Early warning method and device for stress flow of rock burst, electronic equipment and storage medium

Abstract

The invention discloses a stress flow early warning method and device for rock burst, electronic equipment and a storage medium, and relates to the technical field of data processing. Compared with the related technology, the embodiment of the invention comprehensively analyzes and deduces a preset dynamic yield surface model of a coal and rock mass influenced by stress flow by calculating the stress flow and combining the damage condition of a similar model; the test between the stress flow and the coal rock mass instability is obtained by simulating different coal rock structures, the stress flow-based rock burst early warning threshold is set, different early warning thresholds exist for different construction conditions, and the prediction precision of the rock burst is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a stress flow early warning method and device for rock burst, electronic equipment and storage medium. Background Art

[0003] At present, the stress flow early warning method of rock burst is mainly based on stress control theory, and early warning is achieved by monitoring the stress of the structure. The stress monitoring methods are mainly divided into two types: destructive monitoring and non-destructive monitoring. The drill cuttings method is the most prominent representative of destructive monitoring, which drills holes on the structure and judges by the amount of drill cuttings and the strain of the borehole. There are many non-destructive monitoring methods, including microseismic monitoring, geoacoustic monitoring, electromagnetic radiation monitoring, etc., which mainly use geophysical characteristics to invert stress and strain to warn of possible rock burst. Although the above two early warning methods can achieve early warning of rock burst to a certain extent, the early warning error of this method is large and it is easy to misjudge. Summary of the invention

[0004] The present disclosure provides a stress flow early warning method, device, electronic device and storage medium for rock burst. According to a first aspect of the present disclosure, a stress flow early warning method for rock burst is provided, which includes:

[0005] Based on a preset boosting method, load tests are performed on a preset number of different similar models, and deformation data and stress flow data of the similar models are obtained; wherein the construction conditions of different similar models are different;

[0006] determining a correlation between the stress flow data and the deformation data;

[0007] Obtaining a preset dynamic yield surface model, and performing numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions;

[0008] Based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation, the stress flow warning value under mining conditions and structural conditions is determined.

[0009] Optionally, the performing load tests on a preset number of different similar models based on a preset pressurization method and obtaining deformation data and stress flow data of the similar models includes:

[0010] determining a total value of a dead load on the similar model based on a similarity scale;

[0011] Loads are applied to the top and left and right sides of the similar model in preset stages until the load value reaches the total load value, and the evolution data of the deformation field and crack field and the static load stress flow data of the similar model are collected based on a preset collection method.

[0012] Optionally, the performing load tests on a preset number of different similar models based on a preset pressurization method and obtaining deformation data and stress flow data of the similar models includes:

[0013] Different dynamic loads are applied to the different similar models, and the evolution data of the deformation field and the crack field and the dynamic stress flow data of the similar models are collected based on a preset collection method; wherein the disturbance frequencies and disturbance amplitudes of the different dynamic loads are different.

[0014] Optionally, determining the correlation between the stress flow data and the deformation data includes:

[0015] Calculate the outer envelope surface of the static stress vector according to the static stress flow data and the dynamic stress flow vector according to the dynamic stress flow data;

[0016] By combining the static load stress vector, the outer envelope surface of the dynamic load stress flow vector, the evolution data of the deformation field and the crack field of the similar model corresponding to the static load, and the evolution data of the deformation field and the crack field of the similar model corresponding to the dynamic load, the stress flow precursor characteristics of the impact rock pressure of different similar models are determined.

[0017] Optionally, before obtaining a preset dynamic yield surface model and performing numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions, the method further includes:

[0018] The preset dynamic yield surface model is established based on non-local hardening parameters and internal time variables.

[0019] Optionally, the determining of the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similarity model, the preset dynamic yield surface model and the result of the numerical simulation includes:

[0020] According to the results of numerical simulation under the different structural conditions and the stress flow precursor characteristics of rock burst of the different similar models, the stress flow warning values ​​of rock burst under different mining conditions and structural conditions are determined.

[0021] According to a second aspect of the present disclosure, a stress flow early warning device for rock burst is provided, comprising:

[0022] An acquisition unit, used for performing load tests on a preset number of different similar models based on a preset boosting method, and acquiring deformation data and stress flow data of the similar models; wherein the construction conditions of different similar models are different;

[0023] A first determining unit, configured to determine the correlation between the stress flow data and the deformation data;

[0024] A simulation unit, used to obtain a preset dynamic yield surface model, and perform numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions;

[0025] The second determination unit is used to determine the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation.

[0026] Optionally, the acquiring unit is further used for:

[0027] determining a total value of a dead load on the similar model based on a similarity scale;

[0028] Loads are applied to the top and left and right sides of the similar model in preset stages until the load value reaches the total load value, and the evolution data of the deformation field and crack field and the static load stress flow data of the similar model are collected based on a preset collection method.

[0029] Optionally, the acquiring unit is further used for:

[0030] Different dynamic loads are applied to the different similar models, and the evolution data of the deformation field and the crack field and the dynamic stress flow data of the similar models are collected based on a preset collection method; wherein the disturbance frequencies and disturbance amplitudes of the different dynamic loads are different.

[0031] Optionally, the first determining unit is further configured to:

[0032] Calculate the outer envelope surface of the static stress vector according to the static stress flow data and the dynamic stress flow vector according to the dynamic stress flow data;

[0033] By combining the static load stress vector, the outer envelope surface of the dynamic load stress flow vector, the evolution data of the deformation field and the crack field of the similar model corresponding to the static load, and the evolution data of the deformation field and the crack field of the similar model corresponding to the dynamic load, the stress flow precursor characteristics of the impact rock pressure of different similar models are determined.

[0034] Optionally, the device further comprises:

[0035] A unit is established, which is used to obtain a preset dynamic yield surface model in a simulation unit, and to perform numerical simulation based on the preset dynamic yield surface model to obtain the critical characteristics of rock burst under different stresses and different structural conditions, and then to establish the preset dynamic yield surface model based on non-local hardening parameters and internal time variables.

[0036] Optionally, the second determining unit is further configured to:

[0037] According to the results of numerical simulation under the different structural conditions and the stress flow precursor characteristics of rock burst of the different similar models, the stress flow warning values ​​of rock burst under different mining conditions and structural conditions are determined.

[0038] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0039] at least one processor; and

[0040] a memory communicatively connected to the at least one processor; wherein,

[0041] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0042] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0043] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0044] The stress flow warning method, device, electronic device and storage medium for rock burst provided by the present disclosure include: based on a preset supercharging method, a load test is performed on a preset number of different similar models, and deformation data and stress flow data of the similar models are obtained; wherein the structural conditions of different similar models are different; the correlation between the stress flow data and the deformation data is determined; a preset dynamic yield surface model is obtained, and numerical simulation is performed based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions; based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation, the stress flow warning value under mining conditions and structural conditions is determined. Compared with the related art, the embodiment of the present application calculates the stress flow, combines the situation when the similar model is destroyed, comprehensively analyzes and derives the preset dynamic yield surface model of the stress flow affecting the coal rock mass, simulates different coal rock structures to obtain the test between stress flow and coal rock mass instability, sets the rock burst warning threshold based on stress flow, and has different warning thresholds for different structural conditions, thereby improving the prediction accuracy of rock burst.

[0045] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0047] Figure 1 A schematic diagram of a flow chart of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure;

[0048] Figure 2 A schematic diagram of a flow chart of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure;

[0049] Figure 3 A schematic diagram of a flow chart of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure;

[0050] Figure 4 A schematic diagram of stress flow characterization provided in an embodiment of the present application;

[0051] Figure 5 A schematic diagram of a stress flow vector provided in an embodiment of the present application;

[0052] Figure 6 A schematic structural diagram of a rock burst warning device provided in an embodiment of the present disclosure;

[0053] Figure 7A schematic structural diagram of a stress flow early warning device for rock burst provided in an embodiment of the present disclosure;

[0054] Figure 8 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0055] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0056] The following describes the stress flow early warning method, device, electronic device and storage medium for rock burst according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0057] Figure 1 A schematic flow chart of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure.

[0058] like Figure 1 As shown, the method comprises the following steps:

[0059] Step 101 : performing load tests on a preset number of different similar models based on a preset pressurization method, and obtaining deformation data and stress flow data of the similar models; wherein the construction conditions of different similar models are different.

[0060] In some embodiments, before executing this step, a similar model is made, wherein the similar model is used to simulate the distribution of the bottom layer of a real mine, such as the distribution of rock formations, rock formation thickness, rock formation inclination, etc. In some embodiments, different types of materials can be used instead based on the characteristics of different rock formations, such as using foamed ceramics, gypsum, barite powder, water, gypsum and electro-optical paper materials, etc., to simulate coal seams with different inclinations, top and bottom rock formations, structural surfaces of mine rock formations, large faults and fissure surfaces. Specifically, the embodiments of the present application are not limited to this. It should be noted that a mine of preset size needs to be reserved in the coal seam. By carrying out load experiments with similar models of different structures, the loads for mines under different structural conditions in more cases can be simulated through differential settings.

[0061] In some embodiments, when performing a load test, stress flow data and deformation data may be collected based on strain gauges, displacement sensors, pressure gauges, etc. Specifically, the embodiments of the present application do not limit the collection method.

[0062] Step 102: Determine the correlation between the stress flow data and the deformation data.

[0063] The dynamic stress flow data are combined with the model deformation and failure process to reveal the precursor characteristics of stress flow before and after coal rock rupture under stress, and to clarify the intrinsic correlation between stress flow and coal rock rupture and rock burst.

[0064] Step 103, obtaining a preset dynamic yield surface model, and performing numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions.

[0065] The dynamic yield surface model is a theoretical model that describes the yield behavior of materials under dynamic loading conditions. This model takes into account the strain rate effect, that is, the yield characteristics of the material change with the change of strain rate.

[0066] In some embodiments, appropriate numerical simulation software, such as finite element analysis software, is selected to perform simulation analysis. Relevant parameters of the dynamic yield surface model, such as mechanical properties of the material, loading conditions, etc., are set in the software, and numerical simulation is run to calculate the material response under different stress and structural conditions to obtain the critical state of the material under rock burst, that is, the critical condition for rock burst to occur.

[0067] Step 104, based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the result of the numerical simulation, determine the stress flow warning value under mining conditions and structural conditions.

[0068] Combining the results of experimental simulation, theoretical derivation and numerical simulation, the stress flow warning value of rock burst under specific mining conditions and structural conditions is systematically determined.

[0069] The stress flow early warning method for rock burst provided by the present disclosure includes: based on a preset boosting method, a load test is performed on a preset number of different similar models, and deformation data and stress flow data of the similar models are obtained; wherein the structural conditions of different similar models are different; the correlation between the stress flow data and the deformation data is determined; a preset dynamic yield surface model is obtained, and numerical simulation is performed based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions; based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation, the stress flow early warning value under mining conditions and structural conditions is determined. Compared with the related art, the embodiment of the present application calculates the stress flow, combines the situation when the similar model is destroyed, comprehensively analyzes and derives the preset dynamic yield surface model of the stress flow affecting the coal rock mass, simulates different coal rock structures to obtain the test between stress flow and coal rock mass instability, sets the rock burst early warning threshold based on stress flow, and has different early warning thresholds for different structural conditions, thereby improving the prediction accuracy of rock burst.

[0070] In some embodiments, the load is divided into dynamic load and static load, wherein the dynamic load includes vibration and extrusion generated during coal mining, etc.; the static load is the extrusion force between geology; therefore, when executing step 1, the static load and dynamic load need to be simulated separately. Figure 2 , Figure 2 A schematic flow diagram of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure includes:

[0071] Step 201 : determining the total value of the static load on the similar model based on the similarity scale.

[0072] In some embodiments, if the size of the model is 1 / 10 of the prototype, the geometric scale is 1:10; specifically, it can be determined according to the size of the model, and the embodiments of the present application are not limited to this. In some embodiments, the stress scale is generally proportional to the square of the geometric scale.

[0073] Step 202, applying loads to the top and left and right sides of the similar model according to preset stages until the load value reaches the total load value, and collecting the evolution data of the deformation field and crack field and the static load stress flow data of the similar model based on a preset collection method.

[0074] First, an initial load of about 1 MPa was applied to the top and left and right sides of the model respectively; secondly, the horizontal loads on the left and right sides were kept fixed, and the top load was applied to 50% of the predetermined top total load; then, the top vertical load was kept fixed, and the horizontal load was applied to 80% of the predetermined horizontal total load; finally, the top load and the horizontal loads on the left and right sides were applied simultaneously to the predetermined total load. At the same time, acoustic emission monitoring, high-speed cameras and digital image correlation technology (DIC) were used to measure the deformation field and crack field evolution process of the model surface in real time.

[0075] Optionally, when performing a dynamic load test, the test may be performed according to the following steps, including:

[0076] Different dynamic loads are applied to the different similar models, and the evolution data of the deformation field and the crack field and the dynamic stress flow data of the similar models are collected based on a preset collection method; wherein the disturbance frequencies and disturbance amplitudes of the different dynamic loads are different.

[0077] In some embodiments, a controllable medium and low frequency separated Hopkinson bar (SHPB) impact test device can be combined with a biaxial loading and unloading similar physical simulation test system, and the incident wave can be controlled to be excited by the special-shaped bullet head of the SHPB by changing the shape, material, length and impact speed of the bullet head. More than 10 mining dynamic load stress wave inputs are simulated. Under the control of the dynamic similarity theory, the SHPB test disturbance frequency and disturbance amplitude are similar to the actual mining stress waves at the engineering site, and the disturbance of the dynamic load stress wave on the surrounding rock of the tunnel and the triggering effect on the impact ground pressure are observed by a high-speed camera. It should be noted that the above mining dynamic load stress wave input is set to 10 as an exemplary description, and the embodiments of the present application do not limit this.

[0078] In some embodiments, since the directions of the dynamic load and the static load are different, the calculation methods are also different. When calculating specifically, refer to the following steps for calculation. Figure 3 , Figure 3 A schematic flow diagram of a stress flow early warning method for rock burst provided in an embodiment of the present disclosure includes:

[0079] Step 301 , respectively calculating a static stress vector according to the static stress flow data and calculating an outer envelope surface of a dynamic stress flow vector according to the dynamic stress flow data.

[0080] The static stress flow is characterized by calculating the stress flow vector, and the spatial state of the dynamic stress flow is characterized by calculating the outer envelope of the dynamic stress flow vector. The dynamic stress flow envelope of different particles is used to draw stress streamlines in space, such as Figure 4 and Figure 5 As shown, Figure 4 A schematic diagram of stress flow characterization provided in an embodiment of the present application; Figure 5 A schematic diagram of a stress flow vector provided in an embodiment of the present application.

[0081] Step 302, combining the static load stress vector, the outer envelope surface of the dynamic load stress flow vector, the evolution data of the deformation field and the crack field of the similar model corresponding to the static load, and the evolution data of the deformation field and the crack field of the similar model corresponding to the dynamic load, to determine the stress flow precursor characteristics of the rock burst of different similar models.

[0082] The calculation results of stress flow under dynamic and static loads are combined with the model deformation and failure process captured by high-speed cameras under static and dynamic load tests, respectively, to reveal the precursor characteristics of stress flow before and after coal rock rupture under dynamic and static loads, and to clarify the intrinsic correlation between stress flow and coal rock rupture and rock burst.

[0083] When determining the stress flow precursor characteristics of rock burst of different similar models, it is necessary to combine the outer envelope of the static load stress vector, the dynamic load stress flow vector, and the evolution data of the deformation field and crack field of the similar models corresponding to the static and dynamic loads.

[0084] Static load stress vector refers to the stress distribution and direction inside the model under static loading conditions. This stress state does not change with time and can provide information on the stress response of the model under constant load. Through static load tests, the evolution data of the deformation field and crack field of similar models under static loading conditions can be obtained. These data reflect the failure process and mechanical behavior of the model under static load.

[0085] The dynamic load stress flow vector describes the stress changes and flow trends inside the model under dynamic loading conditions. Unlike the static load stress vector, the dynamic load stress flow vector takes into account the time factor and can reflect the propagation and change process of stress in the model. Through dynamic load tests, the evolution data of the deformation field and crack field of similar models under dynamic loading conditions can be obtained. These data reveal the dynamic response and failure mechanism of the model under dynamic load.

[0086] The outer envelope surface refers to the surface connecting the tips of the static load stress vector and the dynamic load stress flow vector. It represents the maximum stress state that the model can reach under different loading conditions. By analyzing the shape and changes of the outer envelope surface, we can understand the load-bearing capacity and damage risk of the model under different loading conditions.

[0087] Under the action of dynamic and static loads, the stress inside the model will be redistributed. By analyzing the pattern of stress redistribution, the precursor characteristics of rock burst, such as stress concentration areas and potential fracture surfaces, can be determined. The occurrence of rock burst is often accompanied by the accumulation and sudden release of energy. By monitoring the energy changes inside the model, the risk of rock burst can be warned.

[0088] Before rock burst occurs, the model usually shows some precursory phenomena, such as the rapid expansion of small cracks, the sharp increase of local deformation, etc. These phenomena can be captured by equipment such as high-speed cameras and combined with stress flow precursor characteristics to improve the accuracy of early warning.

[0089] In some embodiments, it is also necessary to establish and preset a dynamic yield surface model in advance, and the specific steps include:

[0090] The preset dynamic yield surface model is established based on non-local hardening parameters and internal time variables.

[0091] From the perspective of stress gradient, the theoretical relationship between stress flow and coal rock mass failure and even rock burst is established. The influence of non-local stress gradient zone is considered in the material hardening strain parameter, and non-local hardening parameters are introduced. On the other hand, the idea of ​​endogenous constitutive theory is borrowed to introduce endogenous time variables into the plastic yield surface to simulate the change of yield surface with time. The dynamic yield surface model formula is:

[0092]

[0093] Where, σ is the stress tensor; k is the hardening strain parameter; is the non-local hardening parameter; ζ is the internal time variable.

[0094] The non-local hardening parameters and the internal time variables jointly reflect the influence of stress changes in time and space on the strength theory of coal and rock mass (i.e., yield criterion). The new yield surface constructed can be called the dynamic yield surface model.

[0095] In some embodiments, the determining of the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similarity model, the preset dynamic yield surface model and the result of the numerical simulation includes:

[0096] According to the results of numerical simulation under the different structural conditions and the stress flow precursor characteristics of rock burst of the different similar models, the stress flow warning values ​​of rock burst under different mining conditions and structural conditions are determined.

[0097] In order to simulate the process of coal-rock destruction and rock burst, the Fortran language was used to integrate the stress flow vector and stress flow envelope calculation program into the peridynamics and finite element coupling software PDCF, so as to simulate both the coal-rock destruction and rock burst as well as the formation and evolution of stress flow, clarify the mutual feedback mechanism between static and dynamic stress flow and coal-rock fracture and plastic zone evolution, determine the critical characteristics and precursor information of rock burst caused by stress flow under different mining conditions and different structural conditions, and systematically reveal the intrinsic mechanism of stress flow-induced coal-rock destruction and rock burst.

[0098] Corresponding to the above-mentioned rock burst stress flow warning method, the present invention also proposes a rock burst stress flow warning device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, the details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0099] Figure 6 A schematic diagram of the structure of a stress flow warning device for rock burst provided by an embodiment of the present disclosure is shown in FIG. Figure 6 As shown, including:

[0100] An acquisition unit 41 is used to perform a load test on a preset number of different similar models based on a preset boosting method, and to acquire deformation data and stress flow data of the similar models; wherein the construction conditions of different similar models are different;

[0101] A first determining unit 42, configured to determine the correlation between the stress flow data and the deformation data;

[0102] The simulation unit 43 is used to obtain a preset dynamic yield surface model, and perform numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions;

[0103] The second determination unit 44 is used to determine the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation.

[0104] The stress flow warning device for rock burst provided by the present disclosure includes the following main technical solutions: based on a preset boosting method, a load test is performed on a preset number of different similar models, and deformation data and stress flow data of the similar models are obtained; wherein the structural conditions of different similar models are different; the correlation between the stress flow data and the deformation data is determined; a preset dynamic yield surface model is obtained, and numerical simulation is performed based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions; based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation, the stress flow warning value under mining conditions and structural conditions is determined. Compared with the related art, the embodiment of the present application calculates the stress flow, combines the situation when the similar model is destroyed, comprehensively analyzes and derives the preset dynamic yield surface model of the stress flow affecting the coal rock mass, simulates different coal rock structures to obtain the test between stress flow and coal rock mass instability, sets the rock burst warning threshold based on stress flow, and has different warning thresholds for different structural conditions, thereby improving the prediction accuracy of rock burst.

[0105] Furthermore, in a possible implementation of the embodiment of the present disclosure, the acquisition unit 41 is further configured to:

[0106] determining a total value of a dead load on the similar model based on a similarity scale;

[0107] Loads are applied to the top and left and right sides of the similar model in preset stages until the load value reaches the total load value, and the evolution data of the deformation field and crack field and the static load stress flow data of the similar model are collected based on a preset collection method.

[0108] Furthermore, in a possible implementation of the embodiment of the present disclosure, the acquisition unit 41 is further configured to:

[0109] Different dynamic loads are applied to the different similar models, and the evolution data of the deformation field and the crack field and the dynamic stress flow data of the similar models are collected based on a preset collection method; wherein the disturbance frequencies and disturbance amplitudes of the different dynamic loads are different.

[0110] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 7 As shown, the first determining unit 42 is further used for:

[0111] Calculate the outer envelope surface of the static stress vector according to the static stress flow data and the dynamic stress flow vector according to the dynamic stress flow data;

[0112] By combining the static load stress vector, the outer envelope surface of the dynamic load stress flow vector, the evolution data of the deformation field and the crack field of the similar model corresponding to the static load, and the evolution data of the deformation field and the crack field of the similar model corresponding to the dynamic load, the stress flow precursor characteristics of the impact rock pressure of different similar models are determined.

[0113] Furthermore, in a possible implementation of the embodiment of the present disclosure, the device further includes:

[0114] An establishing unit 45 is used to obtain a preset dynamic yield surface model in the simulation unit 43, and to perform numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions, and then to establish the preset dynamic yield surface model based on non-local hardening parameters and internal time variables.

[0115] Further, in a possible implementation of the embodiment of the present disclosure, the second determining unit 44 is further configured to:

[0116] According to the results of numerical simulation under the different structural conditions and the stress flow precursor characteristics of rock burst of the different similar models, the stress flow warning values ​​of rock burst under different mining conditions and structural conditions are determined.

[0117] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principle is the same, which is no longer limited in the embodiment of the present disclosure.

[0118] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0119] Figure 8A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0120] like Figure 8 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 502 or a computer program loaded from a storage unit 508 to a RAM (Random Access Memory) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0121] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0122] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a stress flow early warning method for rock burst. For example, in some embodiments, the stress flow early warning method for rock burst may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method described above may be executed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the aforementioned rock burst stress flow early warning method in any other appropriate manner (for example, by means of firmware).

[0123] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0125] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0126] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0127] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0128] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0129] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0130] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0131] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A stress flow early warning method for rock burst, characterized in that: include: Based on a preset boosting method, load tests are performed on a preset number of different similar models, and deformation data and stress flow data of the similar models are obtained; wherein the construction conditions of different similar models are different; determining a correlation between the stress flow data and the deformation data; Obtaining a preset dynamic yield surface model, and performing numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions; Based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation, the stress flow warning value under mining conditions and structural conditions is determined.

2. The method according to claim 1, characterized in that The method of performing load tests on a preset number of different similar models based on a preset boosting method and obtaining deformation data and stress flow data of the similar models includes: determining a total value of a dead load on the similar model based on a similarity scale; Loads are applied to the top and left and right sides of the similar model in preset stages until the load value reaches the total load value, and the evolution data of the deformation field and crack field and the static load stress flow data of the similar model are collected based on a preset collection method.

3. The method according to claim 1, characterized in that The method of performing load tests on a preset number of different similar models based on a preset boosting method and obtaining deformation data and stress flow data of the similar models includes: Different dynamic loads are applied to the different similar models, and the evolution data of the deformation field and the crack field and the dynamic stress flow data of the similar models are collected based on a preset collection method; wherein the disturbance frequencies and disturbance amplitudes of the different dynamic loads are different.

4. The method according to any one of claims 1 to 3, characterized in that Determining the correlation between the stress flow data and the deformation data includes: Calculate the outer envelope surface of the static stress vector according to the static stress flow data and the dynamic stress flow vector according to the dynamic stress flow data; By combining the static load stress vector, the outer envelope surface of the dynamic load stress flow vector, the evolution data of the deformation field and the crack field of the similar model corresponding to the static load, and the evolution data of the deformation field and the crack field of the similar model corresponding to the dynamic load, the stress flow precursor characteristics of the impact rock pressure of different similar models are determined.

5. The method according to claim 1, characterized in that Before obtaining a preset dynamic yield surface model and performing numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions, the method further includes: The preset dynamic yield surface model is established based on non-local hardening parameters and internal time variables.

6. The method according to claim 4, characterized in that Determining the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similarity model, the preset dynamic yield surface model and the result of the numerical simulation includes: According to the results of numerical simulation under the different structural conditions and the stress flow precursor characteristics of rock burst of the different similar models, the stress flow warning values ​​of rock burst under different mining conditions and structural conditions are determined.

7. A stress flow warning device for rock burst, characterized in that: include: An acquisition unit, used for performing load tests on a preset number of different similar models based on a preset boosting method, and acquiring deformation data and stress flow data of the similar models; wherein the construction conditions of different similar models are different; A first determining unit, configured to determine the correlation between the stress flow data and the deformation data; A simulation unit, used to obtain a preset dynamic yield surface model, and perform numerical simulation based on the preset dynamic yield surface model to obtain critical characteristics of rock burst under different stresses and different structural conditions; The second determination unit is used to determine the stress flow warning value under mining conditions and structural conditions based on the deformation data and stress flow data of the similar model, the preset dynamic yield surface model and the results of the numerical simulation.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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