A high-strength mining working face mine pressure appearance law dynamic early warning method and system

Abstract

The present application relates to the technical field of coal mining and safety monitoring, and discloses a high-strength mining working face mine pressure appearance law dynamic early warning method and system, the method comprising: constructing an overburden structure model and collecting multi-source data; respectively solving a stoping advance speed vector representing mining intensity and a stress field migration speed vector representing surrounding rock breakage response; calculating the speed difference of the two, and determining that the system is in an energy lag accumulation state when the difference exceeds a preset threshold; converting the speed difference into geometric correction parameters such as the target drill hole axial angle of high-depth hole blasting; and finally performing three-dimensional coordinated pressure relief operation according to the correction parameters. The present application quantifies the time and space non-synchronous characteristics of mining disturbance and surrounding rock response through double-speed field coupling analysis, realizes dynamic early warning of roof fracture lag risk and adaptive regulation and control of blasting parameters, and effectively eliminates the accumulated elastic energy of surrounding rock.

Description

Technical Field

[0001] This invention relates to the field of coal mining and safety monitoring technology, specifically to a dynamic early warning method and system for the manifestation of mine pressure in high-intensity mining faces. Background Technology

[0002] In the current coal mining sector, due to capacity restrictions in some regions, mine production models are gradually shifting towards single-face production and efficiency targets. Mining faces urgently need to improve speed and efficiency to ensure production targets are met. With increasing mining depth and improved fully mechanized mining equipment efficiency, high-speed mining has become a significant trend in the mining of thick, hard-roofed coal seams. However, high-speed mining leads to increased overburden movement and highly concentrated mining stress, especially in large-span working faces where large deformation along the goaf and intense mine pressure occur, which to some extent restricts the working face's production efficiency. To ensure rockburst prevention and maintain continuous production, monitoring systems are typically constructed on-site using microseismic, acoustic, and stress monitoring methods to obtain basic data on surrounding rock fracturing activity and bearing pressure.

[0003] Existing mine pressure early warning mechanisms are insufficiently adaptable to high-speed longwall mining. Traditional monitoring methods primarily rely on static thresholds of single physical quantities for identification, triggering an alarm when the monitored value exceeds a fixed warning value. This approach ignores the dynamic correlation between physical mining operations and the mechanical response of the surrounding rock in the spatiotemporal dimensions. Under high-speed advance conditions, the frequency of mining disturbances increases, while the stress migration and fracture response of thick, hard roofs often exhibit significant lag. If only absolute monitoring values ​​are considered without quantifying the asynchronous difference between the longwall advance rate and the stress field migration rate, the system struggles to accurately identify the energy accumulation state caused by the lag in roof fracture lines due to excessively high advance speeds, resulting in a delay in the identification of dynamic disaster risks such as rockbursts.

[0004] In the management and control of areas with severe mining pressure, existing three-dimensional blasting decompression technologies mostly employ fixed parameters determined during the design phase (such as fixed borehole spacing, angles, and charge quantities) for construction, lacking a dynamic feedback mechanism that adapts to changes in mining speed and real-time energy accumulation. When the elastic energy accumulated within the surrounding rock fluctuates drastically during high-speed mining, fixed blasting parameters are insufficient to effectively overcome the high-stress locking effect and cannot promptly sever the cantilever structure of key layers. Furthermore, existing mining processes typically do not fully utilize the rheological damage characteristics of the rock mass after strong disturbance; the control of mining speed is often independent of the weakened state of the rock mass, making it difficult to achieve precise spatiotemporal coordination between rapid mining and decompression effects, thus limiting further improvements in tunnel excavation efficiency and economic benefits. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a dynamic early warning method and system for the manifestation of mining pressure in high-intensity mining faces. This solves the technical problems of existing monitoring methods relying solely on static stress thresholds, which make it difficult to accurately quantify the spatiotemporal asynchronous characteristics between mining disturbances and the response to surrounding rock fracture. This results in the inability to promptly identify the energy accumulation risk caused by the lag in roof fracture, and the inability of traditional fixed blasting parameters to adaptively adjust to dynamically changing accumulated energy.

[0006] To achieve the above objectives, the first aspect of the present invention provides a dynamic early warning method for the manifestation pattern of mining pressure in high-intensity mining faces, comprising: A spatial structure model of the overburden was constructed, and a multi-source monitoring array was deployed in the mining area of ​​the mining face; Based on the overlying rock spatial structure model, the location data of mining equipment and the mechanical response data of surrounding rock that characterizes the manifestation of mining pressure are collected in real time. After smoothing, the mining advance speed vector that characterizes the intensity of mining disturbance and the stress field migration speed vector that characterizes the fracture response characteristics of surrounding rock are calculated respectively. Calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector. When the velocity difference exceeds a preset threshold determined based on the overburden space structure model, determine that the mining face is in a state of energy lag accumulation and generate a dynamic early warning signal. In response to the dynamic early warning signal, the velocity difference is converted into geometric correction parameters for high-level deep hole blasting, and the geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof. Based on the axial deflection angle and the corresponding charge parameters, deep hole blasting of key layers at high positions is carried out, and three-dimensional coordinated operation is completed in conjunction with low-position pressure relief measures.

[0007] In the above method, the data acquisition and preprocessing stages are used to establish a unified spatiotemporal reference, which serves as the digital carrier of the overburden spatial structure model. The specific construction and processing steps are as follows: By establishing a three-dimensional rectangular coordinate system for the entire working face, the static model data obtained from geological exploration (including the coal seam floor structure, fault location, and key layer geometric parameters) are mapped into this three-dimensional rectangular coordinate system, thereby completing the initialization of the spatial overburden structure model.

[0008] For the location data of mining equipment, a sliding window mean filtering algorithm is used to process the original three-dimensional coordinate sequence, remove high-frequency random noise caused by underground environmental interference, and generate a continuous equipment running trajectory. This equipment running trajectory is represented as a moving target curve that extends over time in the overburden space structure model.

[0009] For the surrounding rock stress data, the inverse distance weighted interpolation method is used to process the discrete monitoring point data arranged in the advance roadway to construct a continuous stress distribution curve along the roadway direction. On this basis, by calculating the location where the first derivative is zero and the second derivative is less than zero, the peak point location of the advance support pressure is identified, thereby transforming the discrete sensor values ​​into the stress field extreme value characteristics in the spatial model.

[0010] Furthermore, the real-time acquisition of the mining equipment location data and the surrounding rock mechanical response data characterizing the mineral pressure manifestation features are smoothed, including: A sliding window mean filtering algorithm is used to process the three-dimensional coordinate sequence of the mining equipment, remove positioning noise, and generate a continuous running trajectory. The discrete stress monitoring values ​​in the advance section of the mining roadway are processed by the inverse distance weighted interpolation method to construct a continuous stress distribution curve along the roadway direction. The extreme value search is then performed on the continuous stress distribution curve to identify the peak point of the advance support pressure.

[0011] Furthermore, the calculation of the stress field migration velocity vector characterizing the fracture response of the surrounding rock includes: A subset of effective microseismic events within a time window is selected, and energy-weighted localization is performed on the microseismic events within the subset of effective microseismic events to calculate the axial coordinates of the stress field energy release centroid. The micro-vibration centroid migration velocity component is calculated based on the change of the axial coordinate over time, and the stress peak migration velocity component is calculated based on the change of the peak point of the advanced support pressure over time. The microseismic centroid migration velocity component and the stress peak migration velocity component are synthesized using a weighted fusion strategy to obtain the final stress field migration velocity vector.

[0012] Furthermore, the preset threshold is set based on the lithological characteristics of the overlying strata, and the setting process includes: Obtain the thickness parameters, uniaxial compressive strength parameters, and rock elastic modulus parameters of the main critical layer of the top plate; The maximum allowable velocity deviation threshold is determined based on the thickness parameter, uniaxial compressive strength parameter, and rock elastic modulus parameter, wherein the maximum velocity deviation threshold is positively correlated with the thickness parameter and the uniaxial compressive strength parameter, and negatively correlated with the rock elastic modulus parameter; The maximum velocity deviation threshold is used to characterize the velocity difference tolerance of rock strata that allows energy to accumulate without sudden fracture.

[0013] Furthermore, after determining that the mining face is in a state of energy lag accumulation and generating a dynamic early warning signal, the method further includes: Starting from the end time of the most recent top plate cycle, the energy accumulation intensity index is obtained by time integral accumulation of the difference between the velocity difference and the preset threshold during the time period before the current time when the velocity difference exceeds the preset threshold. The energy accumulation intensity index is used to quantitatively characterize the degree of cumulative lag caused by velocity asynchrony, and the energy accumulation intensity index is transmitted as a gain variable to the process of converting the velocity difference into geometric correction parameters for high-position deep hole blasting using a nonlinear mapping function.

[0014] Furthermore, the process of determining the matching propellant parameters includes: A modified explosive unit consumption model based on the energy accumulation intensity index is established. Using the standard rock explosive unit consumption as a benchmark, the dynamic explosive unit consumption is calculated using the energy accumulation intensity index. As the energy accumulation intensity index increases, the dynamic explosive consumption per unit increases dynamically.

[0015] Furthermore, the velocity difference is transformed into geometric correction parameters for high-altitude deep-hole blasting using a nonlinear mapping function.

[0016] Furthermore, the method of converting the velocity difference into geometric correction parameters for high-altitude deep-hole blasting using a nonlinear mapping function includes: Determine the borehole spacing that can meet the dynamic explosive unit consumption requirements; when the velocity difference increases, leading to an increase in dynamic explosive unit consumption, reduce the borehole spacing. The borehole elevation angle is dynamically compensated based on the speed difference. The calculation logic is as follows: on the basis of the basic elevation angle, an angle correction amount that is positively correlated with the ratio of the speed difference to the mining advance speed vector is added.

[0017] Furthermore, the generation process of the geometric correction parameters also includes security verification logic: Determine whether the calculated borehole spacing is less than the minimum safe distance for drilling operations; If the distance is less than the minimum safe distance, switch to the double-row staggered arrangement mode, correct the output borehole spacing to twice the original calculated value, and add a row of borehole coordinates to the construction parameter table. The second row of borehole coordinates is offset relative to the first row of borehole coordinates along the direction of the correction to half of the borehole spacing.

[0018] Furthermore, after completing the three-dimensional collaborative operation, it also includes: Determine the optimal weakening period of the surrounding rock after blasting; Based on the optimal weakening period, the advancing speed of the longwall face is dynamically adjusted so that the cutting operation is completed within the optimal weakening period.

[0019] Specifically, the determination of the optimal weakening period of the surrounding rock after blasting; and the dynamic adjustment of the advance speed of the longwall face based on the optimal weakening period, so that the cutting operation is completed within the optimal weakening period; specifically including: The effective window period for rheological decompression is identified based on the characteristics of surrounding rock damage evolution. The identification criteria are the preset proportions in which the microseismic energy release rate drops back to the background noise level and the sound wave velocity inside the rock mass decreases to the wave velocity of the intact rock mass. Perform dynamic matching of the mining speed based on the effective window period of the rheological decompression, and calculate the theoretical time required for the working face to pass through the blasting area; If the theoretical duration is longer than the remaining duration of the effective window period for rheological decompression, an acceleration command is issued to increase the traction speed of the coal mining machine, so that the mining and cutting operation is completed during the period when the rock mass is in the state of maximum damage.

[0020] A second aspect of the present invention provides a dynamic early warning system for the manifestation of mining pressure in high-intensity mining faces, comprising: The multi-source monitoring module is used to construct an overburden spatial structure model and deploy a multi-source monitoring array in the mining area of ​​the mining face; and based on the overburden spatial structure model, to collect real-time data on the location of mining equipment and the mechanical response data of the surrounding rock that characterizes the mineral pressure manifestation. The velocity calculation module, connected to the multi-source monitoring module, is used to smooth the location data of the mining equipment and the surrounding rock mechanical response data that characterizes the mineral pressure manifestation characteristics, and then calculate the mining advance velocity vector that characterizes the mining disturbance intensity and the stress field migration velocity vector that characterizes the surrounding rock fracture response characteristics, respectively. The coupling determination module, connected to the velocity calculation module, is used to calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector. When the velocity difference exceeds a preset threshold determined based on the overburden space structure model, the mining face is determined to be in a state of energy lag accumulation and a dynamic early warning signal is generated. The parameter inversion module, connected to the coupling determination module, is used to convert the velocity difference into geometric correction parameters for high-level deep hole blasting in response to the dynamic early warning signal. The geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof. The pressure relief control module is connected to the parameter inversion module and is used to perform deep hole blasting of key layers at high positions based on the axial deflection angle and the corresponding charge parameters, and to complete three-dimensional coordinated operations in conjunction with low-position pressure relief measures.

[0021] The present invention provides a dynamic early warning method and system for the manifestation of mining pressure in high-intensity mining faces, which has the following beneficial effects: This invention constructs a dual-velocity field coupling analysis model for mining advance and stress field migration, calculates the difference between the physical mining speed and the stress response speed of the surrounding rock, and combines this with a dynamic threshold set based on the lithological characteristics of key strata for state identification. This method can quantify the degree of asynchrony between mining disturbance and surrounding rock fracturing in time and space, promptly identify the energy accumulation state caused by the lag of roof fracture, solve the problem that traditional static monitoring methods are unable to capture the dynamic stress migration law, and improve the accuracy of early warning of dynamic disaster risks in high-intensity mining.

[0022] This invention establishes a blasting parameter inversion mechanism that responds to the energy accumulation state, mapping the velocity difference and accumulated energy index to dynamic explosive consumption, borehole spacing, and borehole elevation parameters. Under energy accumulation conditions, the system automatically increases explosive consumption and adjusts the borehole angle, utilizing explosive energy to overcome the high stress constraints within the surrounding rock. Furthermore, by changing the crack propagation direction, it shortens the equivalent arm of the cantilever beam, ensuring timely fracture and energy release of the deep, thick, and hard roof in the mining-induced stress accumulation zone.

[0023] This invention analyzes the characteristics of microseismic energy attenuation and acoustic wave velocity reduction after blasting to define the effective window period for rheological stress relief during rock mass damage development. Based on the duration of this window period, the mining machine's advance speed is dynamically matched. This control strategy ensures that cutting operations are performed during the period when rock mass fractures are most fully developed and have not yet been recompacted. It utilizes the rheological weakening effect after rock blasting to reduce equipment cutting resistance and surrounding rock support pressure, achieving synergistic optimization of mining efficiency and stress relief effect. Attached Figure Description

[0024] Figure 1 This is a system framework diagram of an embodiment of the present invention; Figure 2 This is a flowchart of a method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the spatiotemporal alignment and preprocessing logic for multi-source heterogeneous data in an embodiment of the present invention; Figure 4 This is a schematic diagram of the dual-velocity field solution logic for mining advancement and stress field migration in an embodiment of the present invention; Figure 5 This is a schematic diagram of the velocity difference coupling analysis and energy accumulation state identification logic in an embodiment of the present invention; Figure 6 This is a schematic diagram of the dynamic inversion process of blasting parameters based on velocity difference in an embodiment of the present invention; Figure 7 This is a schematic diagram of the three-dimensional collaborative decompression and rheological window utilization logic in an embodiment of the present invention; Figure 8 This is a real-time monitoring curve of the changes in the mining advance speed, stress field migration speed, and energy accumulation intensity index in an embodiment of the present invention.

[0025] Icon number explanation: 100. Multi-source monitoring module; 200. Velocity calculation module; 300. Coupling determination module; 400. Parameter inversion module; 500. Pressure relief and control module. Detailed Implementation

[0026] The technical solutions in 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 a part of the embodiments of the present invention, and not all of them. 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.

[0027] See Figure 1 , Figure 1 This is a logical structure block diagram of a dynamic early warning system for the manifestation pattern of mining pressure in a high-intensity mining face according to an embodiment of the present invention. The embodiment of the present invention provides a dynamic early warning system for the manifestation pattern of mining pressure in a high-intensity mining face, comprising: The multi-source monitoring module 100 is used to construct an overburden space structure model and deploy a multi-source monitoring array in the mining area of ​​the mining face; and based on the overburden space structure model, to collect real-time location data of mining equipment and surrounding rock mechanical response data characterizing the mineral pressure manifestation features. The velocity calculation module 200, connected to the multi-source monitoring module 100, is used to smooth the location data of the mining equipment and the surrounding rock mechanical response data that characterizes the mineral pressure manifestation characteristics, and then calculate the mining advance velocity vector that characterizes the mining disturbance intensity and the stress field migration velocity vector that characterizes the surrounding rock fracture response characteristics, respectively. The coupling determination module 300 is connected to the velocity calculation module 200 and is used to construct a velocity difference coupling analysis model, calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector, and determine that the mining face is in an energy lag accumulation state and generate a dynamic early warning signal when the velocity difference exceeds the preset threshold determined based on the overburden space structure model. The parameter inversion module 400 is connected to the coupling determination module 300. In response to the dynamic early warning signal, the module converts the velocity difference into geometric correction parameters for high-level deep hole blasting using a nonlinear mapping function based on the velocity difference. The geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof. The pressure relief control module 500 is connected to the parameter inversion module 400 and is used to perform deep hole blasting of key layers at high positions based on the axial deflection angle and the corresponding charge parameters, and to complete three-dimensional collaborative operation in conjunction with low-position pressure relief measures.

[0028] In the above scheme, the law of mine pressure manifestation refers to the dynamic migration and evolution of stress concentration zones and high-energy fracturing events (characterized by peak values ​​of advance support pressure and high-energy microseismic event clusters) in the overlying strata under mining disturbance, in space and time, and ultimately leading to roof failure and energy release. This is a quantifiable and predictable causal relationship and spatiotemporal evolution characteristic.

[0029] In the above scheme, the multi-source monitoring module 100 is responsible for performing data acquisition and preprocessing to establish a unified spatiotemporal benchmark. Specifically, the multi-source monitoring module 100 establishes a three-dimensional rectangular coordinate system covering the entire mining face and maps the static model data obtained from geological exploration into this three-dimensional rectangular coordinate system. The static model data is basic geological data obtained during the geological exploration stage that does not change in real time during the mining process. For the location data of mining equipment, the multi-source monitoring module 100 uses a sliding window mean filtering algorithm to process the original three-dimensional coordinate sequence, removing high-frequency random noise caused by underground environmental interference, and generating continuous equipment operating trajectories. For the surrounding rock stress data, the multi-source monitoring module 100 uses inverse distance weighted interpolation to process the discrete monitoring point data arranged in the advance roadway, constructing a continuous stress distribution curve along the roadway direction; based on this, the multi-source monitoring module 100 identifies the peak position of the advance support pressure by calculating the positions where the first derivative is zero and the second derivative is less than zero.

[0030] In the above scheme, the velocity calculation module 200 performs a dual-velocity field calculation process to quantify the dynamic correlation between mining operations and surrounding rock response. The mining advance velocity vector is the average displacement of the mining equipment in the advance direction within a unit time window. The velocity calculation module 200 integrates microseismic monitoring data and stress monitoring data when calculating the stress field migration velocity vector. Specifically, the velocity calculation module 200 first selects a subset of effective microseismic events within the time window, using the energy value of each microseismic event as a weighting coefficient to calculate the axial coordinates of the equivalent centroid of stress field energy release. Subsequently, the velocity calculation module 200 calculates the migration velocity components of the microseismic centroid coordinates over time and the migration velocity components of the peak point of the advance support pressure over time. Finally, the velocity calculation module 200 uses a weighted fusion strategy to synthesize the two velocity components into the final stress field migration velocity vector to reflect the overall movement trend of the stress concentration zone within the surrounding rock.

[0031] In the above scheme, the coupling judgment module 300 performs state identification based on the dynamic threshold of lithological characteristics and the energy accumulation intensity index. The preset threshold is determined by the coupling judgment module 300 according to the physical properties of the main key layer of the roof. Specifically, the coupling judgment module 300 sets the preset threshold to be positively correlated with the thickness and uniaxial compressive strength of the main key layer, and negatively correlated with the rock elastic modulus, thereby characterizing the rate difference tolerance for energy accumulation in different rock layers without sudden failure. At the same time, the coupling judgment module 300 uses an integral algorithm to calculate the energy accumulation intensity index. Taking the end time of the most recent roof cycle pressure as the starting point, it performs time integration and accumulation on the difference between the rate difference and the threshold for the time period before the current time where the rate difference exceeds the preset threshold. This index quantitatively characterizes the cumulative lag caused by the asynchronous mining rate and stress migration rate.

[0032] In the above scheme, the parameter inversion module 400 is responsible for determining the matching charge parameters. This process includes: the parameter inversion module 400 establishing a modified explosive unit consumption model based on the energy accumulation intensity index, using the standard rock explosive unit consumption as a benchmark, and calculating the dynamic explosive unit consumption using the energy accumulation intensity index; as the energy accumulation intensity index increases, the parameter inversion module 400 dynamically increases the dynamic explosive unit consumption.

[0033] In the above scheme, the parameter inversion module 400 further performs the parameter inversion step, converting the state index into physical blasting parameters. First, the parameter inversion module 400 uses the energy accumulation intensity index as a gain variable to calculate the dynamic explosive unit consumption, and increases the dynamic explosive unit consumption with the increase of accumulation intensity to overcome the stress constraint inside the surrounding rock. Second, the parameter inversion module 400 combines the single-hole charging capacity to invert the borehole spacing that can meet the dynamic explosive unit consumption requirements; when the calculated borehole spacing is less than the minimum safe spacing for drilling operations, the parameter inversion module 400 automatically switches to a double-row staggered arrangement mode, corrects the borehole spacing to twice the original calculated value, and adds a second row of boreholes, offsetting it relative to the first row along the strike direction by half of the corrected borehole spacing. Meanwhile, the parameter inversion module 400 dynamically compensates the borehole elevation angle based on the real-time speed difference, and adds an angle correction amount on top of the basic elevation angle. This correction amount is positively correlated with the ratio of the speed difference to the mining advance speed. The parameter inversion module 400 changes the direction of blast crack propagation by increasing the elevation angle, thereby shortening the equivalent arm length of the cantilever beam.

[0034] In the above scheme, after the three-dimensional collaborative operation is completed, the pressure relief control module 500 performs closed-loop control based on rheological characteristics. The pressure relief control module 500 identifies the effective window period for rheological pressure relief by monitoring the microseismic energy release rate and the acoustic wave velocity inside the rock mass in the blasting area. The identification is based on a preset ratio where the microseismic energy release rate drops to the background noise level and the acoustic wave velocity decreases to the velocity of intact rock mass. Based on this, the pressure relief control module 500 calculates the theoretical time required for the mining equipment to pass through the blasting area and compares this theoretical time with the remaining time of the effective window period for rheological pressure relief. If the theoretical time is longer than the remaining time, the pressure relief control module 500 issues an acceleration command to increase the traction speed, ensuring that the cutting operation is completed within the period when the rock mass is in its most damaged state, thus keeping the mining operation and the rheological damage state of the surrounding rock in a spatiotemporal synchronization.

[0035] See Figure 2 , Figure 2 This is a flowchart illustrating a dynamic early warning method for the manifestation pattern of mining pressure in a high-intensity mining face according to an embodiment of the present invention. The method, provided by this embodiment, includes the following steps: S1. Construct a spatial structure model of thick and hard overburden, and deploy a multi-source monitoring array including microseismic sensors, stress monitoring meters and equipment positioning devices in the mining face area to complete the initialization of the monitoring system.

[0036] Specifically, the deployment may include: Microseismic sensors are installed at intervals on the roof, floor, or sidewalls of the mining roadways on both sides of the mining face to pick up elastic wave signals induced by overburden fracturing in order to calculate the three-dimensional spatial location and energy of microseismic events. Stress monitoring gauges are installed in deep holes in the coal and rock mass ahead of the mining face to sense and collect the numerical changes in the advance support pressure in real time. Install equipment positioning devices on key components of the coal mining machine body or hydraulic support to track the dynamic spatial coordinates of the mining line in real time; The microseismic sensor, stress monitor and equipment positioning device are connected to the data processing terminal through the mining transmission network to perform unified time synchronization and reference zero-point calibration of multi-source data. S2, based on the overlying rock spatial structure model, real-time acquisition of mining equipment location data and surrounding rock mechanical response data, and after smoothing processing, calculation of the mining advance speed vector characterizing the mining disturbance intensity and the stress field migration speed vector characterizing the surrounding rock fracture response characteristics.

[0037] Specifically, real-time acquisition of mining equipment location data and surrounding rock mechanical response data based on the aforementioned overburden spatial structure model refers to using this overburden spatial structure model as a unified spatial benchmark and geological framework to guide and interpret the acquisition process of multi-source data. The three-dimensional coordinate system provided by this overburden spatial structure model ensures that the location and data of all monitoring equipment have a unified spatiotemporal reference. Simultaneously, the rock strata structure and lithological parameters included in this overburden spatial structure model (such as the derived overburden wave velocity model) are crucial for processing microseismic signals and calculating seismic source locations. Therefore, data acquisition is conducted within the precise spatial framework and geological technical definitions established by this overburden spatial structure model, thereby ensuring the accuracy and reliability of subsequent velocity calculations.

[0038] Specifically, the equipment positioning device deployed in step S1 is used to read the operating coordinate sequence of the coal mining machine or hydraulic support in real time as the location data of the mining equipment. At the same time, the microseismic sensor and stress monitoring meter deployed in step S1 are used to synchronously collect the spatiotemporal distribution information of microseismic events and the numerical change information of the advance support pressure. The spatiotemporal distribution information of microseismic events and the numerical change information of the advance support pressure together constitute the surrounding rock mechanical response data characterizing the mine pressure manifestation characteristics. Then, the above data is denoised and smoothed using a moving average or low-pass filtering algorithm. The mining advance speed vector is calculated based on the displacement of the equipment coordinates per unit time, and the stress field migration speed vector is calculated based on the spatial migration trend of the high-energy microseismic event accumulation area and the stress peak area.

[0039] Specifically, the overburden spatial structure model includes at least: the vertical layering sequence of the overburden strata on the working face, the thickness and depth of each stratum, the location of key strata, and their mechanical parameters. The mechanical parameters of the key strata include the uniaxial compressive strength, elastic modulus, and rock density of the key strata. Constructing the overburden spatial structure model includes: obtaining the layer thickness, spatial configuration, and lithological parameters of the overburden strata on the mining working face based on geological borehole, geophysical exploration, and / or laboratory test data, and establishing a three-dimensional digital geological model. The overburden spatial structure model also includes an overburden wave velocity model, which defines the propagation velocity of elastic waves in different strata to locate microseismic events. The overburden wave velocity model assigns corresponding P-wave velocity and / or S-wave velocity values ​​to different layers or zones of the overburden strata. The overburden spatial structure model provides a lithological parameter basis for determining the preset threshold, and the lithological parameters include at least the thickness, uniaxial compressive strength, and elastic modulus of the key strata in the top plate.

[0040] S3. Construct a velocity difference coupling analysis model, calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector, and when the velocity difference exceeds the preset threshold determined based on the overburden space structure model, determine that the high-intensity mining face is in a state of energy lag accumulation and generate a dynamic early warning signal.

[0041] S4, in response to the dynamic early warning signal, the velocity difference is converted into geometric correction parameters for high-level deep hole blasting using a nonlinear mapping function. The geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof.

[0042] The high-level deep-hole blasting refers to the long-bore blasting fracturing measure implemented on the thick and hard rock strata (i.e., high-level key strata) located directly above the coal seam and serving as the main source of mine pressure manifestation. Among them, "high-level" is defined as the key stratum where the final position of the borehole is located above the caving zone, and "deep hole" is defined as a borehole with a length sufficient to penetrate the immediate roof and extend into the interior of the high-level key stratum, and a hole depth greater than that of conventional shallow-hole blasting (usually greater than 5 or 10 meters, depending on specific geological conditions); the "immediate roof" refers to the roof stratum that is close to the coal seam and is the first to be damaged or collapsed under mining operations. The geometric correction parameters are used to precisely adjust the spatial attitude of the borehole to adapt to the energy accumulation state. In addition to at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof, they may also include the azimuth angle of the borehole on the horizontal projection plane relative to the roadway direction and the target depth of the borehole.

[0043] S5 performs deep-hole blasting of key high-level layers based on the calculated axial deflection angle and matching charge parameters, and completes three-dimensional coordinated operation in conjunction with low-level pressure relief measures.

[0044] The high-level key layer refers to a thick, hard rock layer located above the caving zone (usually within a fracture zone or a flexural subsidence zone), with a large thickness and high uniaxial compressive strength, which plays a major role in controlling the macroscopic movement of the overlying strata and the manifestation of mining pressure. The delayed fracture of this rock layer is the main force source for the formation of energy accumulation. Among them, the large thickness and high uniaxial compressive strength mean that the rock layer has a greater thickness and higher uniaxial compressive strength than the immediate roof strata, so that it can form an integral bearing structure during mining and play a major role in controlling the macroscopic movement of the overlying strata and the manifestation of mining pressure.

[0045] The aforementioned low-level stress relief measures refer to local stress release methods implemented within the coal seam itself and the immediate roof and other low-level rock masses in the mining roadway or working face coal wall area. Specifically, these measures may include large-diameter borehole stress relief, hydraulic fracturing, or shallow-hole loosening blasting.

[0046] The large-diameter borehole pressure relief method includes: constructing at least one pressure relief borehole in the surrounding rock of the mining roadway or the coal wall of the working face along a predetermined direction. The diameter of the pressure relief borehole is larger than that of a conventional anchor bolt hole or a conventional exploration hole. After the borehole is completed, the borehole is made to form a free surface and volume loss, so as to reduce the local constraint conditions of the coal and rock mass around the borehole and thus realize the local stress release.

[0047] The shallow-hole loosening blasting includes: constructing at least one blasting hole in the surrounding rock of the mining roadway or the coal wall of the working face, wherein the depth of the blasting hole is less than that used for deep-hole blasting of high-level key layers, and the final hole of the blasting hole is located inside the coal seam and / or the immediate roof stratum; loading explosives into the blasting hole and setting an initiating element, and setting a sealing medium in the direction of the blasting hole opening to form a sealing section; after detonation, forming a destruction zone in the coal and rock mass around the blasting hole, mainly characterized by fracture propagation and structural loosening, so as to reduce the overall stiffness of the near-field coal and rock mass and achieve local pressure relief.

[0048] By implementing deep-hole blasting on key high-level layers to cut off the far-field dynamic load source, and combining it with low-level pressure relief measures to improve the near-field static load environment, a three-dimensional coordinated pressure relief of the surrounding rock system of the working face can be achieved.

[0049] Furthermore, after step S5, the method may further include monitoring the change in velocity difference within the next time window to verify the depressurization effect, specifically including: Set a post-effect evaluation time window (i.e., a preset monitoring period after the blasting operation), during which the multi-source monitoring module 100 and the velocity calculation module 200 are continuously run to recalculate and track the evolution trend of the velocity difference between the mining advance velocity vector and the stress field migration velocity vector; The real-time speed difference within the post-effect evaluation time window is compared with the preset threshold: If the velocity difference is detected to show a convergent downward trend and fall back below the preset threshold, it indicates that the high-level key layer has been broken and the energy accumulation has been eliminated. The pressure relief is deemed effective and the system automatically resets to the normal monitoring state. If the speed difference is monitored to remain above the preset threshold or show a divergent upward trend, it indicates that the suspended structure has not yet become unstable and the pressure relief is insufficient. The system iteratively optimizes the geometric correction parameters based on the current residual speed difference and generates supplementary pressure relief construction instructions for the unbroken area.

[0050] The following section will provide a detailed explanation of the data processing, coupling analysis, and parameter inversion logic involved in the above steps.

[0051] See Figure 3 , Figure 3 This is a schematic diagram of the spatiotemporal alignment and preprocessing process for multi-source heterogeneous data according to an embodiment of the present invention. To provide a unified and accurate data foundation for subsequent dual-velocity field calculations, this method performs standardization and cleaning of multi-source data, specifically including the following sub-steps: Step S11: The multi-source monitoring module 100 establishes a three-dimensional rectangular coordinate system covering the entire working face as the geometric reference for data fusion. The origin of the coordinate system is the center point of the bottom plate of the mining face or the entrance of the air intake roadway. The direction of advance along the coal seam and the working face is defined as... The axis is defined along the dip direction of the coal seam and the length of the working face. The axis is defined as the direction that is perpendicularly upward through the overlying strata. Axis. The multi-source monitoring module 100 uses the contour lines of the coal seam floor, fault structure locations, and stratigraphic information of key layers obtained from geological exploration, based on this coordinate system. Perform coordinate transformation to construct a static geological space model that includes the goaf, working face, and advance support area; Among them, the goaf refers to the abandoned space behind the coalfield after the coal is mined out, where the overlying strata lose support and collapse, and the space is filled; the working face refers to the dynamic advancing space where fully mechanized mining equipment such as coal mining machines and hydraulic supports are arranged and coal cutting, loading and transportation operations are underway; the advanced support area refers to the solid coal area located in front of the coal wall of the working face that has not yet been mined. The solid coal area is affected by mining, resulting in stress redistribution and forming an advanced support pressure field with high stress concentration.

[0052] Step S12: The multi-source monitoring module 100 collects and analyzes the mining motion status data of the mining equipment, and generates a continuous equipment running trajectory after filtering. Specifically, this step obtains the sampling frequency by reading data from the inertial navigation system or infrared positioning sensor installed on the coal mining machine or tunneling machine. The three-dimensional coordinate sequence of the mining equipment. To address positioning noise caused by interference from underground environmental signals, the multi-source monitoring module 100 employs a sliding window mean filtering algorithm to process the original coordinate sequence. The time window length is set to... For the current moment The original coordinate observations Calculate the effective coordinate position after smoothing. : ; In the formula, For discrete sampling point index, The number of times before the current moment The coordinates of each sampling point The time window length is set. High-frequency random noise is removed through the above calculations to generate continuous mining equipment operation trajectory data.

[0053] In step S13, the multi-source monitoring module 100 acquires and filters effective surrounding rock fracture response data, and generates a set of effective microseismic events through double filtering.

[0054] Specifically, this step utilizes a microseismic sensor array deployed around the mining area to continuously receive elastic wave signals released by rock fractures. The multi-source monitoring module 100 calculates the source location and energy magnitude of the microseismic event based on the arrival time and waveform characteristics of P-waves and S-waves. Here, arrival time refers to the precise timestamp at which the first arrival signal of the microseismic elastic wave is sensed by each monitoring station in the sensor array.

[0055] The specific implementation process of this step is as follows: First, the arrival times of the P-wave and S-wave recorded by each sensor channel are automatically picked up using the long-short window energy ratio method (STA / LTA) to obtain arrival time data; Secondly, based on the pre-determined overburden wave velocity model, the least squares method or the Geiger iterative algorithm is used to establish a model containing the source coordinates (x, y, z) and the time of earthquake occurrence. The location equations are used to determine the epicenter location by minimizing the residual between the theoretical arrival time and the actual observed arrival time.

[0056] The overlying strata spatial structure model is a comprehensive digital model characterizing the overall geological structure and mechanical properties of the strata above the mining face. It includes static information such as strata layering, thickness, spatial distribution, and lithological mechanical parameters (e.g., elastic modulus, density). The overlying wave velocity model is a specific application and extension of the overlying strata spatial structure model in terms of elastic wave propagation characteristics. Based on the lithological layering and spatial location information provided by the former, it assigns corresponding P-wave and S-wave propagation velocity parameters to each specific stratum or area through methods such as borehole exposure, well logging data, or source calibration. Therefore, the overlying wave velocity model is a core subset or specific application branch of the overlying strata spatial structure model specifically serving microseismic monitoring and location analysis. Its essence is to transform the static geomechanical model into a physical parameter model that can be used for precise location of dynamic microseismic events.

[0057] The overburden wave velocity model refers to a velocity distribution model used to characterize the propagation characteristics of microseismic elastic waves in the working face and its overlying strata. It describes the propagation velocity of microseismic waves at different spatial locations and in different lithological media. The overburden wave velocity model includes at least P-wave velocity and / or S-wave velocity, and establishes a correspondence between wave velocity and location using spatial coordinates as independent variables. The overburden wave velocity model is constructed based on geological data of the mining area, stratum structure information, and measured wave velocity data. Specifically, it can be based on lithological stratification results revealed by boreholes, well logging data, and / or artificial source calibration experiments. A layered uniform model, a zoned uniform model, or a continuously varying model is used to assign wave velocity values ​​to the overburden, thereby forming a three-dimensional or quasi-three-dimensional wave velocity model that can reflect the differences in wave velocity between different strata and different lithological overburden media. In the process of microseismic event localization, the overburden wave velocity model is used to calculate the theoretical propagation time of microseismic waves from the source location to each monitoring station, and serves as the basis for the value of wave velocity parameters in the localization equation. By comparing with the actual observation time, the source coordinates and the time of occurrence are iteratively corrected, thereby improving the accuracy and stability of microseismic localization results.

[0058] Finally, by performing full-wavelength integration on the microseismic waveform signal, the time integral value of the velocity square is calculated, and combined with the geometric diffusion compensation coefficient and the medium attenuation coefficient, the energy released by the microseismic event is quantified. During the data cleaning stage, the multi-source monitoring module 100 executes dual filtering logic: first, it compares the production record timestamps to remove signals overlapping with the blasting operation time window; second, it sets a minimum energy threshold. Only retain energy High-energy microseismic events. The multi-source monitoring module 100 further verifies the source coordinates. Far-field events whose coordinate values ​​exceed the boundary of the monitoring area of ​​the working face are removed, and a sample set consisting of effective microseismic events is generated.

[0059] Step S14: The multi-source monitoring module 100 collects surrounding rock stress data and identifies the pressure peak point through interpolation and extreme value search.

[0060] Specifically, in this step, the multi-source monitoring module 100 constructs the spatial distribution characteristics of the advance support pressure. By collecting real-time monitoring values ​​from borehole stress gauges or anchor cable force gauges embedded in the advance roadway of the working face, discrete surrounding rock stress data are obtained. The advance roadway refers to the intake or return airway section located in front of the coal wall advance direction of the working face, which has not yet been mined but has been significantly affected by the mining stress field.

[0061] The borehole stress gauge is installed in the deep borehole of the coal and rock mass and is configured to sense and monitor the internal stress changes and the migration position of the peak bearing pressure in the deep surrounding rock. The anchor cable force gauge is installed at the end of the roadway surface support component and is configured to monitor the axial load of the support body and the deformation pressure of the shallow surface layer of the surrounding rock.

[0062] The combination of these two methods enables comprehensive monitoring of stress state from deep to shallow layers, and from the surrounding rock mass to the support structure. Given that physical sensors can only cover a limited number of discrete points, the multi-source monitoring module 100 employs an inverse distance-weighted interpolation method to construct a continuous stress distribution curve along the roadway's direction. For any point on the roadway axis... Its stress estimate The calculation is as follows: ; in, Let be the coordinates of any point on the tunnel axis where stress estimation is required. The total number of valid monitoring points participating in the calculation. For the first Measured stress values ​​at each monitoring point Point to be sought With the monitoring points The Euclidean distance between them The reciprocal of the square of the distance weight represents the first... Each monitoring point is required to make a request. The degree of influence. Based on this, the multi-source monitoring module 100 analyzes the continuous stress distribution curve. Perform an extremum search to identify the location of a maximum value that satisfies the following conditions: ; in, Stress distribution curve Regarding location The first derivative of represents the rate of change of stress; Stress distribution curve Regarding location The second derivative of the curve characterizes its concavity and convexity. The multi-source monitoring module 100 marks the location points that meet the above conditions as the peak points of the advanced support pressure.

[0063] In step S15, the multi-source monitoring module 100 performs spatiotemporal registration and fusion of multi-source data to generate a standard dataset of mining disturbance and surrounding rock mechanical response.

[0064] Specifically, the multi-source monitoring module 100 uses a unified network time clock as a reference to perform time synchronization correction on equipment positioning data, microseismic event data, and stress monitoring data, eliminating clock drift between subsystems. Spatially, all data points processed in steps S12 to S14 are uniformly projected into the three-dimensional Cartesian coordinate system established in step S11. After the above processing, a standard dataset containing mining disturbance input and surrounding rock mechanical response output is formed. This dataset accurately reflects the spatial correspondence between mining actions and surrounding rock conditions at the same moment.

[0065] See Figure 4 , Figure 4 This is a schematic diagram of the dual-velocity field solution logic for mining advance and stress field migration according to an embodiment of the present invention. To quantify the dynamic correlation characteristics between mining disturbance and surrounding rock response in the spatiotemporal dimension, the velocity solution module 200 performs dual-velocity field solution based on multi-source data preprocessing results. This process specifically includes the following sub-steps: Step S21: The velocity calculation module 200 establishes an average differential algorithm model based on a sliding time window to calculate the mining advance velocity vector that characterizes the physical mining intensity.

[0066] Specifically, given that the operation of coal mining machines or tunneling machines is affected by equipment maintenance, shift changes, and geological structures, exhibiting discontinuous and non-uniform motion characteristics, the velocity calculation module 200 establishes an average differential algorithm model based on a sliding time window. The time step is set. and the length of the sliding time window At the current moment Extract the past Within a time step, the center of the mining equipment moves along the direction of the working face advance (i.e., The coordinate sequence (axis direction). Calculate the smoothed physical propulsion velocity using the following formula. : ; in, for Average mining advance speed at any given time This represents the absolute coordinate position of the mining equipment along the propulsion axis at the current moment. To move forward from the current moment The device coordinates at each time step. This represents the total duration of the sliding time window. This calculation logic eliminates velocity fluctuations caused by short-term shutdowns through long-period position differentials, obtaining an average physical velocity index characterizing the overall propulsion intensity of the working face.

[0067] In step S22, the velocity calculation module 200 performs energy-weighted positioning of the effective microseismic events and calculates the axial coordinates of the center of mass of stress field energy release.

[0068] Specifically, under the conditions of high-intensity mining with a thick and hard roof, the movement of the peak stress within the surrounding rock is characterized by the distribution and migration features of microseismic high-energy events. The velocity calculation module 200 selects a time window. A subset of effective microseismic events is selected, and energy-weighted localization is performed on the microseismic events within this subset. The axial coordinates of the centroid of stress field energy release are then calculated. ; in, The equivalent centroid coordinates for stress field energy release within the current time window. This represents the total number of valid microseismic events selected within the current time window. For the first The energy released by a microseismic event For the first The formula uses the energy value as a weighting coefficient to calculate the coordinates of the centroid coordinates along the propagation direction of each microseismic event. It can physically reflect the spatial center location of the main fracture zone and stress concentration zone of the surrounding rock within the current time period.

[0069] Step S23: The velocity calculation module 200 calculates the microseismic centroid migration velocity component and the peak migration velocity component of the advanced support stress.

[0070] Specifically, the velocity calculation module 200 calculates the stress field migration velocity vector based on multi-source data fusion. To improve the anti-interference capability of the velocity index, the velocity calculation module 200 adopts a weighted fusion strategy of microseismic centroid migration velocity and peak migration velocity of the leading support pressure. First, based on the centroid coordinate change calculated in step S22, the components of the microseismic centroid migration velocity are calculated. : ; At the same time, the coordinates of the peak point of the advance support pressure identified in step S14 are called. Calculate the peak stress migration velocity component : ; Finally, the final stress field migration velocity vector is calculated using the weighted fusion formula. : ; in, For speed updates, it is preferable to set the update cycle to the duration of 1 to 2 mining shifts; and These are the coordinates of the energy release centroid and the peak support pressure point, respectively, for the previous calculation cycle; The weighting coefficient has a range of values. The weighting coefficients are biased towards microseismic data because microseismic monitoring has global coverage, while discrete stress monitoring points have locality. When the calculated... Less than This indicates that the migration of the stress concentration zone lags behind the advancement of the working face, and characterizes the mechanical state of energy accumulation in the roof strata.

[0071] See Figure 5 , Figure 5 This is a schematic diagram of velocity difference coupling analysis and state identification logic according to an embodiment of the present invention. To accurately identify the risk of dynamic disasters caused by roof fracture hysteresis under high-intensity mining conditions, the coupling determination module 300 performs dynamic coupling analysis based on the forward mining advance speed and the stress field migration speed. This process specifically includes the following sub-steps: In step S31, the coupling determination module 300 establishes a coupling calculation relationship between the velocity difference of the longwall advance and the stress response, and obtains the velocity difference value. This calculation relationship is based on the principle of energy conservation, and uses the longwall advance velocity calculated in step S21 as the basis for the calculation. Defined as the external engineering disturbance loading rate, the stress field migration velocity calculated in step S23 is... Defined as the rate of energy release and transfer within the surrounding rock. The coupling determination module 300 calculates both at the same time step. The algebraic difference is used to obtain the velocity difference. : ; in, This represents the asynchronous velocity difference between the mining disturbance and the surrounding rock response. When At that time, it indicates that the surrounding rock fracture responds promptly to mining, and the energy is in a dynamic equilibrium state of being released as mining progresses; when When the rate of advancement of the physical working face is greater than the rate of stress migration, the high-stress zone migrates with lag, resulting in an increase in the overhang length of the roof and the accumulation of elastic energy in the overhang area.

[0072] In step S32, the coupling determination module 300 sets a dynamic early warning threshold based on the lithological characteristics of the overburden. Considering that rock strata of different hardness have different storage capacities for deformation energy, the coupling determination module 300 sets the dynamic threshold according to the uniaxial compressive strength and thickness of the key layer of the top plate. : ; in, The maximum allowable speed deviation threshold, The thickness of the main key layer refers to the thickest, most physically and mechanically strong, and hard rock layer located in the overburden above the coal seam. Its deformation and fracture can control the synchronous movement of the overburden layers of the entire thickness from the location of this layer to the surface (that is, the fracture of this layer will cause all the rock layers above it to fracture or deform). For the uniaxial compressive strength of the key layer rock, For the elastic modulus of rock, This is a dimensionless empirical coefficient, ranging from 0.05 to 0.1. The physical meaning of the dynamic threshold determined by this formula is that the thicker the rock stratum, the higher its strength, and the smaller its elastic modulus, the greater the tolerance for the velocity difference that allows energy to accumulate without sudden fracture. This is achieved by introducing a coefficient with a time dimension. This ensured the threshold. The unit is the speed unit and the speed difference. They are comparable.

[0073] In step S33, the coupling determination module 300 performs logical identification of the energy accumulation state and generates a dynamic warning signal when the speed difference exceeds the dynamic threshold.

[0074] Specifically, the coupling determination module 300 will calculate the real-time velocity difference. With dynamic threshold Perform numerical comparison. If... The current working face is determined to be in a quasi-static unloading state, with sufficient energy release from the surrounding rock, and no warning is triggered. If The system determines that the current working face is in a state of energy lag and accumulation. In this state, the mining equipment is far from the original stress equilibrium zone, and the roof fracture line has not followed up in time, resulting in a large amount of bending elastic energy accumulating in the lateral cantilever beam structure of the goaf. The coupling judgment module 300 generates a dynamic early warning signal that includes the current difference value.

[0075] In step S34, the coupling determination module 300 quantifies the energy accumulation intensity and outputs the warning level, and transmits the key state parameters to the parameter inversion module 400.

[0076] Specifically, in order to provide quantitative basis for subsequent blasting parameter inversion, the coupling judgment module 300 calculates the energy accumulation intensity index based on an integral algorithm. : ; in, This refers to the end time of the most recent top plate cycle. For the current calculation time, For continuous time variables within the integration interval For time integral infinitesimal elements, This is a unit step function that outputs 1 when the input value is greater than 0, and 0 otherwise. It is used to accumulate only the velocity difference exceeding a threshold. For time variables The corresponding speed difference. The numerical value quantitatively characterizes the cumulative lag caused by speed asynchrony since the end of the previous cycle. The coupling determination module 300 uses this index... and real-time speed difference As a key state parameter, it is transmitted to the parameter inversion module 400.

[0077] See Figure 8 , Figure 8 This is a real-time monitoring curve of the changes in the mining advance speed, stress field migration speed, and energy accumulation intensity index according to an embodiment of the present invention. Figure 8 As shown, during the monitoring period, when the mining advance speed... (Solid line) Remains stable, while the stress field migration rate When the (dashed line) shows a significant decrease leading to separation between the two, the difference between them exceeds a preset threshold, thereby driving the energy accumulation intensity index. (Dotted line) shows a clear cumulative upward trend; the index stops growing when the two speeds resynchronize.

[0078] Finally, the coupling determination module 300 will use the index and real-time speed difference As a key state parameter, it is transmitted to the parameter inversion module 400.

[0079] See Figure 6 , Figure 6 This is a schematic diagram of a dynamic inversion process for blasting parameters based on velocity difference according to an embodiment of the present invention. To achieve precise weakening of the lagging roof and thus eliminate accumulated elastic energy, the parameter inversion module 400 converts the state indicators calculated in the preceding steps into executable physical blasting parameters. This process specifically includes the following sub-steps: Step S41: The parameter inversion module 400 establishes a modified explosive unit consumption model based on energy accumulation intensity to calculate the dynamic explosive unit consumption.

[0080] Specifically, traditional blasting designs typically use a fixed explosive consumption, which cannot adapt to the dynamic changes in roof stress state during mining. The parameter inversion module 400 uses the standard rock explosive consumption as a benchmark and incorporates the energy accumulation intensity index calculated in step S34. As a gain variable, calculate the required dynamic explosive consumption in the current state. : ; in, For the current moment Regarding the required rock explosive consumption per unit volume for roof weakening, This is the basic explosive consumption value determined based on the Protodyakonov coefficient of the rock. The blasting enhancement factor, ranging from 0.2 to 0.5, is used to adjust the response sensitivity to the energy accumulation state. The energy accumulation intensity index at the current moment. The preset energy accumulation limit constant is determined based on the maximum accumulated hysteresis energy at the time of the initial fracture of the roof in historical mining data. This formula indicates that as the degree of energy accumulation increases, the parameter inversion module 400 will dynamically increase the explosive consumption per unit to overcome the additional constraints caused by high stress locking inside the surrounding rock.

[0081] Step S42: The parameter inversion module 400 inverts the borehole spacing parameters for deep hole blasting based on the single-hole charging capability.

[0082] Specifically, after determining the dynamic explosive unit consumption Subsequently, the parameter inversion module 400, in conjunction with the borehole diameter and single-hole charge capacity, calculates the borehole spacing that can meet the unit consumption requirement. Considering that the charge amount per borehole is limited by the borehole depth and sealing process, the parameter inversion module 400 first determines the maximum charge amount per borehole based on the linear charge density and effective charge length, and then calculates the optimal borehole spacing using the following formula: ; in, The spacing between blast holes is the distance between the blast holes arranged along the dip of the working face. This is the maximum charge per hole, and its value is equal to the linear charge density. The product of the effective charge length and the linear charge density refers to the mass of explosives loaded per unit length in the axial direction of the borehole. The density parameter of the linear charge is determined by both the borehole diameter and the bulk density of the explosive. The specific value is equal to the cross-sectional area of ​​the borehole (calculated based on the drill bit diameter) multiplied by the standard bulk density of the selected explosive (e.g., emulsion explosive or ammonium nitrate explosive). This refers to the distance between the blasting resistance line and the borehole spacing. This represents the effective failure depth of the blast hole. This calculation is used to determine when an increase in the difference between the mining rate and the stress migration rate leads to... When raised, the parameter inversion module 400 automatically reduces the borehole spacing. This allows for the input of more chemical energy into the unit rock mass to induce roof fracture.

[0083] Step S43: The parameter inversion module 400 adjusts the drilling angle based on the real-time speed difference.

[0084] Specifically, in order for the blasting cracks to effectively cut off the root of the cantilever beam and induce it to rotate towards the goaf side, the parameter inversion module 400 calculates the real-time velocity difference based on step S31. Dynamic compensation is applied to the borehole elevation angle. The base elevation angle is set as follows: Calculate the dynamic construction elevation angle : ; in, The angle between the borehole axis and the horizontal plane. The basic cutting angle is designed for normal mining conditions. This is the angle correction factor. The speed difference Given the current mining progress rate, The arctangent function is used to map a dimensionless velocity ratio to an angle correction. The physical meaning of this formula is: when the velocity difference... When the angle increases, it indicates an increase in the overhang hysteresis distance, which is achieved by increasing the elevation angle. This alters the direction of crack propagation, mechanically shortening the equivalent arm length of the cantilever beam and reducing the ultimate bending moment required for rock mass fracture.

[0085] In step S44, the parameter inversion module 400 generates a digital blasting construction instruction set.

[0086] Specifically, the parameter inversion module 400 will use the dynamic explosive unit consumption calculated above. Hole spacing and construction elevation angle The system performs formatted encapsulation and, combined with the current working face mileage, generates a construction parameter table containing borehole coordinates, angles, depths, and charge quantities. The parameter inversion module 400 incorporates built-in safety verification logic; if the currently calculated borehole spacing... Less than the minimum safe distance for drilling operations Then, the parameter inversion module 400 will automatically switch to the double-row staggered arrangement mode. In the double-row staggered arrangement mode, the parameter inversion module 400 will correct the output borehole spacing to... A second row of borehole coordinates is added to the construction parameter table, with the second row of borehole coordinates offset relative to the first row of borehole coordinates along the strike direction. This results in a staggered, quincunx-shaped arrangement of piles. This processing logic ensures that the minimum construction safety spacing is met. Under physical constraints, the total charge density within a unit rock mass is maintained in accordance with the calculation requirements of step S41.

[0087] See Figure 7 , Figure 7 This is a schematic diagram of a three-dimensional collaborative pressure relief and rheological window utilization logic according to an embodiment of the present invention. To ensure the accurate implementation of blasting parameters on-site and to achieve low-energy propulsion by utilizing the rheological properties of the rock mass after blasting, the pressure relief control module 500 executes three-dimensional collaborative pressure relief and rheological window utilization. This process specifically includes the following sub-steps: In step S51, the pressure relief control module 500 performs physical mapping and construction control of digital blasting parameters. This construction control includes controlling the drilling rig to operate according to the dynamic elevation angle and borehole spacing. The pressure relief control module 500 receives the construction parameter table containing borehole coordinates, angles, depths, and charge quantities generated by the parameter inversion module 400 and converts it into execution instructions for automated drilling equipment. During construction, the pressure relief control module 500 controls the drilling rig to operate according to the calculated dynamic elevation angle and borehole spacing. For areas with double-row staggered arrangements, after completing the first row of boreholes, the pressure relief control module 500 controls the drilling rig to automatically adjust the chassis position or drill arm posture, maintaining the specified row spacing and axial offset for the second row of boreholes, ensuring the formation of a spatially precise and uniformly distributed blasting pre-splitting structure within the top strata.

[0088] In step S52, the pressure relief control module 500 employs a micro-differential segmented detonation strategy to form a three-dimensional pressure relief fracture network. To construct a continuous three-dimensional weakened structure within the key rock strata, the pressure relief control module 500 does not use synchronous detonation but instead employs a micro-differential segmented detonation strategy. The pressure relief control module 500 controls the electronic detonators to detonate sequentially from low-position holes to high-position holes, and from the middle to the two wings. This detonation sequence utilizes the superposition effect of explosive stress waves and the principle of free surface reflection, allowing the first detonated holes to provide new free surfaces for the subsequent detonated holes, thereby forming an interwoven three-dimensional fracture network in the deep rock mass. This three-dimensional fracture network severs the mechanical connection of the lateral cantilever beams in the goaf, transforming the originally complete thick and hard roof into a loosely structured block structure, achieving three-dimensional pressure relief of the high-stress concentration zone of the surrounding rock.

[0089] Step S53: The pressure relief control module 500 monitors the changes in microseismic energy and wave velocity after blasting to define the effective window period for rheological pressure relief. Specifically, the pressure relief control module 500 identifies the rheological time window based on the characteristics of surrounding rock damage evolution. After the rock mass is subjected to strong disturbance by blasting, its internal damage and fracture propagation are not completed instantaneously, but exhibit obvious time correlation, i.e., rheological characteristics. The pressure relief control module 500 determines the optimal mining advancement time window by analyzing the attenuation law of microseismic events after blasting. Specifically, the pressure relief control module 500 continuously monitors the changes in microseismic energy release rate and ultrasonic wave velocity in the blasting area. When the microseismic energy release rate is detected to fall from its peak and remain at the background noise level before blasting, and at the same time the sound wave velocity inside the rock mass decreases to a certain proportion (e.g., 0.6 to 0.7 times) of the wave velocity of intact rock mass that has not been disturbed by blasting, it is determined that the rock mass fracture development is sufficient and has not yet entered the compaction enhancement stage. The pressure relief control module 500 defines the effective window period for rheological pressure relief as the time from the moment when the above judgment conditions are met until the moment when the wave velocity of the rock mass begins to rise due to the recompaction of the rock mass caused by mining stress.

[0090] In step S54, the pressure relief control module 500 performs dynamic matching of the mining speed based on the rheological window. To fully utilize the weakening effect of the rock mass after blasting and reduce the cutting resistance of the coal mining machine and the load pressure on the hydraulic supports, the pressure relief control module 500 adjusts the traction speed of the coal mining machine in reverse according to the determined effective window length for rheological pressure relief. The pressure relief control module 500 first calculates the theoretical time required for the working face to pass through the blasting area. This theoretical time is equal to the quotient of the blasting area's strike length and the current traction speed of the coal mining machine. Subsequently, the pressure relief control module 500 compares this theoretical time with the remaining time of the effective rheological pressure relief window. If the theoretical time is longer than the remaining time of the window, the pressure relief control module 500 issues an acceleration command within the rated traction speed range of the coal mining machine, increasing the traction speed to ensure that the cutting operation is completed when the rock mass is in its maximum damaged state. If the theoretical time is less than or equal to the remaining time of the window, the current speed is maintained or the speed is appropriately reduced to reduce cutting tooth wear, provided that production capacity is met. Through the above control strategy, the pressure relief and regulation module 500 keeps the mining operation period and the rheological damage state of the surrounding rock synchronized in time and space.

[0091] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A dynamic early warning method for the manifestation pattern of mining pressure in high-intensity mining faces, characterized in that, Includes the following steps: A spatial structure model of the overburden was constructed, and a multi-source monitoring array was deployed in the mining area of ​​the mining face; Based on the overlying rock spatial structure model, the location data of mining equipment and the mechanical response data of surrounding rock that characterizes the mineral pressure manifestation are collected in real time. After smoothing, the mining advance speed vector that characterizes the mining disturbance intensity and the stress field migration speed vector that characterizes the surrounding rock fracture response characteristics are calculated respectively. Calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector. When the velocity difference exceeds a preset threshold determined based on the overburden space structure model, determine that the mining face is in a state of energy lag accumulation and generate a dynamic early warning signal. In response to the dynamic early warning signal, the velocity difference is converted into geometric correction parameters for high-level deep hole blasting, and the geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof. Based on the axial deflection angle and the corresponding charge parameters, high-level key layer deep hole blasting is carried out, and low-level pressure relief measures are used to complete three-dimensional collaborative operations; The calculation of the stress field migration velocity vector characterizing the fracture response of the surrounding rock includes: A subset of effective microseismic events within a time window is selected, and energy-weighted localization is performed on the microseismic events within the subset of effective microseismic events to calculate the axial coordinates of the stress field energy release centroid. The micro-vibration centroid migration velocity component is calculated based on the change of the axial coordinate over time, and the stress peak migration velocity component is calculated based on the change of the peak point of the advance support pressure over time. The microseismic centroid migration velocity component and the stress peak migration velocity component are synthesized using a weighted fusion strategy to obtain the final stress field migration velocity vector. Wherein, the mining advance speed vector is the average displacement of the mining equipment in the advance direction within a unit time window; The process of converting the velocity difference into geometric correction parameters for high-altitude deep-hole blasting includes: Determine the borehole spacing that can meet the dynamic explosive unit consumption requirements; when the velocity difference increases, leading to an increase in dynamic explosive unit consumption, reduce the borehole spacing. Dynamic compensation is performed on the borehole elevation angle based on the speed difference; The process of determining that the mining face is in a state of energy lag accumulation and generating a dynamic early warning signal further includes: Starting from the end time of the most recent top plate cycle, the energy accumulation intensity index is obtained by time integral accumulation of the difference between the velocity difference and the preset threshold during the time period before the current time when the velocity difference exceeds the preset threshold. The process of determining the matching propellant parameters includes: A modified explosive unit consumption model based on the energy accumulation intensity index is established. Using the standard rock explosive unit consumption as a benchmark, the dynamic explosive unit consumption is calculated using the energy accumulation intensity index. As the energy accumulation intensity index increases, the dynamic explosive consumption increases dynamically. The aforementioned low-level stress relief measures refer to localized stress release methods implemented within the coal face of the mining roadway or working face, targeting the low-level rock mass, including the coal seam itself and the immediate roof.

2. The method for dynamic early warning of the manifestation law of mine pressure in high-intensity mining faces according to claim 1, characterized in that, The real-time acquisition of mining equipment location data and surrounding rock mechanical response data characterizing the mineral pressure manifestation features are smoothed, including: A sliding window mean filtering algorithm is used to process the three-dimensional coordinate sequence of the mining equipment, remove positioning noise, and generate a continuous running trajectory. The discrete stress monitoring values ​​in the advance section of the mining roadway are processed by the inverse distance weighted interpolation method to construct a continuous stress distribution curve along the roadway direction. The extreme value search is then performed on the continuous stress distribution curve to identify the peak point of the advance support pressure.

3. The method for dynamic early warning of the manifestation law of mine pressure in high-intensity mining faces according to claim 1, characterized in that, The process of setting the preset threshold includes: Obtain the thickness parameters, uniaxial compressive strength parameters, and rock elastic modulus parameters of the main critical layer of the top plate; The maximum allowable velocity deviation threshold is determined based on the thickness parameter, uniaxial compressive strength parameter, and rock elastic modulus parameter.

4. The method for dynamic early warning of the manifestation law of mine pressure in high-intensity mining faces according to claim 1, characterized in that, The process of generating the geometric correction parameters also includes: Determine whether the calculated borehole spacing is less than the minimum safe distance for drilling operations; If the distance is less than the minimum safe distance, switch to the double-row staggered arrangement mode, correct the output borehole spacing to twice the original calculated value, and add a row of borehole coordinates to the construction parameter table. The second row of borehole coordinates is offset relative to the first row of borehole coordinates along the direction of the correction to half of the borehole spacing.

5. The method for dynamic early warning of the manifestation law of mine pressure in high-intensity mining faces according to claim 1, characterized in that, After completing the three-dimensional collaborative operation, it also includes: Determine the optimal weakening period of the surrounding rock after blasting; Based on the optimal weakening period, the advancing speed of the longwall face is dynamically adjusted so that the cutting operation is completed within the optimal weakening period.

6. A dynamic early warning system for the manifestation pattern of mining pressure in high-intensity mining faces, characterized in that, The system implements the dynamic early warning method for the manifestation of mining pressure in high-intensity mining faces according to any one of claims 1-5, wherein the system comprises: The multi-source monitoring module is used to construct an overburden spatial structure model and deploy a multi-source monitoring array in the mining area of ​​the mining face; and based on the overburden spatial structure model, to collect real-time data on the location of mining equipment and the mechanical response data of the surrounding rock that characterizes the mineral pressure manifestation. The velocity calculation module is used to smooth the location data of the mining equipment and the surrounding rock mechanical response data that characterizes the mineral pressure manifestation characteristics, and then calculate the mining advance velocity vector that characterizes the mining disturbance intensity and the stress field migration velocity vector that characterizes the surrounding rock fracture response characteristics, respectively. The coupling determination module is used to calculate the velocity difference between the mining advance velocity vector and the stress field migration velocity vector. When the velocity difference exceeds a preset threshold determined based on the overburden space structure model, the mining face is determined to be in a state of energy lag accumulation and a dynamic early warning signal is generated. The parameter inversion module is used to convert the velocity difference into geometric correction parameters for high-level deep hole blasting in response to the dynamic early warning signal. The geometric correction parameters include at least the axial deflection angle of the borehole relative to the vertical line of the roadway roof. The pressure relief control module is used to perform deep hole blasting of key layers at high positions based on the axial deflection angle and the corresponding charge parameters, and to complete three-dimensional coordinated operations in conjunction with low-position pressure relief measures.

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