Multi-source dynamic disturbance rockburst combined support prevention and control system and method

Abstract

The invention provides a multi-source dynamic disturbance rockburst combined support prevention and control system and method, and relates to the technical field of rockburst disaster prevention and control, the system comprises stress release holes, wave-absorbing grouting holes, energy-absorbing anchor rods and a passive pressure-bearing structure; the stress release holes are formed in a rockburst high-risk area of the tunnel surrounding rock; the wave-absorbing grouting holes are distributed around the rockburst high-risk area in a staggered mode, the wave-absorbing grouting holes are filled with wave-absorbing grouting materials, and a three-dimensional wave-absorbing grouting area is formed; the energy-absorbing anchor rod is arranged in the three-dimensional wave-absorbing grouting area; the passive pressure-bearing structure comprises a quick-setting concrete layer, a concrete layer containing rubber particles, a steel arch and a steel fiber concrete layer, the concrete layer containing rubber particles is arranged behind the reinforcing mesh, the steel arch is arranged behind the concrete layer containing rubber particles, and steel fiber concrete is arranged behind the steel arch. By constructing the pressure relief-wave absorption-energy absorption-passive pressure bearing four-stage combined supporting system, the safety and adaptability of the supporting system for the rockburst high-risk area are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of rockburst disaster prevention and control technology, and more specifically, to a multi-source dynamic disturbance rockburst combined support and control system and method. Background Technology

[0002] As underground engineering projects continue to advance deeper, the stress level of the surrounding rock increases dramatically, highlighting the risk of high-stress disasters. During the construction and operation of deep-buried tunnels and deep underground caverns, multi-source dynamic disturbances, such as those caused by blasting, frequently occur, making rockbursts triggered by these disturbances highly likely. Dynamically disturbed rockbursts are characterized by their suddenness, high intensity, and wide impact range. Their occurrence mechanism is controlled by the coupling of multiple factors, including stress fields and disturbance fields. Their spatial location is difficult to accurately determine in advance, and real-time warnings are challenging, posing significant risks to tunnel construction and operation.

[0003] Dynamic rockbursts pose higher demands on support systems. Traditional support and control systems and methods are mostly based on passive support and empirical calculations. In situations where high-risk rockburst zones cannot be accurately identified, surrounding rock energy is difficult to release effectively, external energy input cannot be controlled, and passive energy absorption capacity is limited, traditional support measures lacking specificity not only have low support efficiency and poor support effect, but also cannot withstand the effects of dynamic disturbances continuously.

[0004] Based on the shortcomings of the existing technologies, there is an urgent need for a multi-source dynamic disturbance rockburst joint support and control system and method. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-source dynamic disturbance rockburst combined support and control system and method to improve the above-mentioned problems. To achieve the above objective, the technical solution adopted by this invention is as follows: In a first aspect, this application provides a multi-source dynamic disturbance rockburst joint support and control system, comprising: stress relief holes, wave-absorbing grouting holes, energy-absorbing anchors, and a passive pressure-bearing structure; the stress relief holes are located in the high-risk rockburst zone of the tunnel surrounding rock; the wave-absorbing grouting holes are staggered around the high-risk rockburst zone, and the wave-absorbing grouting holes are filled with wave-absorbing grouting material to form a three-dimensional wave-absorbing grouting area; the energy-absorbing anchors are located within the three-dimensional wave-absorbing grouting area; the passive pressure-bearing structure includes a quick-setting concrete layer, a steel mesh, a sprayed rubber-particle-containing concrete layer, a steel arch, and a supplementary sprayed steel fiber concrete layer; the quick-setting concrete layer is located after the wave-absorbing grouting holes, the steel mesh is located after the energy-absorbing anchors, the rubber-particle-containing concrete layer is located after the steel mesh, the steel arch is located after the rubber-particle-containing concrete layer, and the steel fiber concrete layer is located after the steel arch.

[0006] Furthermore, the steel arch frame is an arc-shaped steel structure that matches the profile of the tunnel cross section.

[0007] Furthermore, the microwave absorbing grouting material is cement mortar with added rubber particles, foaming agent and polyacrylonitrile fiber.

[0008] Furthermore, the thickness of the quick-setting concrete layer is 2 cm.

[0009] Furthermore, the thickness of the rubber particle-containing concrete layer is 5 cm.

[0010] Furthermore, the diameter of the absorbing grouting hole is 35mm.

[0011] Secondly, this application provides a method for controlling rockburst using multi-source dynamic disturbance combined support, including: Acquire data on surrounding rock stress state, microseismic event monitoring data, historical disturbance event records, and support system database information; Based on the stress state data of the surrounding rock and the microseismic event monitoring data, stress concentration areas are identified and processed to determine the location of high-risk rockburst zones. Based on the location of the high-risk rockburst zone, the historical disturbance event records, and the support system database information, a disturbance rockburst support test was conducted. By constructing a numerical model, the response of different support measures under the conditions of energy accumulation degree and disturbance parameter combination was simulated, and the mapping relationship between the energy accumulation characteristics of the surrounding rock and the support parameters was obtained. Based on the mapping relationship, a BP neural network model and weight optimization are performed to construct a support decision model. Real-time support decision processing is performed based on the support decision model. By inputting real-time monitoring data, the optimal support form and parameter combination are output.

[0012] The beneficial effects of this invention are as follows: This invention constructs a four-level combined support system of pressure relief, wave absorption, energy absorption, and passive pressure bearing. It combines a rockburst risk zone location method based on the fusion of microseismic monitoring and numerical simulation, a surrounding rock state-disturbance condition classification mechanism, and a BP neural network weighted feedback optimization decision model to form a precise response capability to multi-source dynamic disturbances such as blasting disturbances, TBM disturbances, and rockburst events. This enables dynamic control of disturbance energy and significantly improves the safety and adaptability of the support system in high-risk rockburst areas. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the structure of the multi-source dynamic disturbance rockburst joint support and control system; Figure 2 This is a cross-sectional view of a high-risk rockburst zone; Figure 3 Numerical simulation diagram of the stress concentration area; Figure 4 This is a flowchart of the multi-source dynamic disturbance rockburst combined support and control method.

[0015] The markings in the diagram are: 1. High-risk area for rockburst; 2. Stress relief hole; 3. Wave-absorbing grouting hole; 4. Energy-absorbing anchor; 5. Quick-setting concrete layer; 6. Steel arch frame; 7. Concrete layer containing rubber particles; 8. Reinforcing mesh; 9. Steel fiber reinforced concrete layer. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0017] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0018] Example 1: like Figure 1 and Figure 2As shown, this embodiment provides a multi-source dynamic disturbance rockburst joint support and control system, which includes: stress relief holes 2, microwave absorbing grouting holes 3, energy-absorbing anchor bolts 4, and a passive pressure-bearing structure; the stress relief holes 2 are set in the high-risk rockburst zone 1 of the tunnel surrounding rock, and actively release stress by forming a micro-fracture network through drilling or microwave fracturing; the microwave absorbing grouting holes 3 are staggered around the high-risk rockburst zone 1, and the microwave absorbing grouting holes 3 are filled with microwave absorbing grouting material to form a three-dimensional microwave absorbing grouting area to attenuate disturbance waves; the energy-absorbing anchor bolts 4 are set in the three-dimensional microwave absorbing grouting area. Within the grouting area, the bearing capacity of the surrounding rock is enhanced. The passive pressure-bearing structure includes a quick-setting concrete layer 5, a reinforcing mesh 8, a rubber-particle-containing concrete layer 7, a steel arch frame 6, and a steel fiber reinforced concrete layer 9. The quick-setting concrete layer 5 is placed after the aforementioned wave-absorbing grouting holes 3, the reinforcing mesh 8 is placed after the aforementioned energy-absorbing anchors 4, the rubber-particle-containing concrete layer 7 is placed after the reinforcing mesh 8, the steel arch frame 6 is placed after the rubber-particle-containing concrete layer 7, and the steel fiber reinforced concrete layer 9 is placed after the steel arch frame 6, forming a composite protection system of layered dissipation and rigid support. Among them, the quick-setting concrete layer 5 is the initial shotcrete, the rubber-particle-containing concrete layer 7 is the shotcrete layer, and the steel fiber reinforced concrete layer 9 is the supplementary shotcrete layer.

[0019] Each component constructs a three-dimensional prevention and control mechanism through spatial positioning and functional integration, solving the industry pain points of traditional support being passive, inefficient, and unable to resist multi-source power disturbances.

[0020] Furthermore, the steel arch frame 6 is an arc-shaped steel structure that matches the profile of the tunnel cross section.

[0021] Furthermore, the absorbing grouting material is cement mortar containing rubber particles, foaming agent and polyacrylonitrile fiber.

[0022] Furthermore, the thickness of the rubber particle-containing concrete layer 7 is 5 cm.

[0023] Furthermore, the diameter of the absorbing grouting hole 3 is 35mm.

[0024] Example 2:

[0025] Corresponding to the above embodiment of the multi-source dynamic disturbance rockburst combined support and control system, this embodiment provides a multi-source dynamic disturbance rockburst combined support and control method, such as... Figure 4 As shown, steps S100 to S500 are included: Step S100: Obtain surrounding rock stress state data, microseismic event monitoring data, historical disturbance event records, and support system database information; Understandably, the surrounding rock stress state data refers to the stress state data of some points obtained from on-site monitoring. The microseismic event monitoring data includes the frequency, magnitude, and spatial distribution information of microseismic events monitored by microseismic equipment. The historical disturbance event record covers various disturbances that have occurred in the tunnel: for single-tunnel tunnels, this specifically includes disturbance events such as blasting at the tunnel face and blasting of connecting tunnels; for twin-tunnel tunnels, blasting events of the preceding and following tunnels must be recorded; it also includes a complete record of rockburst events occurring at any part of the tunnel, as well as strong disturbance events such as earthquakes. The support system database contains a complete set of technical parameters for a predefined four-level collaborative support system: pressure relief, wave absorption, energy absorption, and passive bearing. This includes the borehole diameter / spacing / range and microwave power parameters for borehole / microwave fracturing pressure relief measures; the required diameter for the wave-absorbing grouting system; the grouting hole layout rules and the ratio of rubber particles, foaming agent, and polyacrylonitrile fiber combined wave-absorbing materials; the type / quantity / energy absorption level configuration of anchors / cables in active energy-absorbing components; the construction standards for passive bearing structures including a 2cm thick initial sprayed quick-setting concrete layer; the construction standards for a 5cm thick concrete layer containing rubber particles; the construction standards for supplementary sprayed steel fiber concrete layers; and the steel arch frame model / sprayed concrete model, thickness, and steel mesh configuration rules. By systematically storing the core technical indicators of the four-level support measures, it provides structured data support for subsequent decision-making.

[0026] Step S200: Based on the surrounding rock stress state data and microseismic event monitoring data, stress concentration areas are identified to determine the location of high-risk rockburst zones; It should be noted that this step interactively verifies the spatial correlation between the stress field distribution characteristics of the surrounding rock excavation and microseismic events, accurately locates stress concentration areas, and outputs spatial location markers for high-risk rockburst zones. The numerical simulation diagram of the stress concentration area is shown below. Figure 3 As shown, Figure 3 The red area in the middle is the stress concentration area.

[0027] Step S300: Based on the location of high-risk rockburst zones, historical disturbance event records, and support system database information, conduct disturbance rockburst support tests. By constructing a numerical model, simulate the response of different support measures under the conditions of energy accumulation degree and disturbance parameter combination, and obtain the nonlinear mapping law between surrounding rock energy accumulation characteristics and support parameters. Understandably, this step defines various working conditions based on the degree of energy accumulation (energy accumulation zone / high energy accumulation zone) and the combination of disturbance parameters. The corresponding support procedures are executed in the numerical model, and the coupled response of the surrounding rock stress field parameters, disturbance wave parameters and support measure parameters is recorded to establish the mapping relationship between the energy accumulation characteristics of the surrounding rock and the support parameters.

[0028] Step S400: Based on the mapping relationship, perform BP neural network modeling and weight optimization to construct the support decision model; It should be noted that this step uses a BP neural network architecture to transform engineering experience into a computable model, and achieves adaptive iterative optimization of support parameters through a dynamic feedback mechanism of weights, forming an intelligent decision-making core with controllable error.

[0029] Step S500: Perform real-time support decision processing based on the support decision model. By inputting real-time monitoring data, output the most suitable support form and parameter combination.

[0030] Understandably, this step combines real-time disturbance waveform analysis with surrounding rock condition perception to drive the intelligent model to generate a dynamic ratio scheme for the four-level support system, thereby achieving precise matching between disturbance source characteristics and control measures.

[0031] Further, step S200 includes steps S210 to S220.

[0032] Step S210: Perform numerical simulation processing of surrounding rock excavation based on the surrounding rock stress state data, and obtain the distribution characteristics of the surrounding rock excavation stress field through simulation calculation; Step S220: Based on the distribution characteristics, and combined with the frequency, magnitude and spatial distribution data of microseismic events monitored by the microseismic equipment, stress concentration areas are identified. Through interactive verification, the distribution characteristics of the stress concentration areas in the surrounding rock are determined, and the location of the high-risk rockburst zone is obtained.

[0033] Specifically, the above process first analyzes the stress state of the surrounding rock at the on-site monitoring points and extracts the stress distribution patterns at discrete points. Then, based on this data, it drives numerical simulation to deduce the global evolution characteristics of the stress field induced by the surrounding rock excavation process. Finally, it integrates multi-dimensional parameters such as microseismic event frequency, magnitude, and spatial distribution, and through cross-verification of the coupling relationship between stress field distribution and microseismic activity space, analyzes the three-dimensional configuration of the stress concentration zone in the surrounding rock, thereby pinpointing the spatial coordinates of the high-risk rockburst zone. This process assimilates point monitoring, full-field simulation, and fracture response data, overcoming the limitations of traditional single-method localization.

[0034] Further, step S300 includes steps S310 to S330.

[0035] Step S310: Define the support test condition treatment based on the degree of energy accumulation and the combination of disturbance parameters. Establish the simulated support principle by determining the energy accumulation zone level and the combination of disturbance parameters of the rockburst risk section. Step S320: Implement support measures according to the simulated support principle, and obtain the execution results by implementing the corresponding support procedures in the numerical model; Step S330: Process the surrounding rock response record based on the results of the support measures. By recording the response relationship between the surrounding rock stress field parameters, disturbance wave parameters and support measure parameters in the numerical simulation, obtain the mapping relationship.

[0036] Specifically, based on the combination relationship between the energy accumulation degree (energy accumulation zone / high energy accumulation zone) and disturbance parameters (low amplitude / high amplitude disturbance) of the rockburst risk section, the support principles for working conditions A1-A4 are analytically defined, and the prevention and control guidelines under different surrounding rock conditions and disturbance coupling states are established; the simulated support principle for disturbed rockburst is as follows: Type A1 working condition definition: A scenario combining energy accumulation zones and frequent low-amplitude disturbances, characterized by the development of micro-fractures at the rockburst risk section, relatively concentrated stress, and low energy release from rockbursts; the rockburst risk section is far from the tunnel face, resulting in minimal blasting disturbance at the tunnel face, and there is no impact from severe disturbances such as adjacent tunnel blasting. Treatment principle: Maintain the stability of the surrounding rock.

[0037] Type A2 working condition definition: A scenario combining energy accumulation zones and frequent high-amplitude disturbances, characterized by the development of micro-fractures at the rockburst risk section, relatively concentrated stress, and low rockburst energy release; the rockburst risk section is close to the tunnel face, and high-energy disturbances such as adjacent tunnel blasting and earthquakes occur frequently. Treatment principle: Reduce external disturbances and increase the absorbing grouting range.

[0038] Type A3 working condition definition: A scenario combining high-energy accumulation zones and frequent low-amplitude disturbances. Its characteristics include well-developed micro-fractures at the rockburst risk section, high stress concentration, and high rockburst energy release; the rockburst risk section is far from the tunnel face, resulting in minimal blasting disturbance at the tunnel face, and there is no impact from severe disturbances such as adjacent tunnel blasting. Treatment principle: Increase stress release and reduce energy accumulation.

[0039] Type A4 working condition definition: A scenario combining high-energy accumulation zones and frequent high-amplitude disturbances, characterized by well-developed micro-fractures at the rockburst risk section, high stress concentration, and high rockburst energy release; the rockburst risk section is close to the tunnel face, and high-energy disturbances such as adjacent tunnel blasting and earthquakes occur frequently. Treatment principle: Reduce external disturbances while releasing energy, and increase passive support.

[0040] The corresponding support measures are as follows: For type A1 working conditions: Drill small-range stress relief holes at high intervals, inject microwave absorbing grouting material, drill ordinary medium-hole grouting anchors, and spray concrete.

[0041] For type A2 working condition: Drill small-range stress relief holes at high intervals, inject microwave absorbing grouting material, continue to drill multiple microwave absorbing grouting holes and inject microwave absorbing grouting material, drill ordinary medium-hole grouting anchor rods, first spray a layer of microwave absorbing grouting concrete, and then spray ordinary / steel fiber concrete.

[0042] For the A3 type working condition: Drill multiple stress relief holes at low intervals, use microwave stress relief technology, inject microwave absorbing grouting material, install high-energy energy-absorbing anchors, set up steel arch frames, and spray ordinary / steel fiber concrete.

[0043] For the A4 type working condition: Drill multiple stress relief holes at low intervals, use microwave stress relief technology, inject microwave absorbing grouting material, continue to drill multiple microwave absorbing grouting holes and inject microwave absorbing grouting material, install high-energy energy-absorbing anchors, set up steel arch frames, and spray ordinary / steel fiber concrete.

[0044] Furthermore, numerical models were used to conduct disturbance rockburst support tests on the stress concentration zone, disturbance characteristics, and support measures of the tunnel. Based on the test results, the mapping relationship between the surrounding rock stress field parameters, disturbance characteristic parameters, and support measures was established, as well as the energy accumulation characteristics of the surrounding rock under different support conditions.

[0045] Among them, the surrounding rock parameters in the stress concentration zone include cohesion, internal friction angle, elastic modulus, Poisson's ratio, etc.; the stress field parameters include the maximum principal stress, intermediate principal stress, minimum principal stress, and the three principal stress directions; the disturbance wave characteristic parameters include the disturbance wave frequency, amplitude, and duration.

[0046] The support measures parameters include the diameter, spacing, and range of stress relief holes; microwave-induced stress relief power; depth and range of microwave absorbing grouting holes; number of energy-absorbing anchors; type and thickness of shotcrete; and type of steel mesh and steel arch frame.

[0047] Finally, by recording the numerical simulation results—that is, the support system with the fewest procedures used while ensuring no rockburst failure—the correspondence between the parameters of the potential rockburst risk zone and the parameters of the support measures is obtained.

[0048] Further, step S400 includes steps S410 to S430.

[0049] Step S410: Perform initial neural network modeling based on the mapping relationship. By establishing initial synaptic weight connections from the input layer to the output layer, the initial support decision model is obtained. Step S420: Perform error analysis processing based on the output results of the initial support decision model. By comparing the difference between the actual output value and the expected output value, obtain the error distribution data of the output layer. Step S430: Perform synaptic weight optimization processing based on the output layer error distribution data, and iteratively correct the weights and thresholds through the backpropagation algorithm until the global error converges, thereby obtaining the optimal connection weight support decision model.

[0050] Specifically, the parameters of the rockburst risk zone are input into the input layer of a BP neural network, processed by the neuron connection weights, and output to the output layer to obtain preliminary values ​​for support measures and parameters; the specific expression is: ; in, This is the input signal representing the parameters of the rockburst tunnel. These are the synaptic weights of neurons. It is the number of neurons in the input layer. It's a bias. It is an activation function. It is an output signal that indicates the support measures and parameters. , This represents the number of neurons.

[0051] Preferably, after obtaining the preliminary values ​​of the flexible network parameters in the BP neural network, the method further includes the following steps: The output of the BP neural network is compared with the test sample and the error is analyzed. If the error does not meet the requirements, it is propagated back to the input layer through the neuron connection, and the connection weights are corrected through the neurons. The connection weights are continuously corrected until the error meets the requirements.

[0052] Preferably, the step of comparing the output of the BP neural network with the test sample and analyzing the error, and if the error does not meet the requirements, propagating back to the input layer through neuron connections, and correcting the connection weights through neurons, continuously correcting the connection weights until the error meets the requirements, includes the following steps: Obtaining the input of the hidden layer of a BP neural network The specific expression is: ; in, For input layer nodes To hidden layer nodes The weights, For input signals; The input to the hidden layer of the BP neural network is processed to obtain the output of the hidden layer. The specific expression is as follows: ; in, For activation function, Hidden layer nodes The threshold, This represents the output of the hidden layer.

[0053] The output of the hidden layer of the BP neural network Input / output layer, output The specific expression is: ; in, Hidden layer nodes To the output layer node The weights, Hidden layer nodes The output, The threshold value for the output layer nodes. For output layer nodes The actual output value; The output error is obtained by the difference between the expected output and the actual output value of the BP neural network. The specific expression is as follows: ; in, For output layer nodes The expected output value, The number of nodes in the output layer. Indicates the output error; By adjusting the weights and thresholds of the BP neural network, the optimal actual output value is obtained, and the optimal output error is obtained through the optimal actual output value. The adjusted weights and thresholds are as follows: ; Through the optimal output error The global error is obtained using the following expression: ; in, For learning rate, The gradient values ​​of the output layer neurons. The gradient values ​​of the hidden layer neurons are... To adjust the hidden layer nodes To the output layer node The weights, For the adjusted input layer nodes To hidden layer nodes The weights, To adjust the output layer nodes The threshold, To adjust the hidden layer nodes The threshold.

[0054] Further, step S500 includes steps S510 to S530.

[0055] Step S510: Based on the real-time monitoring data and the construction organization design prediction data, perform disturbance feature identification processing. By analyzing the waveforms of blasting at the working face, TBM vibration, or rockburst events, obtain the real-time disturbance waveform parameters. Step S520: Perform surrounding rock state-disturbance coupling analysis based on real-time disturbance waveform parameters and rockburst prevention and control decision model. By inputting disturbance waveform parameters and surrounding rock characteristics into neural network model for calculation, the preliminary parameter combination of pressure relief-wave absorption-energy absorption-passive pressure support is obtained. Step S530: Perform dynamic configuration processing of the support system based on the preliminary parameter combination. By calling the parameterized combination rules of pressure relief, wave absorbing grouting, energy absorbing anchors, steel arch frames and concrete spraying in the support system library, output the support form and parameter combination.

[0056] Understandably, steps S510 to S530 achieve a dynamic decision-making closed loop for rockburst prevention and control: First, based on the construction organization design prediction data, the waveform characteristics of the face blasting / TBM vibration / rockburst events are analyzed to extract the real-time disturbance frequency, amplitude, and duration; then, the disturbance parameters and surrounding rock characteristics are input into the support decision model, driving the neural network to perform coupled analytical calculations of surrounding rock state and disturbance, generating a preliminary parameter combination of a four-level system: pressure relief (drilling / microwave fracturing), wave absorption (three-dimensional grouting network), energy absorption (anchor bolt placement), and passive pressure bearing (steel mesh, steel arch frame, shotcrete composite structure); finally, the parameterized rules in the support system library are called to dynamically optimize the borehole diameter, grouting range, number of anchor bolts, steel arch frame model, and concrete model and thickness, outputting a support form and parameter execution scheme adapted to the real-time disturbance characteristics.

[0057] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-source dynamic disturbance rockburst combined support and control system, characterized in that, include: Stress relief hole (2), the stress relief hole (2) is set in the rock burst high risk zone (1) of the surrounding rock of the tunnel; The absorbing grouting holes (3) are arranged in an alternating pattern around the rockburst high-risk zone (1). The absorbing grouting holes (3) are filled with absorbing grouting material and form a three-dimensional absorbing grouting area. Energy-absorbing anchor (4), wherein the energy-absorbing anchor (4) is disposed within the three-dimensional wave-absorbing grouting area; and The passive pressure-bearing structure includes a quick-setting concrete layer (5), a steel mesh (8), a rubber particle concrete layer (7), a steel arch frame (6), and a steel fiber concrete layer (9). The quick-setting concrete layer (5) is located after the above-mentioned wave-absorbing grouting hole (3). The steel mesh (8) is located after the above-mentioned energy-absorbing anchor (4). The rubber particle concrete layer (7) is located after the steel mesh (8). The steel arch frame (6) is located after the rubber particle concrete layer (7). The steel fiber concrete layer (9) is located after the steel arch frame (6).

2. The multi-source dynamic disturbance rockburst combined support and control system according to claim 1, characterized in that: The steel arch frame (6) is an arc-shaped steel structure that matches the profile of the tunnel cross section.

3. The multi-source dynamic disturbance rockburst combined support and control system according to claim 1, characterized in that: The microwave absorbing grouting material is cement mortar containing rubber particles, foaming agent and polyacrylonitrile fiber.

4. The multi-source dynamic disturbance rockburst combined support and control system according to claim 1, characterized in that: The thickness of the quick-setting concrete layer (5) is 5 cm.

5. The multi-source dynamic disturbance rockburst combined support and control system according to claim 1, characterized in that: The diameter of the absorbing grouting hole (3) is 35 mm.

6. A method for controlling rockburst using multi-source dynamic disturbance combined support, characterized in that, The method uses the multi-source dynamic disturbance rockburst combined support and control system according to any one of claims 1-5, and the method includes: Acquire data on surrounding rock stress state, microseismic event monitoring data, historical disturbance event records, and support system database information; Based on the surrounding rock stress state data and the microseismic event monitoring data, stress concentration areas are identified to determine the location of high-risk rockburst zones. Based on the location of the high-risk rockburst zone, the historical disturbance event records, and the support system database information, a disturbance rockburst support test was conducted. By constructing a numerical model, the response of different support measures under the conditions of energy accumulation degree and disturbance parameter combination was simulated, and the mapping relationship between the energy accumulation characteristics of the surrounding rock and the support parameters was obtained. Based on the mapping relationship, a BP neural network model and weight optimization are performed to construct a support decision model. Real-time support decision processing is performed based on the support decision model. By inputting real-time monitoring data, the optimal support form and parameter combination are output.

7. The method for combined support and control of rockburst caused by multi-source dynamic disturbance according to claim 6, characterized in that, Based on the surrounding rock stress state data and the microseismic event monitoring data, stress concentration areas are identified to determine the locations of high-risk rockburst zones, including: Numerical simulation processing of tunnel excavation is performed based on the surrounding rock stress state data, and the distribution characteristics of the surrounding rock excavation stress field are obtained through simulation calculation. Based on the distribution characteristics, stress concentration areas are identified by combining the frequency, magnitude, and spatial distribution data of microseismic events in the microseismic event monitoring data. Through interactive verification, the distribution characteristics of the stress concentration areas in the surrounding rock are determined, and the location of high-risk rockburst zones is obtained.

8. The method for combined support and control of rockburst caused by multi-source dynamic disturbance according to claim 6, characterized in that, Based on the location of the high-risk rockburst zone, the historical disturbance event records, and the support system database information, disturbance rockburst support tests were conducted. Numerical models were constructed to simulate the response of different support measures under varying energy accumulation levels and combinations of disturbance parameters. The mapping relationship between surrounding rock energy accumulation characteristics and support parameters was obtained, including: The working conditions for the support test are defined based on the degree of energy accumulation and the combination of disturbance parameters. By determining the energy accumulation zone level and the combination of disturbance amplitude and frequency of the rockburst risk section, the principle of simulated support is established. The support measures are implemented according to the simulated support principles, and the execution results are obtained by implementing the corresponding support procedures in the numerical model. Based on the results of the support measures, the surrounding rock response records are processed. By recording the response relationship between the surrounding rock stress field parameters, disturbance wave parameters and support measure parameters in the numerical simulation, the mapping relationship is obtained.

9. The method for combined support and control of rockburst caused by multi-source dynamic disturbance according to claim 6, characterized in that, Based on the mapping relationship, a BP neural network model and weight optimization are performed to construct a support decision model, including: Based on the mapping relationship, the initial modeling process of the neural network is performed. By establishing the initial synaptic weight connection from the input layer to the output layer, the initial model for support decision is obtained. Error analysis is performed on the output of the initial support decision model. By comparing the difference between the actual output value and the expected output value, the error distribution data of the output layer is obtained. Based on the output layer error distribution data, synaptic weights are optimized, and the weights and thresholds are iteratively corrected through backpropagation algorithm until the global error converges, thus obtaining the optimal connection weight support decision model.

10. The method for combined support and control of rockburst caused by multi-source dynamic disturbance according to claim 6, characterized in that, Real-time support decision processing is performed based on the rockburst prevention and control decision model. By inputting real-time monitoring data, the optimal support form and parameter combination are output, including: Based on the real-time monitoring data and construction organization design prediction data, disturbance feature identification processing is performed, and real-time disturbance waveform parameters are obtained by analyzing the waveforms of blasting at the working face, TBM vibration, or rockburst events. Based on the real-time disturbance waveform parameters and the rockburst prevention and control decision model, the surrounding rock state-disturbance coupling analysis is performed. By inputting the disturbance waveform parameters and surrounding rock stress characteristics into the neural network model for calculation, the preliminary parameter combination of pressure relief-wave absorption-energy absorption-passive pressure support is obtained. The support system is dynamically configured based on the preliminary parameter combination. By calling the parameterized combination rules of pressure relief, wave absorbing grouting, energy absorbing anchors, steel arch frames and concrete spraying in the support system library, the support form and parameter combination are output.

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