A method and system for comprehensive prevention and control of rock burst in a mine for mining an extra-thick coal seam

Abstract

The present application provides a kind of extra-thick coal seam mining mine rock burst comprehensive prevention method and system.It relates to the technical field of coal mining safety, which realizes real-time dynamic monitoring and wireless data transmission of roadway support structure by integrating intelligent sensor array in support material.The central control system can accurately identify abnormal deformation and stress concentration phenomenon, and trigger multi-channel early warning according to preset rules.Combining with the compatibility design of active and passive support, the system can automatically adjust the support mechanics parameters according to the warning content to enhance the roadway strength.This technology changes the traditional inefficient mode of relying on manual inspection, solves the problem of difficult to find abnormal deformation of roadway support structure in time, and can realize real-time dynamic monitoring and intelligent early warning of roadway support structure, significantly improves the timeliness and accuracy of rock burst risk identification, and effectively enhances the safety protection ability of extra-thick coal seam mine.

Description

Technical Field

[0001] This invention relates to the field of coal mining safety technology, and in particular to a comprehensive method and system for preventing and controlling rockbursts in extra-thick coal seam mining. Background Technology

[0002] Rockbursts refer to the sudden release of accumulated elastic deformation potential in rock masses under certain conditions, leading to rock fracturing and explosion. With the increase in coal seam mining depth, the number of mines prone to rockbursts and the frequency of rockbursts are increasing year by year, posing a significant threat to coal mine safety. However, existing research on the mechanisms of rockburst occurrence is still incomplete, and control technologies face many challenges, such as difficulties in accurate prediction and forecasting, and limited effectiveness of control measures. In the process of thick coal seam mining, roadway support is one of the important measures to ensure mine safety. However, in traditional methods, monitoring of roadway support structures often relies on manual inspections and periodic checks. This method is not only inefficient but also makes it difficult to detect abnormal deformations or stress concentrations in the support structure in a timely manner. Summary of the Invention

[0003] The present invention aims to at least partially solve one of the technical problems in the related art.

[0004] Therefore, the first objective of this invention is to propose a comprehensive method for preventing and controlling rockbursts in mining operations with extra-thick coal seams.

[0005] The second objective of this invention is to propose a comprehensive prevention and control system for rockburst in ultra-thick coal seam mining.

[0006] To achieve the above objectives, a first aspect of the present invention proposes a comprehensive method for preventing and controlling rockbursts in ultra-thick coal seam mining, comprising:

[0007] S1 selects high-strength, corrosion-resistant alloy materials as support materials and integrates an intelligent sensor array into the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. S2 collects monitoring data in real time through an intelligent sensor array and wirelessly transmits the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. S3, based on the dynamic analysis results, the early warning module is used to identify abnormal deformation and stress concentration phenomena in the support structure, and multi-channel early warning signals are generated according to the preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. S4. Based on the content of the early warning signal and in combination with the compatibility design of active and passive support of the support structure, adjust the mechanical parameters of the support structure to enhance the roadway support strength. S5 performs regular system maintenance operations, including sensor calibration, data transmission line maintenance, and data processing unit software updates, to continuously optimize the performance and early warning accuracy of the monitoring system.

[0008] In one embodiment of the present invention, S1 includes: The comprehensive performance evaluation index of the support material is calculated using the material durability evaluation formula; The selection of support materials is based on their strength, toughness, corrosion resistance, and cost-effectiveness, and the material life prediction model is optimized by considering the time-varying characteristics of corrosion rate and performance degradation coefficient.

[0009] In one embodiment of the present invention, S2 includes: The overall quality of monitoring data is quantitatively evaluated using a comprehensive evaluation formula for monitoring data. By dynamically adjusting the sensor response coefficient and time delay constant, the sensitivity of the data processing unit to identify abnormal stress changes is optimized.

[0010] In one embodiment of the present invention, S3 includes: The comprehensive performance evaluation index of the early warning system is calculated using the early warning system performance evaluation formula. The real-time performance and accuracy of early warning signals are optimized by using a response speed coefficient and the ratio of actual early warnings to false alarms.

[0011] In one embodiment of the present invention, it further includes: The overall stability assessment of the support structure is carried out, which includes two parts: static analysis and dynamic analysis. The static analysis calculates the static stability based on the geometric dimensions, material properties and loads of the support structure, while the dynamic analysis assesses the dynamic stability by simulating the response under the dynamic load of rockburst. The overall stability assessment conclusion of the support structure is obtained by combining the results of the two parts.

[0012] To achieve the above objectives, a second aspect of the present invention provides a comprehensive prevention and control system for rockburst in ultra-thick coal seam mining, comprising: The support material integration module is used to select high-strength, corrosion-resistant alloy materials as support materials, and integrates an intelligent sensor array into the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. The data acquisition and transmission module is used to collect monitoring data in real time through an intelligent sensor array and wirelessly transmit the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. The early warning signal generation module is used to identify abnormal deformation and stress concentration phenomena in the support structure based on dynamic analysis results, and generate multi-channel early warning signals according to preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. The mechanical parameter adjustment module is used to adjust the mechanical parameters of the support structure to enhance the roadway support strength based on the content of the early warning signal and the compatibility design of the active and passive support of the support structure. The system maintenance module is used to perform system maintenance operations on a regular basis, including sensor calibration, data transmission line maintenance, and software updates for the data processing unit, in order to continuously optimize the performance and early warning accuracy of the monitoring system.

[0013] The method and system of this invention can realize real-time dynamic monitoring and intelligent early warning of roadway support structures, significantly improve the timeliness and accuracy of rockburst risk identification, and effectively enhance the safety control capabilities of extra-thick coal seam mines.

[0014] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0015] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart illustrating a comprehensive method for preventing and controlling rockbursts in ultra-thick coal seam mining, provided as an embodiment of this application; Figure 2 This is a structural diagram of a comprehensive rockburst prevention and control system for ultra-thick coal seam mining, provided in an embodiment of this application. Detailed Implementation

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] The following description, with reference to the accompanying drawings, describes a comprehensive method and system for preventing and controlling rockbursts in ultra-thick coal seam mining operations according to an embodiment of the present invention.

[0019] Figure 1 This is a flowchart of a comprehensive prevention and control method for rockburst in ultra-thick coal seam mining according to an embodiment of the present invention, such as... Figure 1 As shown, it includes: S1 selects high-strength, corrosion-resistant alloy materials as support materials and integrates an intelligent sensor array into the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. S2 collects monitoring data in real time through an intelligent sensor array and wirelessly transmits the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. S3, based on the dynamic analysis results, the early warning module is used to identify abnormal deformation and stress concentration phenomena in the support structure, and multi-channel early warning signals are generated according to the preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. S4. Based on the content of the early warning signal and in combination with the compatibility design of active and passive support of the support structure, adjust the mechanical parameters of the support structure to enhance the roadway support strength. S5 performs regular system maintenance operations, including sensor calibration, data transmission line maintenance, and data processing unit software updates, to continuously optimize the performance and early warning accuracy of the monitoring system.

[0020] Furthermore, it also includes performing an overall stability assessment of the support structure, which includes two parts: static analysis and dynamic analysis. The static analysis calculates the static stability based on the geometric dimensions, material properties, and loads of the support structure, while the dynamic analysis assesses the dynamic stability by simulating the response under the dynamic load of rockburst. The overall stability assessment conclusion of the support structure is then derived by combining the results of the two parts.

[0021] In summary, this invention selects high-strength and corrosion-resistant alloy materials as support materials and incorporates intelligent sensors to monitor key parameters of the roadway support status in real time. This allows for the timely detection of abnormal deformation or stress concentration in the support structure, effectively preventing disasters such as rockbursts and improving the safety of mine operations. The data processing unit of the central control system can receive and analyze data from various sensors in real time, using a comprehensive evaluation formula to determine the overall stability and potential risks of the support structure. Once the early warning module identifies an anomaly, the system will immediately issue an early warning signal, providing timely alerts to mine managers and workers, helping them to quickly take countermeasures and reduce disaster losses.

[0022] The comprehensive prevention and control method for rockburst in extra-thick coal seam mining according to an embodiment of the present invention is described in detail below: In one embodiment of the present invention, the comprehensive prevention and control method for rockburst in extra-thick coal seam mining may specifically include the following steps: Step 1: Selection and performance evaluation of support materials: High-strength, corrosion-resistant alloy materials are used as support materials. The support materials are equipped with intelligent sensors to monitor the parameters of the roadway support status in real time, including the stress distribution, deformation of the support structure, and the durability evaluation of the materials. Step 2: Real-time monitoring and comprehensive data evaluation: The intelligent sensors can transmit monitoring data to the central control system in real time and accurately. The central control system is equipped with an advanced data processing unit. The data processing unit receives and analyzes the data from various sensors and calculates the overall stability and potential risks of the support structure through the comprehensive evaluation formula of monitoring data. The data processing unit is also responsible for the storage and retrieval of monitoring data, which facilitates historical data analysis and trend prediction. Step 3: Early warning system performance evaluation and immediate response: Based on data analysis results, the early warning module in the central control system intelligently identifies abnormal deformation and stress concentration phenomena in the support structure through the early warning system performance evaluation formula, and issues early warning signals. Step 4: Enhance the compatibility design of the support structure and monitoring system: The roadway adopts an active support structure consisting of a suspended beam structure composed of anchor mesh, anchor cable spraying + 36U canopy, and at the same time combines a passive support structure of retractable 36U canopy and hydraulic lifting canopy to enhance the roadway support strength. Step 5: System Maintenance and Continuous Performance Optimization: Regularly maintain and inspect the support structure and monitoring system, including sensor calibration, data transmission line maintenance, and data processing unit software updates, to ensure the continuous and effective operation of the system.

[0023] Therefore, this method first focuses on the selection of support materials, using high-strength and corrosion-resistant alloy materials, and incorporating intelligent sensors to monitor key parameters of the roadway support status in real time. Through the data processing unit of the central control system, the real-time monitoring data is comprehensively evaluated to determine the overall stability and potential risks of the support structure. Once the early warning module identifies abnormal deformation or stress concentration, the system will immediately issue an early warning signal. In addition, this method also emphasizes the compatibility design of the support structure and the monitoring system, using multiple support structures to enhance the roadway strength. Finally, the maintenance and continuous optimization of the system's performance are also important components of this method, ensuring that the support structure and the monitoring system can operate effectively for a long time.

[0024] In another embodiment of the present invention, this embodiment is basically the same as the previous embodiment, except that the intelligent sensor includes a stress sensor and a displacement sensor, which are used to comprehensively monitor the stress state, deformation degree and dynamic response of the support structure.

[0025] Specifically, the formula for evaluating the durability of the material is as follows: ; in, The comprehensive performance evaluation indicators for support materials include mechanical properties and corrosion resistance. The elastic modulus of the support material as a function of time represents the stiffness of the material. For support materials in time The maximum stress that it can withstand. This is a coefficient representing the degradation of material properties over time, used to describe the stability of material properties. For support materials in time The corrosion rate is below; The range of is [0, +∞), and the larger the value, the better the overall performance of the support material.

[0026] Specifically, the central control system includes a data processing unit and an early warning module. The data processing unit is used to analyze monitoring data and identify anomalies, and the early warning module is used to issue an early warning signal when an anomaly is detected.

[0027] Specifically, the comprehensive evaluation formula for the monitoring data is as follows: ; As a comprehensive quality assessment indicator for monitoring data, For the first The stress value measured by each sensor. For the first The displacement change measured by each sensor For the first The measurement time interval of each sensor The sensor's response coefficient to changes in time. The time delay constant of the sensor response. For the first The noise level of each sensor, For the first The total measured values ​​of all sensors; The value range is [0,1], and the closer the value is to 1, the higher the overall quality of the monitoring data.

[0028] Specifically, the formula for evaluating the effectiveness of the early warning system is as follows: ; As a comprehensive performance evaluation index for the early warning system, For the first The amount of stress change monitored during the first warning. For the first The stress threshold set during the initial warning. This is the response speed coefficient of the early warning system to abnormal situations. For the first The system's response time during the first warning Let k be the number of times a true warning is issued. Let k be the number of false alarms. The value range is [0,1], and the closer the value is to 1, the higher the overall effectiveness of the early warning system.

[0029] As can be seen from the above, this embodiment can comprehensively monitor the stress state, deformation degree and dynamic response of the support structure through stress sensors and displacement sensors. The durability evaluation formula of the support material comprehensively considers the mechanical properties and corrosion resistance of the material, as well as the performance degradation and corrosion rate over time. The central control system realizes the analysis of monitoring data and anomaly identification, as well as the issuance of early warning signals through the data processing unit and early warning module. In addition, the comprehensive evaluation formula of monitoring data is used to quantitatively evaluate the accuracy and reliability of the monitoring data, while the early warning system effectiveness evaluation formula is used to evaluate the accuracy and response speed of the early warning system.

[0030] In another embodiment of the present invention, the difference lies in that the overall stability assessment method of the support structure includes two parts: static analysis and dynamic analysis. The static analysis is mainly based on the geometric dimensions, material properties and loads of the support structure to calculate and assess the stability of the support structure under static conditions. The dynamic analysis considers the response of the support structure under the action of rockburst dynamic load and assesses its dynamic stability through simulation methods. The results of the two parts are combined to obtain the overall stability assessment conclusion of the support structure.

[0031] Specifically, the selection of support materials takes into account their strength, toughness, corrosion resistance, and cost-effectiveness; the monitoring system is deployed to fully cover the key support areas and accurately reflect the stress state and deformation of the support structure.

[0032] Specifically, the methods of issuing early warning signals include, but are not limited to, audible and visual alarms, SMS notifications, email reminders, and remote monitoring system alarms; the content of the early warning signals includes the warning level, warning area, reason for the warning, and suggested emergency measures, so that mine managers and workers can respond quickly.

[0033] Specifically, during system maintenance and continuous performance optimization, a regular maintenance and inspection mechanism should be established, including daily inspections of the support structure, regular calibration of sensors, maintenance of data transmission lines, and software updates for the data processing unit.

[0034] As can be seen from the above, this embodiment clarifies the specific details of support material selection, monitoring system layout, early warning signal issuance methods, and system maintenance and continuous performance optimization. The overall stability assessment method of the support structure combines static and dynamic analysis to comprehensively evaluate the stability of the support structure under different conditions. The selection of support materials comprehensively considers strength, toughness, corrosion resistance, and cost-effectiveness. The monitoring system fully covers key support areas to ensure data accuracy. The early warning signals are issued in various ways and with detailed content, which helps mine managers and operators to react quickly. In addition, this embodiment also emphasizes the importance of system maintenance and continuous performance optimization, and establishes a regular maintenance and inspection mechanism to ensure the long-term stable operation of the support structure and monitoring system.

[0035] All standard parts used in this invention can be purchased commercially, and irregularly shaped parts can be customized according to the description and drawings. The specific connection methods for each part all employ conventional methods such as bolts, rivets, and welding, which are mature technologies in the prior art. The machinery, parts, and equipment all use conventional models in the prior art, and the circuit connections also use conventional connection methods in the prior art, which will not be detailed here. Any content not described in detail in this specification belongs to the prior art known to those skilled in the art.

[0036] Understandably, this embodiment incorporates intelligent sensors to monitor key parameters of the roadway support status in real time, such as stress distribution and deformation, in order to detect anomalies promptly. The data processing unit of the central control system can receive and analyze sensor data in real time, and use a comprehensive evaluation formula to determine the overall stability and potential risks of the support structure. The early warning module can intelligently identify abnormal deformation and stress concentration phenomena and immediately issue early warning signals to provide timely alerts to mine managers and workers.

[0037] To achieve the above embodiments, such as Figure 2 As shown, this embodiment also provides a comprehensive rockburst prevention and control system 10 for extra-thick coal seam mining, including: The support material integration module 100 is used to select high-strength, corrosion-resistant alloy materials as support materials, and integrates an intelligent sensor array in the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. The data acquisition and transmission module 200 is used to acquire monitoring data in real time through an intelligent sensor array and wirelessly transmit the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. The early warning signal generation module 300 is used to identify abnormal deformation and stress concentration phenomena in the support structure based on dynamic analysis results, and generate multi-channel early warning signals according to preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. The mechanical parameter adjustment module 400 is used to adjust the mechanical parameters of the support structure to enhance the roadway support strength based on the content of the early warning signal and the compatibility design of the active and passive support of the support structure. The system maintenance module 500 is used to perform system maintenance operations periodically, including sensor calibration, data transmission line maintenance, and software updates for the data processing unit, in order to continuously optimize the performance and early warning accuracy of the monitoring system.

[0038] Furthermore, the support material integration module is also used for: The comprehensive performance evaluation index of the support material is calculated using the material durability evaluation formula; The selection of support materials is based on their strength, toughness, corrosion resistance, and cost-effectiveness, and the material life prediction model is optimized by considering the time-varying characteristics of corrosion rate and performance degradation coefficient.

[0039] Furthermore, the data acquisition and transmission module is also used for: The overall quality of monitoring data is quantitatively evaluated using a comprehensive evaluation formula for monitoring data. By dynamically adjusting the sensor response coefficient and time delay constant, the sensitivity of the data processing unit to identify abnormal stress changes is optimized.

[0040] Furthermore, the early warning signal generation module is also used for: The comprehensive performance evaluation index of the early warning system is calculated using the early warning system performance evaluation formula. The real-time performance and accuracy of early warning signals are optimized by using a response speed coefficient and the ratio of actual early warnings to false alarms.

[0041] Furthermore, it also includes: The static analysis module is used to calculate the static stability based on the geometry, material properties, and loads of the support structure. The dynamic analysis module is used to evaluate dynamic stability by simulating the response under dynamic loads of rockburst. The comprehensive evaluation module is used to integrate the results of static and dynamic analysis to arrive at an overall stability assessment conclusion for the support structure.

[0042] The comprehensive rockburst prevention and control system for extra-thick coal seam mining in this invention can realize real-time dynamic monitoring and intelligent early warning of roadway support structures, significantly improve the timeliness and accuracy of rockburst risk identification, and effectively enhance the safety control capabilities of extra-thick coal seam mines.

[0043] In the description of this specification, the references to "one embodiment," "some embodiments," "example," "specific example," or "some examples" refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0044] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two or three, unless otherwise explicitly specified.

Claims

1. A comprehensive method for preventing and controlling rockburst in ultra-thick coal seam mining, characterized in that, include: S1 selects high-strength, corrosion-resistant alloy materials as support materials and integrates an intelligent sensor array into the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. S2 collects monitoring data in real time through an intelligent sensor array and wirelessly transmits the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. S3, based on the dynamic analysis results, the early warning module is used to identify abnormal deformation and stress concentration phenomena in the support structure, and multi-channel early warning signals are generated according to the preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. S4. Based on the content of the early warning signal and in combination with the compatibility design of active and passive support of the support structure, adjust the mechanical parameters of the support structure to enhance the roadway support strength. S5 performs regular system maintenance operations, including sensor calibration, data transmission line maintenance, and data processing unit software updates, to continuously optimize the performance and early warning accuracy of the monitoring system.

2. The method as described in claim 1, characterized in that, S1 includes: The comprehensive performance evaluation index of the support material is calculated using the material durability evaluation formula; The selection of support materials is based on their strength, toughness, corrosion resistance, and cost-effectiveness, and the material life prediction model is optimized by considering the time-varying characteristics of corrosion rate and performance degradation coefficient.

3. The method as described in claim 1, characterized in that, S2 includes: The overall quality of monitoring data is quantitatively evaluated using a comprehensive evaluation formula for monitoring data. By dynamically adjusting the sensor response coefficient and time delay constant, the sensitivity of the data processing unit to identify abnormal stress changes is optimized.

4. The method as described in claim 1, characterized in that, S3 includes: The comprehensive performance evaluation index of the early warning system is calculated using the early warning system performance evaluation formula. The real-time performance and accuracy of early warning signals are optimized by using a response speed coefficient and the ratio of actual early warnings to false alarms.

5. The method as described in claim 1, characterized in that, Also includes: The overall stability assessment of the support structure is carried out, which includes two parts: static analysis and dynamic analysis. The static analysis calculates the static stability based on the geometric dimensions, material properties and loads of the support structure, while the dynamic analysis assesses the dynamic stability by simulating the response under the dynamic load of rockburst. The overall stability assessment conclusion of the support structure is obtained by combining the results of the two parts.

6. A comprehensive prevention and control system for rockburst in ultra-thick coal seam mining, characterized in that, include: The support material integration module is used to select high-strength, corrosion-resistant alloy materials as support materials, and integrates an intelligent sensor array into the support materials to monitor the stress distribution, deformation and material durability of the roadway support structure in real time. The data acquisition and transmission module is used to collect monitoring data in real time through an intelligent sensor array and wirelessly transmit the monitoring data to the data processing unit of the central control system. The data processing unit performs dynamic analysis on the monitoring data and calculates the overall stability and potential risks of the support structure. The early warning signal generation module is used to identify abnormal deformation and stress concentration phenomena in the support structure based on dynamic analysis results, and generate multi-channel early warning signals according to preset early warning rules. The multi-channel early warning signals include audible and visual alarms, SMS notifications, email reminders and remote monitoring system alarms. The mechanical parameter adjustment module is used to adjust the mechanical parameters of the support structure to enhance the roadway support strength based on the content of the early warning signal and the compatibility design of the active and passive support of the support structure. The system maintenance module is used to perform system maintenance operations on a regular basis, including sensor calibration, data transmission line maintenance, and software updates for the data processing unit, in order to continuously optimize the performance and early warning accuracy of the monitoring system.

7. The system as described in claim 6, characterized in that, The support material integration module is also used for: The comprehensive performance evaluation index of the support material is calculated using the material durability evaluation formula; The selection of support materials is based on their strength, toughness, corrosion resistance, and cost-effectiveness, and the material life prediction model is optimized by considering the time-varying characteristics of corrosion rate and performance degradation coefficient.

8. The system as described in claim 6, characterized in that, The data acquisition and transmission module is also used for: The overall quality of monitoring data is quantitatively evaluated using a comprehensive evaluation formula for monitoring data. By dynamically adjusting the sensor response coefficient and time delay constant, the sensitivity of the data processing unit to identify abnormal stress changes is optimized.

9. The system as described in claim 6, characterized in that, The warning signal generation module is also used for: The comprehensive performance evaluation index of the early warning system is calculated using the early warning system performance evaluation formula. The real-time performance and accuracy of early warning signals are optimized by using a response speed coefficient and the ratio of actual early warnings to false alarms.

10. The system as described in claim 6, characterized in that, Also includes: The static analysis module is used to calculate the static stability based on the geometry, material properties, and loads of the support structure. The dynamic analysis module is used to evaluate dynamic stability by simulating the response under dynamic loads of rockburst. The comprehensive evaluation module is used to integrate the results of static and dynamic analysis to arrive at an overall stability assessment conclusion for the support structure.

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