Residual hazard assessment and active pressure relief system after rock burst disaster

Abstract

The application discloses a rock burst post-disaster residual danger evaluation and active pressure relief system, comprising a multi-source data acquisition module, a residual danger intelligent evaluation module, an active directional pressure relief module, a support repair module and a monitoring feedback module; the application realizes accurate prediction of danger zoning and secondary impact probability through multi-source data cooperative acquisition and fusion noise reduction, capture of surrounding rock stress, fissure and temperature field change, three-level evaluation model combined with transfer learning and damage mechanics algorithm, differential pressure relief technology dynamically optimizes parameters for different danger zones, directional release of residual stress, the support repair module is used for strengthening the stability of surrounding rock, the monitoring feedback module is used for constructing a dynamic closed loop, real-time triggering of secondary prevention and control instructions, effective solution to the problems of poor targeting, prevention and control lag and other problems of traditional technology, reduction of secondary impact danger, and reliable technical support for rapid recovery of production, protection of personnel and equipment safety after disaster in coal mines.

Description

Technical Field

[0001] This invention relates to the field of coal mine hazard assessment technology, specifically to a system for assessing residual hazard and actively depressurizing after a rockburst disaster. Background Technology

[0002] Rockburst is a typical dynamic disaster in deep coal mining. It refers to the sudden and violent destructive dynamic phenomenon of coal (rock) mass around the mine roadway or working face due to the instantaneous release of elastic deformation energy, often accompanied by instantaneous displacement, ejection, loud noise, and air waves.

[0003] The occurrence of this disaster is closely related to geological structure, mining depth, and coal mining technology, and is often accompanied by precursors such as micro-earthquakes, stress concentration, and fracture development. As coal mining extends to deeper areas, the level of ground stress increases, and the risk of rockburst increases significantly, which has become a core problem restricting the safe mining of deep coal resources. It needs to be prevented and controlled through comprehensive technologies such as monitoring, hazard assessment, or active pressure relief.

[0004] Existing rockburst control technologies primarily focus on pre-disaster early warning and prevention, lacking effective means to address secondary rockburst hazards caused by residual stress concentration and increased fracture development in roadway surrounding rock after a disaster. Traditional post-disaster stress relief methods (such as borehole stress relief) lack specificity, failing to accurately locate peak residual stress areas, and making it difficult to monitor stress release effects in real time during the stress relief process, resulting in the continued existence of secondary rockburst risks. Simultaneously, the damaged roadway support structure after a disaster lacks a coordinated solution for rapid repair and rockburst prevention reinforcement, impacting production recovery and personnel safety. Therefore, achieving accurate assessment of post-disaster residual hazards, integrated proactive and directional stress relief, and support repair has become a key technical challenge in post-disaster prevention and control. Summary of the Invention

[0005] The purpose of this invention is to provide a system for assessing residual hazards and actively depressurizing after rockburst disasters, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a residual hazard assessment and active pressure relief system after a rockburst disaster, comprising a multi-source data acquisition module, a residual hazard intelligent assessment module, an active directional pressure relief module, a support and repair module, and a monitoring and feedback module: wherein, the multi-source data acquisition module is used to collect multi-dimensional data of the surrounding rock of the roadway after the disaster, and after data fusion and noise reduction, the results are transmitted to the residual hazard intelligent assessment module; The residual hazard intelligent assessment module constructs a three-level assessment model based on the received fused data, generates a residual hazard level distribution map and a secondary impact probability prediction result, and sends the result to the active directional depressurization module; The active directional depressurization module adopts differentiated depressurization technology based on the hazard assessment results, dynamically adjusts the depressurization parameters, and synchronizes the depressurization process data to the monitoring feedback module. The support and repair module receives the surrounding rock status data after decompression transmitted by the monitoring and feedback module; The monitoring and feedback module continuously monitors the surrounding rock and support system data after depressurization, constructs a dynamic hazard assessment model to update the hazard level, and triggers secondary depressurization or support adjustment commands.

[0007] Preferably, the multi-source data acquisition module includes a portable ultrasonic stress detector, a ground-penetrating radar, a distributed fiber optic sensor network, and a data fusion module; The portable ultrasonic stress detector and ground-penetrating radar are used to collect data on residual stress distribution, fracture development depth and support structure damage. The distributed optical fiber sensor network is used to collect surrounding rock temperature field data; The data fusion module uses an adaptive Kalman filter algorithm to reduce noise in multi-source heterogeneous data and calls pre-disaster stress field, microseismic events and geological structure baseline data for comparative analysis.

[0008] Preferably, the three-level assessment model of the residual hazard intelligent assessment module is as follows: The primary assessment identifies areas of residual stress anomalies and crack propagation zones through pre- and post-disaster data difference analysis. The secondary assessment is based on the damage mechanics model and the probability density decay model, and quantifies the hazard weight by coupling residual stress field, crack field and temperature field data. The Level 3 assessment introduces the core algorithm of the microseismic damage reconstruction stress model, combines historical secondary impact cases, optimizes parameters through transfer learning algorithms, and outputs a hazard level distribution map and secondary impact probability. The hazard level is divided into high-risk, medium-risk, and low-risk areas.

[0009] Preferably, in the residual hazard intelligent assessment module, the damage mechanics model adopts the following formula: In the formula, The residual risk index, This represents the residual stress value after the disaster. This represents the baseline stress value before the disaster. Let be the dynamic stress concentration factor of the i-th node. Post-disaster fissure density, Pre-disaster fissure density, , , The weight coefficients are optimized using the transfer learning algorithm, and + + =1; the formula for calculating the dynamic stress concentration factor of the i-th node is: In the formula, For the maximum principal stress, For minimum principal stress, For the dynamic elastic modulus of rock mass, For dynamic strain rate, For maximum shear stress, It represents the uniaxial compressive strength of the rock mass.

[0010] Preferably, the active directional pressure relief module designs the drilling path for high-risk areas based on the residual stress distribution, calculates fracturing pressure and flow parameters through dynamic stress concentration factors, directionally cuts the stress transmission path, and simultaneously injects liquid nitrogen. It also dynamically adjusts the liquid nitrogen injection volume and rate in conjunction with the energy accumulation critical index. The active directional pressure relief module uses pressure relief drilling and acoustic vibration to relieve pressure in the centered high-risk areas, and optimizes the hole spacing, depth, and vibration frequency based on the fracture propagation rate.

[0011] Preferably, the active directional pressure relief module calculates the fracturing pressure of the i-th borehole using the following formula: In the formula, This refers to the fracturing pressure. This is a correction factor for geological conditions. The ultimate compressive strength of the surrounding rock. The coefficient representing the influence of fracture density is... The dynamic stress concentration factor. This represents the residual stress value after the disaster. This refers to the density of fissures after the disaster.

[0012] Preferably, in the residual hazard intelligent assessment module, the data difference analysis and construction of the probability density decay model adopt the following calculation formula: Stress anomaly degree: ,when This point was identified as a stress anomaly. Fracture anomaly degree: ,when These were identified as abnormal fracture points; among them, This represents the residual stress value of the i-th grid node after the disaster. This represents the baseline stress value of the corresponding node before the disaster. Post-disaster fissure density, This refers to the pre-disaster fissure density.

[0013] Preferably, the active directional pressure relief module collects stress change and crack closure rate data in real time through fiber optic sensors and stress sensors, and dynamically adjusts the pressure relief parameters using a multi-objective optimization algorithm.

[0014] Preferably, the support and repair module includes a modular fiber-reinforced concrete support plate, adaptive anchor cables, and a support optimization module; wherein, the support plate has built-in stress sensors and microseismic monitoring nodes to provide real-time feedback on support stress and surrounding rock stability, and the support optimization module simulates the support bearing evolution based on an energy crack coupling model and dynamically adjusts the anchor cable preload.

[0015] Preferably, the monitoring and feedback module continuously collects data on residual stress, crack development, support stress, and microseismic events after depressurization, constructs a dynamic hazard assessment model, and updates the hazard level in real time. When the stress change rate exceeds 100% or microseismic energy accumulates abnormally, a secondary depressurization command is automatically triggered.

[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention captures changes in surrounding rock stress, fissures, and temperature fields through multi-source data collaborative acquisition and fusion noise reduction; a three-level assessment model combined with transfer learning and damage mechanics algorithms enables accurate prediction of dangerous zones and the probability of secondary impact; differentiated pressure relief technology dynamically optimizes parameters for different dangerous zones and releases residual stress in a targeted manner; a support and repair module enhances the stability of the surrounding rock; and a monitoring and feedback module constructs a dynamic closed loop to trigger secondary prevention and control commands in real time. This effectively solves the problems of poor targeting and delayed prevention and control in traditional technologies, reduces the risk of secondary impact, and provides reliable technical support for the rapid recovery of coal mine production after a disaster and the protection of personnel and equipment safety. Attached Figure Description

[0017] Figure 1 This is a block diagram of the architecture of the post-earthquake residual hazard assessment and active depressurization system according to an embodiment of the present invention.

[0018] Figure 2 This is a flowchart illustrating the process of the post-earthquake residual hazard assessment and active depressurization system according to an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 The embodiments of the present invention provide a residual hazard assessment and active depressurization system after a rockburst disaster, including a multi-source data acquisition module, a residual hazard intelligent assessment module, an active directional depressurization module, a support and repair module, and a monitoring and feedback module.

[0021] The multi-source data acquisition module is used to collect multi-dimensional data of the surrounding rock of the roadway after the disaster. After data fusion and noise reduction, the results are transmitted to the residual hazard intelligent assessment module. The multi-source data acquisition module includes a portable ultrasonic stress detector, a ground radar, a distributed optical fiber sensor network and a data fusion module. The portable ultrasonic stress detector and the ground radar are used to collect residual stress distribution, fracture development depth and support structure damage data. The distributed optical fiber sensor network is arranged in a grid pattern along the roof, sides and floor of the tunnel, with an optical fiber spacing of 5 meters and a sampling frequency of 10Hz, providing key evidence for the analysis of energy accumulation and conversion. The data fusion module uses an adaptive Kalman filter algorithm to reduce noise in multi-source heterogeneous data and calls pre-disaster stress field, microseismic events and geological structure baseline data for comparative analysis; Furthermore, the data fusion module is deployed in an industrial computer. The core algorithm adopts adaptive Kalman filtering. The algorithm dynamically adjusts the filter gain and observation noise covariance matrix according to the historical error statistics of each sensor to effectively suppress random noise and abnormal measurement values. The fused data will be automatically compared and analyzed with the pre-stored pre-disaster stress field baseline data, historical microseismic event database and mining area geological structure map to initially identify abnormal stress and fracture change areas.

[0022] Furthermore, the residual hazard intelligent assessment module constructs a three-level assessment model based on the received fused data, generates a residual hazard level distribution map and a secondary impact probability prediction result, and sends the result to the active directional depressurization module. The three-level assessment model of the residual hazard intelligent assessment module is as follows: Level 1 assessment: This level identifies residual stress anomaly zones and fracture propagation zones through pre- and post-disaster data difference analysis; Secondary assessment: Based on the damage mechanics model and the probability density decay model, the risk weight is quantified by coupling residual stress field, crack field and temperature field data; Level 3 assessment: Introducing the core algorithm of the microseismic damage reconstruction stress model, combined with historical secondary impact cases, the parameters are optimized through transfer learning algorithm, outputting a hazard level distribution map and the probability of secondary impact. The hazard level is divided into high-risk area, medium-risk area and low-risk area, and the probability of secondary impact on the working face in the next 24 hours is given. The following calculation formula is used to construct a probability density decay model based on the difference between pre-disaster and post-disaster data: Stress anomaly degree: ,when This point was identified as a stress anomaly. Fracture anomaly degree: ,when These were identified as abnormal fracture points; among them, This represents the residual stress value of the i-th grid node after the disaster. This represents the baseline stress value of the corresponding node before the disaster. Post-disaster fissure density, This refers to the pre-disaster fissure density.

[0023] In addition, the damage mechanics model uses the following formula: In the formula, The residual risk index, This represents the residual stress value after the disaster. This represents the baseline stress value before the disaster. Let be the dynamic stress concentration factor of the i-th node. Post-disaster fissure density, Pre-disaster fissure density, , , The weight coefficients are optimized using the transfer learning algorithm, and + + =1, the transfer learning algorithm uses historical disaster case data as the training set, and the optimization objective is the prediction accuracy. The optimized weight coefficients are... , , The value of is usually in the range of 0.2-0.5; the formula for calculating the dynamic stress concentration factor of the i-th node is: In the formula, For the maximum principal stress, For minimum principal stress, For the dynamic elastic modulus of rock mass, For dynamic strain rate, For maximum shear stress, It represents the uniaxial compressive strength of the rock mass.

[0024] In this embodiment, the active directional depressurization module adopts differentiated depressurization technology based on the hazard assessment results, dynamically adjusts the depressurization parameters, and synchronizes the depressurization process data to the monitoring feedback module. The active directional pressure relief module designs borehole paths in high-risk areas based on residual stress distribution, calculates fracturing pressure and flow parameters using dynamic stress concentration factors, directionally cuts the stress transmission path, and simultaneously injects liquid nitrogen. It dynamically adjusts the liquid nitrogen injection volume and rate based on the energy accumulation critical index, employing an enhanced pressure relief scheme that combines high-pressure hydraulic fracturing and liquid nitrogen synergistic fracturing. The fracturing pressure of the i-th borehole is calculated using the following formula: In the formula, This refers to the fracturing pressure (MPa). This is a correction factor for geological conditions. The ultimate compressive strength of the surrounding rock (MPa). The value is the fracture density influence coefficient, ranging from 0.1 to 0.3. The dynamic stress concentration factor. This represents the residual stress value after the disaster (MPa). Post-disaster fissure density; The injection volume and rate of liquid nitrogen are based on the real-time calculated energy accumulation critical value. Make dynamic adjustments when At that time, increase the liquid nitrogen injection rate; The active directional pressure relief module uses pressure relief drilling and acoustic vibration to relieve pressure in the centered danger zone. Based on the fracture propagation rate, it optimizes the hole spacing, depth, and vibration frequency. It adopts a combination of pressure relief drilling group and low-frequency acoustic vibration. Based on the real-time feedback of fracture propagation rate, it uses a multi-objective optimization algorithm to dynamically adjust the spacing (3-5 meters), depth (8-15 meters), and accompanying acoustic vibration frequency (10-30 Hz) of the pressure relief drilling holes to promote stable fracture propagation and slow energy release. Specifically, the active directional pressure relief module collects stress change and fracture closure rate data in real time through fiber optic sensors and stress sensors, and dynamically adjusts the pressure relief parameters using a multi-objective optimization algorithm. During the pressure relief process, the module collects stress change and fracture closure rate data in real time at a frequency of 100Hz through fiber optic sensors and stress sensors deployed near the borehole, and dynamically adjusts the flow rate and pressure parameters of the fracturing pump using the NSGA-II objective optimization algorithm.

[0025] The support repair module receives the decompression-induced surrounding rock state data transmitted by the monitoring feedback module. The support repair module includes a modular fiber-reinforced concrete support plate, adaptive anchor cables, and a support optimization module. The support plate has built-in stress sensors and micro-seismic monitoring nodes to provide real-time feedback on support stress and surrounding rock stability. The support optimization module simulates the support bearing evolution based on an energy crack coupling model and dynamically adjusts the anchor cable preload. Based on the simulation results and real-time monitoring data, the module dynamically adjusts the preload of the adaptive anchor cables through a hydraulic servo control system, with an adjustment range of 50kN-200kN, to achieve dynamic matching between support resistance and surrounding rock deformation pressure, avoiding over-support or under-support.

[0026] The monitoring and feedback module continuously monitors the surrounding rock and support system data after depressurization, constructs a dynamic hazard assessment model to update the hazard level, and triggers secondary depressurization or support adjustment commands.

[0027] Furthermore, the monitoring and feedback module continuously collects data on residual stress, crack development, support stress, and microseismic events after depressurization, constructs a dynamic hazard assessment model, and updates the hazard level in real time. When the stress change rate exceeds 100% or microseismic energy accumulates abnormally, a secondary depressurization command is automatically triggered.

[0028] Specifically, the monitoring feedback module has a preset triggering mechanism. When real-time monitoring data shows that the stress change rate in a certain area exceeds 100% within 1 minute, or microseismic energy accumulates abnormally within 10 minutes (such as an energy growth rate exceeding 500%), it will automatically generate and trigger a secondary depressurization or support adjustment command, and send the command to the active directional depressurization module or support repair module first, thus starting a new round of prevention and control cycle.

[0029] Reference Figures 1-2 Based on the above technical solution, the working steps of this solution are summarized as follows: After a rockburst disaster occurs, rescue personnel first deploy a multi-source data acquisition module to conduct a comprehensive scan of the disaster-stricken roadway to obtain initial data. After data fusion and noise reduction, the data is transmitted to the residual hazard intelligent assessment module, which completes a three-level assessment and outputs a hazard level distribution map. Subsequently, the active directional depressurization module performs precise depressurization operations in high-risk and medium-risk areas based on the hazard level distribution map, with operation data fed back in real time.

[0030] After depressurization, the support repair module installs the support system and dynamically adjusts the support parameters. Finally, the monitoring and feedback module enters the long-term monitoring phase to ensure that the danger is controllable and to initiate secondary prevention and control measures when necessary.

[0031] All parts not described in this invention are the same as or can be implemented using existing technology. Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A system for assessing residual hazards and actively depressurizing after a rockburst disaster, characterized in that, It includes a multi-source data acquisition module, a residual hazard intelligent assessment module, an active directional depressurization module, a support and repair module, and a monitoring and feedback module. The multi-source data acquisition module is used to collect multi-dimensional data of the surrounding rock of the roadway after the disaster, and transmits the results to the residual hazard intelligent assessment module after data fusion and noise reduction. The residual hazard intelligent assessment module constructs a three-level assessment model based on the received fused data, generates a residual hazard level distribution map and a secondary impact probability prediction result, and sends the result to the active directional depressurization module; The active directional depressurization module adopts differentiated depressurization technology based on the hazard assessment results, dynamically adjusts the depressurization parameters, and synchronizes the depressurization process data to the monitoring feedback module. The support and repair module receives the surrounding rock status data after decompression transmitted by the monitoring and feedback module; The monitoring and feedback module continuously monitors the surrounding rock and support system data after depressurization, constructs a dynamic hazard assessment model to update the hazard level, and triggers secondary depressurization or support adjustment commands.

2. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The multi-source data acquisition module includes a portable ultrasonic stress detector, a ground-penetrating radar, a distributed fiber optic sensor network, and a data fusion module. The portable ultrasonic stress detector and ground-penetrating radar are used to collect data on residual stress distribution, fracture development depth and support structure damage. The distributed optical fiber sensor network is used to collect surrounding rock temperature field data; The data fusion module uses an adaptive Kalman filter algorithm to reduce noise in multi-source heterogeneous data and calls pre-disaster stress field, microseismic events and geological structure baseline data for comparative analysis.

3. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The three-level assessment model of the residual hazard intelligent assessment module is as follows: The primary assessment identifies areas of residual stress anomalies and crack propagation zones through pre- and post-disaster data difference analysis. The secondary assessment is based on the damage mechanics model and the probability density decay model, and quantifies the hazard weight by coupling residual stress field, crack field and temperature field data. The Level 3 assessment introduces the core algorithm of the microseismic damage reconstruction stress model, combines historical secondary impact cases, optimizes parameters through transfer learning algorithms, and outputs a hazard level distribution map and secondary impact probability. The hazard level is divided into high-risk, medium-risk, and low-risk areas.

4. The post-rockburst residual hazard assessment and active depressurization system according to claim 3, characterized in that: In the residual hazard intelligent assessment module, the damage mechanics model adopts the following formula: In the formula, The residual risk index, This represents the residual stress value after the disaster. This represents the baseline stress value before the disaster. Let be the dynamic stress concentration factor of the i-th node. Post-disaster fissure density, Pre-disaster fissure density, , , The weight coefficients are optimized using the transfer learning algorithm, and + + =1; the formula for calculating the dynamic stress concentration factor of the i-th node is: In the formula, For the maximum principal stress, For minimum principal stress, For the dynamic elastic modulus of rock mass, For dynamic strain rate, For maximum shear stress, It represents the uniaxial compressive strength of the rock mass.

5. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The active directional pressure relief module designs the drilling path in high-risk areas based on the residual stress distribution, calculates fracturing pressure and flow parameters through dynamic stress concentration factor, directionally cuts the stress transmission path, injects liquid nitrogen synchronously, and dynamically adjusts the liquid nitrogen injection volume and rate in combination with the energy accumulation critical index. The active directional pressure relief module uses pressure relief drilling and acoustic vibration to relieve pressure in the central danger zone, and optimizes the hole spacing, depth and vibration frequency based on the crack propagation rate.

6. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The active directional pressure relief module The fracturing pressure for the i-th borehole is calculated using the following formula: In the formula, This refers to the fracturing pressure. This is a correction factor for geological conditions. The ultimate compressive strength of the surrounding rock. The coefficient representing the influence of fracture density is... The dynamic stress concentration factor. This represents the residual stress value after the disaster. This refers to the density of fissures after the disaster.

7. The post-rockburst residual hazard assessment and active depressurization system according to claim 3, characterized in that: In the residual hazard intelligent assessment module, the data difference analysis and construction of the probability density decay model adopt the following calculation formula: Stress anomaly degree: ,when This point was identified as a stress anomaly. Fracture anomaly degree: ,when This point was identified as an anomaly in the fracture. in, This represents the residual stress value of the i-th grid node after the disaster. This represents the baseline stress value of the corresponding node before the disaster. Post-disaster fissure density, This represents the pre-disaster fissure density.

8. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The active directional pressure relief module collects stress change and crack closure rate data in real time through fiber optic sensors and stress sensors, and dynamically adjusts the pressure relief parameters using a multi-objective optimization algorithm.

9. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The support and repair module includes a modular fiber-reinforced concrete support plate, adaptive anchor cables, and a support optimization module. The support plate has built-in stress sensors and microseismic monitoring nodes to provide real-time feedback on the support stress and surrounding rock stability. The support optimization module simulates the support bearing evolution based on an energy crack coupling model and dynamically adjusts the anchor cable preload.

10. The post-rockburst residual hazard assessment and active depressurization system according to claim 1, characterized in that: The monitoring and feedback module continuously collects data on residual stress, crack development, support stress, and microseismic events after depressurization, constructs a dynamic hazard assessment model, and updates the hazard level in real time. When the stress change rate exceeds 100% or microseismic energy accumulates abnormally, a secondary depressurization command is automatically triggered.

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