Rock burst risk assessment system, rock burst risk assessment method, medium, electronic device, and program
By collecting and processing rock mass data in the impact ground pressure hazard assessment system and using the Moorkulun damage criteria for analysis, the problem of large errors in the evaluation results in the existing technology is solved, and a more accurate and intelligent impact ground pressure hazard assessment is achieved, ensuring safety and early warning efficiency.
Patent Information
- Application Number
- CN202510130435.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-05
- Publication Date
- 2025-06-20
AI Technical Summary
The prior art is difficult to accurately reflect the localization of the true deformation and stress distribution of underground rock mass, resulting in large errors in the assessment results of impact ground pressure risk, and lack of comprehensive consideration and comprehensive evaluation of various factors.
It provides an impact ground pressure hazard assessment system, including a data acquisition module, a data processing module and a risk assessment module. By obtaining rock mass data in the monitoring area, pre-processing and data analysis based on Morkulan's failure criteria, the safety coefficient of rock mass is determined, and the impact hazard index is calculated based on historical data.
It improves the accuracy and intelligence level of impact ground pressure risk assessment, reduces errors caused by human factors, and can take timely response measures to the dangers of impact ground pressure, reduces the risks and losses of geological disasters, and ensures the safety of personnel and corporate property.
Smart Images
Figure CN120181561A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of coal mine safety, and specifically, to a rock burst hazard assessment system, method, medium, electronic device, and program. Background Art
[0002] In recent years, with the continuous increase in the depth of coal resource exploitation in China, rock burst has gradually become one of the important disasters threatening the safe production of coal mines, and the importance of rock burst hazard assessment and prediction has become increasingly prominent. In the existing technology, rock burst hazard assessment mainly relies on geological exploration data, engineering practice experience, and simple stress and strain monitoring methods. These methods are difficult to accurately reflect the true deformation localization and stress distribution of underground rock masses, resulting in large errors in the assessment results. At the same time, the existing prediction methods are also relatively simple, mainly based on the analysis of a single factor, lacking comprehensive consideration and comprehensive evaluation of multiple factors. Therefore, real-time monitoring and early warning of rock burst, comprehensive assessment of rock burst hazards considering multiple factors (such as deformation localization, stress distribution balance, geological disaster occurrence mechanism, etc.), avoiding the limitations of single-factor analysis, and improving the accuracy of rock burst hazard assessment are currently urgent technical problems to be solved. Summary of the Invention
[0003] To overcome the problems existing in the related art, the present disclosure provides a rock burst hazard assessment system, method, medium, electronic device, and program.
[0004] According to the first aspect of the embodiments of the present disclosure, a rock burst hazard assessment system is provided. The system includes: a data acquisition module, a data processing module, and a risk assessment module; The data acquisition module is configured to obtain rock mass data within a monitoring area and send the rock mass data to the data processing module; The data processing module is configured to preprocess the rock mass data after receiving the rock mass data, and perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass within the monitoring area; The risk assessment module is configured to determine the rock burst hazard index of the rock mass within the monitoring area based on the safety factor and historical rock mass rock burst hazard data.
[0005] Optionally, the data acquisition module includes: a collection unit and a transmission unit; the collection unit includes one or more of a displacement sensor, a strain sensor, and a geophone; The collection unit is configured to obtain rock mass data within the monitoring area, and the rock mass data includes one or more of displacement data of the rock mass, stress data, and rock mass acoustic emission signals; The transmission unit is used to send the rock mass data obtained by the acquisition unit to the data processing module.
[0006] Optionally, the data processing module includes: a data processing unit and a data analysis unit; The data processing unit is used to preprocess the rock mass data, and the preprocessing includes filtering and / or denoising the rock mass data; The data analysis unit is used to perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area.
[0007] Optionally, the data analysis unit is further used to: Based on the Mohr-Coulomb failure criterion, perform data analysis on the stress data and the rock mass acoustic emission signal in the rock mass data to determine the safety factor of the rock mass in the monitoring area; When the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0008] Optionally, the acquisition formula of the safety factor includes:
[0009] In the formula, is the safety factor, is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the internal friction angle of the rock mass obtained based on the wave velocity in the rock mass acoustic emission signal, is the coefficient related to the internal friction angle of the rock mass, , is the uniaxial compressive strength of the intact rock mass.
[0010] Optionally, the system further includes: a display module; The display module is used to display one or more of the safety factor, the historical rock mass rock burst hazard data, and the impact hazard index in the form of charts and / or text.
[0011] Optionally, the system further includes: an early warning module; The warning module is used to determine the rockburst danger warning information of the rock mass based on the impact danger index and the rock mass data in the monitoring area, and issue a warning prompt message according to the rockburst danger warning information of the rock mass.
[0012] According to a second aspect of the embodiments of the present disclosure, there is provided a method for evaluating the danger of rockburst, the method including: Obtain the rock mass data in the monitoring area, and perform preprocessing on the rock mass data, where the preprocessing includes filtering and / or denoising the rock mass data; Perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; Based on the safety factor and the historical rockburst danger data of the rock mass, determine the impact danger index of the rock mass in the monitoring area.
[0013] Optionally, the rock mass data includes one or more of displacement data, stress data, and rock mass acoustic emission signals of the rock mass.
[0014] Optionally, the performing data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area includes: Perform data analysis on the stress data and the rock mass acoustic emission signal in the rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; When the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0015] Optionally, the acquisition formula of the safety factor includes:
[0016] In the formula, is the safety factor, is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the internal friction angle of the rock mass obtained based on the wave velocity in the rock mass acoustic emission signal, is the coefficient related to the internal friction angle of the rock mass, , is the uniaxial compressive strength of the intact rock mass.
[0017] According to a third aspect of the embodiments of the present disclosure, a non-transitory computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the rock burst risk assessment method described in the second aspect of the embodiments of the present disclosure are implemented.
[0018] According to a fourth aspect of the embodiments of the present disclosure, an electronic device is provided, including: a memory on which a computer program is stored; a processor configured to execute the computer program in the memory to implement the steps of the rock burst risk assessment method described in the second aspect of the embodiments of the present disclosure.
[0019] According to a fifth aspect of the embodiments of the present disclosure, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of the rock burst risk assessment method described in the second aspect of the embodiments of the present disclosure are implemented.
[0020] In the above technical solution, the data acquisition module is configured to acquire rock mass data within a monitoring area and send the rock mass data to the data processing module; the data processing module is configured to preprocess the rock mass data after receiving the rock mass data, and perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass within the monitoring area; the risk assessment module is configured to determine the rock burst risk index of the rock mass within the monitoring area based on the safety factor and historical rock burst risk data of the rock mass. Through the above technical solution, by collecting various rock mass data affecting rock bursts and performing data analysis on the rock mass data based on the Mohr-Coulomb failure criterion to determine the rock burst risk index of the rock mass within the monitoring area, not only the automation and intelligence levels of assessment and prediction are improved, but also the errors caused by human factors are reduced. Through accurate rock burst risk assessment and prediction, countermeasures can be taken in a timely manner against the risks of rock bursts, reducing the risks and losses of geological disasters and ensuring the safety of personnel and enterprise property.
[0021] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. They are used together with the following specific implementation to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings: Figure 1 is a block diagram of a rock burst risk assessment system shown according to an exemplary embodiment.
[0023] Figure 2It is a block diagram of another rock burst risk assessment system shown according to an exemplary embodiment.
[0024] Figure 3 It is a block diagram of another rock burst risk assessment system shown according to an exemplary embodiment.
[0025] Figure 4 It is a block diagram of yet another rock burst risk assessment system shown according to an exemplary embodiment.
[0026] Figure 5 It is a block diagram of yet another rock burst risk assessment system shown according to an exemplary embodiment.
[0027] Figure 6 It is a flowchart of a rock burst risk assessment method shown according to an exemplary embodiment.
[0028] Figure 7 It is a flowchart of another rock burst risk assessment method shown according to an exemplary embodiment.
[0029] Figure 8 It is a block diagram of an electronic device 800 shown according to an exemplary embodiment.
[0030] Figure 9 It is a block diagram of an electronic device 900 shown according to an exemplary embodiment. Detailed implementation
[0031] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.
[0032] It can be understood that the terms "first", "second", etc. in the present disclosure are used to describe various information, but this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other, and do not represent a specific order or importance.
[0033] It can be further understood that although the operations are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood that they are required to be performed in the specific order shown or in a serial order, or that all the operations shown are required to obtain the desired result. In a specific environment, multitasking and parallel processing may be advantageous.
[0034] It should be noted that all actions of obtaining signals, information, or data in this disclosure are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where the location is located and with the authorization given by the owner of the corresponding device.
[0035] Figure 1 is a block diagram of a rock burst hazard assessment system shown according to an exemplary embodiment, as Figure 1 shown. The rock burst hazard assessment system 100 includes: a data acquisition module 101, a data processing module 102, and a risk assessment module 103; The data acquisition module 101 is configured to acquire rock mass data in the monitoring area and send the rock mass data to the data processing module 102; The data processing module 102 is configured to preprocess the rock mass data after receiving the rock mass data, and perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; The risk assessment module 103 is configured to determine the rock burst hazard index of the rock mass in the monitoring area based on the safety factor and historical rock mass rock burst hazard data.
[0036] Exemplarily, by installing a variety of sensors in the target rock mass area to be monitored to acquire the rock mass data in the target rock mass area, the rock mass data includes one or more of the displacement data, stress data, and rock mass acoustic emission signals of the rock mass; each type of sensor can be multiple, for example, multiple displacement sensors, multiple strain sensors, and multiple ground sound sensors can be set at different positions in the monitoring area, so that the multiple sensors form a sensor network capable of monitoring the entire monitoring area. The data acquisition module 101 acquires the rock mass data and sends the rock mass data to the data processing module 102; the data processing module 102 preprocesses the rock mass data after receiving the rock mass data, and the preprocessing includes filtering and / or denoising the rock mass data; and performs data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; the risk assessment module 103 determines the rock burst hazard index of the rock mass in the monitoring area based on the safety factor and historical rock mass rock burst hazard data, improving the automation and intelligence level of assessment and prediction, and also reducing the errors caused by human factors.
[0037] Through the above technical solution, by collecting various rock mass data that affect rock burst in the rock mass, and performing data analysis on the rock mass data based on the Mohr-Coulomb failure criterion to determine the rock burst risk index of the rock mass in the monitoring area, not only the automation and intelligence levels of evaluation and prediction are improved, but also the errors caused by human factors are reduced. Through accurate rock burst risk assessment and prediction, countermeasures can be taken in a timely manner against the risk of rock burst, reducing the risk and losses of geological disasters and ensuring the safety of personnel and enterprise property.
[0038] Figure 2 is a block diagram of another rock burst risk assessment system shown according to an exemplary embodiment, as Figure 2 shown, the data acquisition module 101 includes: an acquisition unit 1011 and a transmission unit 1012; the acquisition unit 1011 includes one or more of a displacement sensor, a strain sensor, and a ground sound sensor; The acquisition unit 1011 is used to obtain the rock mass data in the monitoring area, and the rock mass data includes one or more of the displacement data, stress data, and rock mass acoustic emission signal of the rock mass; The transmission unit 1012 is used to send the rock mass data obtained by the acquisition unit 1012 to the data processing module 102.
[0039] Exemplarily, sensors are installed in the target rock mass area to be monitored. The acquisition unit 1011 in the data acquisition module 101 includes one or more of a displacement sensor, a strain sensor, and a ground sound sensor. The acquisition unit 1011 is used to obtain the rock mass data in the monitoring area. Among them, the displacement sensor monitors the rock mass displacement data in the target rock mass area, the strain sensor monitors the stress data in the target rock mass area, the ground sound sensor monitors the rock mass acoustic emission signal in the target rock mass area, and the transmission unit 1012 sends the obtained rock mass data to the data processing module 102, so as to collect various rock mass data that affect rock burst in the rock mass.
[0040] Figure 3 is a block diagram of another rock burst risk assessment system shown according to an exemplary embodiment, as Figure 3 shown, the data processing module 102 includes: a data processing unit 1021 and a data analysis unit 1022; The data processing unit 1021 is used to preprocess the rock mass data, and the preprocessing includes filtering and / or denoising the rock mass data; The data analysis unit 1022 is used to perform data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area.
[0041] Exemplarily, preprocessing the rock mass data by filtering and / or denoising through the data processing unit 1021 can improve the data quality for data analysis, and the data analysis unit 1022 performs data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area, where the safety factor represents the ratio between the stress state actually borne by the rock mass and the uniaxial compressive strength of the intact rock mass; for example: when the rock mass fails under multiple stresses and obeys the Mohr-Coulomb failure criterion, the critical state of the failure condition of the rock mass can be expressed as: , where is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the internal friction angle of the rock mass obtained based on the wave velocity in the acoustic emission signal of the rock mass, is related to the internal friction angle of the rock mass is the related coefficient, , is the uniaxial compressive strength of the intact rock mass. By introducing the safety factor , the state of the rock mass is evaluated.
[0042] Optionally, the data analysis unit 1022 is further configured to: perform data analysis on the stress data and the acoustic emission signal of the rock mass in the rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; when the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; when the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; when the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0043] Exemplarily, the safety factor represents the ratio between the stress state actually borne by the rock mass and the uniaxial compressive strength of the intact rock mass.
[0044] Optionally, the safety factor is expressed as:
[0045] In the formula, is the safety factor, is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the internal friction angle of the rock mass obtained based on the wave velocity in the acoustic emission signal of the rock mass, is related to the internal friction angle of the rock mass is the related coefficient, , is the uniaxial compressive strength of the intact rock mass.
[0046] Through this safety factor n, it can be obtained that: When n > 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When n = 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When n < 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0047] Figure 4 is a block diagram of another rock burst hazard assessment system shown according to an exemplary embodiment. As Figure 4 shown, the rock burst hazard assessment system 100 includes: a display module 104; The display module 104 is configured to display one or more of the safety factor, the historical rock burst hazard data of the rock mass, and the impact hazard index in the form of charts and / or text.
[0048] Figure 5 is a block diagram of another rock burst hazard assessment system shown according to an exemplary embodiment. As Figure 5 shown, the rock burst hazard assessment system 100 includes: a warning module 105; The warning module 105 is configured to determine the rock burst hazard warning information based on the impact hazard index and the rock mass data in the monitoring area, and issue a warning prompt message according to the rock burst hazard warning information.
[0049] Exemplarily, the rock burst hazard warning information is determined through the impact hazard index and the rock mass data in the monitoring area, and a warning prompt message is issued according to the rock burst hazard warning information. The warning prompt message can be sent to the staff through one or more of mobile phone APP, text message, and email, so that the staff can take countermeasures against the risk of rock burst in a timely manner.
[0050] Through the above technical solutions, by collecting various rock mass data affecting rock burst of the rock mass and performing data analysis on the rock mass data based on the Mohr-Coulomb failure criterion to determine the impact hazard index of the rock mass in the monitoring area, not only the automation and intelligence levels of assessment and prediction are improved, but also the errors caused by human factors are reduced. Through accurate impact hazard assessment and prediction, countermeasures can be taken against the risk of rock burst in a timely manner, reducing the risk and loss of geological disasters and ensuring the safety of personnel and enterprise property.
[0051] Figure 6It is a flowchart of a method for evaluating the risk of rock burst according to an exemplary embodiment, as Figure 6 shown. The method includes: In step S11, rock mass data within the monitoring area is acquired, and preprocessing is performed on the rock mass data. The preprocessing includes filtering and / or denoising the rock mass data.
[0052] In step S12, data analysis is performed on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass within the monitoring area.
[0053] In step S13, based on the safety factor and historical rock burst risk data of the rock mass, the rock burst risk index of the rock mass within the monitoring area is determined.
[0054] Exemplarily, by installing sensors within the target rock mass area to be monitored, rock mass data within the target rock mass area is collected. The sensors include one or more of a displacement sensor, a strain sensor, and a ground sound sensor. The displacement sensor monitors the rock mass displacement data within the target rock mass area, the stress data within the target rock mass area is monitored through the strain sensor, the rock mass acoustic emission signal within the target rock mass area is monitored through the ground sound sensor, and filtering and / or denoising is performed on the collected rock mass data to obtain the processed rock mass data. Data analysis is performed on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion, the safety factor of the rock mass within the target rock mass area is introduced, and based on the safety factor and historical rock burst risk data of the rock mass, the rock burst risk of the rock mass within the target rock mass area is predicted, and the rock burst risk index within the target rock mass area is determined, so as to determine early warning prompt information through the rock burst risk index to give an early warning prompt for the rock burst risk.
[0055] Optionally, the rock mass data includes one or more of: rock mass displacement data, stress data, and rock mass acoustic emission signals.
[0056] Figure 7 It is a flowchart of another method for evaluating the risk of rock burst according to an exemplary embodiment, as Figure 7 shown. In step S12, it includes: In step S121, based on the Mohr-Coulomb failure criterion, data analysis is performed on the stress data and rock mass acoustic emission signals in the rock mass data to determine the safety factor of the rock mass within the monitoring area.
[0057] In step S122, when the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state.
[0058] In step S123, when the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state.
[0059] In step S124, when the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0060] Exemplarily, when the rock mass fails under the action of multiple stresses and obeys the Mohr-Coulomb failure criterion, the critical condition of the failure condition of the rock mass is: , is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the internal friction angle of the rock mass obtained based on the wave velocity in the acoustic emission signal of the rock mass, is related to the internal friction angle of the rock mass related coefficient, , is the uniaxial compressive strength of the intact rock mass. Based on the Mohr-Coulomb failure criterion, through the stress data and the acoustic emission signal of the rock mass in the rock mass data, a safety factor is introduced to analyze the rock mass in the target rock mass area. The safety factor represents the ratio between the stress state actually borne by the rock mass and the uniaxial compressive strength of the intact rock mass.
[0061] Optionally, the safety factor can be expressed as:
[0062] In the formula, n is the safety factor. From the safety factor n, it can be obtained that: When n > 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When n = 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When n < 1, the stress actually borne by the rock mass exceeds the failure condition, and the rock mass is in a dangerous state.
[0063] Through the above technical solutions, by collecting various rock mass data affecting the rock burst of the rock mass and performing data analysis on the rock mass data based on the Mohr-Coulomb failure criterion to determine the rock burst hazard index of the rock mass in the monitoring area, not only the automation and intelligent level of evaluation and prediction are improved, but also the errors caused by human factors are reduced. Through accurate rock burst hazard assessment and prediction, countermeasures can be taken in a timely manner against the risk of rock burst, reducing the risk and losses of geological disasters and ensuring the safety of personnel and enterprise property.
[0064] Regarding the device in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.
[0065] Figure 8 is a block diagram of an electronic device 800 shown according to an exemplary embodiment. As Figure 8 shown, the electronic device 800 may include: a processor 801, a memory 802. The electronic device 800 may further include one or more of a multimedia component 803, an input / output (I / O) interface 804, and a communication component 805.
[0066] Among them, the processor 801 is used to control the overall operation of the electronic device 800 to complete all or part of the steps in the above-mentioned rock burst hazard assessment method. The memory 802 is used to store various types of data to support the operation of the electronic device 800. These data may include, for example, instructions for any application or method operating on the electronic device 800, as well as application-related data, such as contact data, received and sent messages, pictures, audio, video, and so on. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 803 may include a screen and an audio component. Among them, the screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signals can be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be a keyboard, a mouse, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the electronic device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 805 may include: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.
[0067] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, and is used to execute the above-mentioned rock burst hazard assessment method.
[0068] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-mentioned rock burst hazard assessment method are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions may be executed by the processor 801 of the electronic device 800 to complete the above-mentioned rock burst hazard assessment method.
[0069] Figure 9 is a block diagram of an electronic device 900 shown according to an exemplary embodiment. For example, the electronic device 900 may be provided as a server. Referring to Figure 9 , the electronic device 900 includes a processor 922, the number of which may be one or more, and a memory 932 for storing computer programs executable by the processor 922. The computer programs stored in the memory 932 may include one or more modules each corresponding to a set of instructions. In addition, the processor 922 may be configured to execute the computer program to execute the above-mentioned rock burst hazard assessment method.
[0070] In addition, the electronic device 900 may further include a power supply component 926 and a communication component 950. The power supply component 926 may be configured to perform power management of the electronic device 900, and the communication component 950 may be configured to implement communication of the electronic device 900, for example, wired or wireless communication. In addition, the electronic device 900 may further include an input / output (I / O) interface 928. The electronic device 900 may operate based on an operating system stored in the memory 932.
[0071] In another exemplary embodiment, there is also provided a computer-readable storage medium including program instructions, and when the program instructions are executed by a processor, the steps of the above-described rock burst hazard assessment method are implemented. For example, the non-transitory computer-readable storage medium may be the above-described memory 932 including program instructions, and the above program instructions may be executed by the processor 922 of the electronic device 900 to complete the above-described rock burst hazard assessment method.
[0072] In another exemplary embodiment, there is also provided a computer program product, which includes a computer program executable by a programmable device, and the computer program has a code portion for executing the above-described rock burst hazard assessment method when executed by the programmable device.
[0073] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.
[0074] In addition, it should be noted that, in the various specific technical features described in the above specific embodiments, they can be combined in any appropriate manner without conflict. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination manners.
[0075] Furthermore, any combination can be made among various different embodiments of the present disclosure, as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.
Claims
1. A rock burst hazard assessment system, characterized in that: The system includes: a data acquisition module, a data processing module and a risk assessment module; The data acquisition module is used to obtain rock mass data in the monitoring area and send the rock mass data to the data processing module; The data processing module is used to pre-process the rock mass data after receiving the rock mass data, and perform data analysis on the pre-processed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; The risk assessment module is used to determine the rock burst hazard index of the rock mass in the monitoring area based on the safety factor and historical rock burst hazard data.
2. The system according to claim 1, characterized in that The data acquisition module includes: an acquisition unit and a transmission unit; the acquisition unit includes one or more of a displacement sensor, a strain sensor and a ground sound sensor; The acquisition unit is used to acquire rock mass data in the monitoring area, wherein the rock mass data includes one or more of displacement data, stress data and rock mass acoustic emission signals; The transmission unit is used to send the rock mass data acquired by the acquisition unit to the data processing module.
3. The system according to claim 1, characterized in that The data processing module includes: a data processing unit and a data analysis unit; The data processing unit is used to preprocess the rock mass data, and the preprocessing includes filtering and / or denoising the rock mass data; The data analysis unit is used to perform data analysis on the pre-processed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area.
4. The system according to claim 3, characterized in that The data analysis unit is also used for: Based on the Mohr-Coulomb failure criterion, the stress data and the rock mass acoustic emission signal in the rock mass data are analyzed to determine the safety factor of the rock mass in the monitoring area; When the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition and the rock mass is in a dangerous state.
5. The system according to claim 3, characterized in that The formula for obtaining the safety factor includes: In the formula, is the safety factor, is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the rock mass internal friction angle obtained based on the wave velocity in the rock mass acoustic emission signal, is the friction angle with the rock mass The correlation coefficient, , is the uniaxial compressive strength of the intact rock mass.
6. The system according to claim 1, characterized in that The system further comprises: a display module; The display module is used to display one or more of the safety factor, the historical rock mass rock burst hazard data and the rock burst hazard index in the form of graphs and / or text.
7. The system according to claim 1, characterized in that The system also includes: an early warning module; The early warning module is used to determine the rock impact hazard early warning information based on the impact hazard index and the rock mass data in the monitoring area, and issue early warning prompt information according to the rock impact hazard early warning information.
8. A rock burst hazard assessment method, characterized in that: The method comprises: Acquire rock mass data in the monitoring area, and preprocess the rock mass data, wherein the preprocessing includes filtering and / or denoising the rock mass data; Performing data analysis on the preprocessed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area; Based on the safety factor and historical rock burst hazard data, a rock burst hazard index of the rock mass in the monitoring area is determined.
9. The method according to claim 8, characterized in that The rock mass data includes: one or more of displacement data, stress data and rock mass acoustic emission signals.
10. The method according to claim 8, characterized in that The performing of data analysis on the pre-processed rock mass data based on the Mohr-Coulomb failure criterion to determine the safety factor of the rock mass in the monitoring area includes: Based on the Mohr-Coulomb failure criterion, the stress data and the rock mass acoustic emission signal in the rock mass data are analyzed to determine the safety factor of the rock mass in the monitoring area; When the safety factor is greater than 1, the stress actually borne by the rock mass is lower than the failure condition, and the rock mass is in a safe state; When the safety factor is equal to 1, the stress actually borne by the rock mass reaches the failure condition, and the rock mass is in a critical state; When the safety factor is less than 1, the stress actually borne by the rock mass exceeds the failure condition and the rock mass is in a dangerous state.
11. The method according to claim 8, characterized in that The formula for obtaining the safety factor includes: In the formula, is the safety factor, is the maximum principal stress of the stress data, is the minimum principal stress of the stress data, is the rock mass internal friction angle obtained based on the wave velocity in the rock mass acoustic emission signal, is the friction angle with the rock mass The correlation coefficient, , is the uniaxial compressive strength of the intact rock mass.
12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 8 to 11 are implemented.
13. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 8 to 11.
14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 8 to 11 are implemented.