock mass vibration wave propagation prediction model to predict the maximum vibration velocity at different locations in the jointed rock mass.

2. The method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on a virtual wave source, as described in claim 1, is characterized in that... Step 2 specifically includes: Several monitoring points with equal spacing and located on the same straight line are selected behind the virtual wave source point of the jointed rock mass, away from the blast-facing side; Alternatively, several monitoring points can be selected in a straight line with gradually increasing spacing, located behind the virtual wave source point of the jointed rock mass and away from the blast-facing side.

3. The method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on a virtual wave source, as described in claim 1, is characterized in that... Step 4 specifically includes: Plot a graph showing the relationship between the maximum velocity of each monitoring point and the distance from each monitoring point to the virtual wave source point, with the distance from each monitoring point to the virtual wave source point as the x-axis and the maximum vibration velocity of each monitoring point as the y-axis. By analyzing the relationship between the maximum vibration velocity at each monitoring point and the distance from each monitoring point to the virtual wave source, it was determined that the vibration velocity at the jointed rock mass location decreases exponentially as the distance from the jointed rock mass location to the virtual wave source increases.

4. The method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on a virtual wave source, as described in claim 1, is characterized in that... When the rock mass integrity index K is unconditionally measured V At that time, based on the unit joint volume number The calculations are as follows: when When the value is between 3 and 35, according to =L k +(H k -L k )*[1-(Jv-L J ) / (H J -L J )] to perform the calculation, where L k represent The lower limit value of H k represent The upper limit of L J represent The lower limit value of H J represent The upper limit of, where, when 3 < When ≤10, L k and H k They are 0.55 and 0.75 respectively, when 10 < When ≤20, L k and H k They are 0.35 and 0.55 respectively, when 20 < When ≤35, L k and H k They are 0.15 and 0.35 respectively; when When <3, according to =0.75+[3 / (1+ )]*0.1 is used for calculation; when >35, according to =0.15*(35 / ) to perform calculations.

5. A method for monitoring, analyzing, and predicting the propagation of vibration waves in jointed rock masses based on a virtual wave source, as described in any one of claims 1, 3, and 4, characterized in that, The method further includes: If the blast-facing side of the jointed rock mass is uncertain, select several monitoring points located on the same straight line with equal spacing or select several monitoring points located on the same straight line with gradually increasing spacing in the jointed rock mass, and place vibration velocity monitoring instruments at the monitoring points. Using the line connecting the two foremost monitoring points as the center line, extend the line to the left and right sides by a preset angle. Set up a preset number of virtual wave source points in front of the first monitoring point along the center line and the angles extended to the left and right sides, and place vibration velocity monitoring instruments at the virtual wave source points.

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