Mining monitoring device and method for spatial arrangement of deep thick ore body three-dimensional panel
By deploying a multi-field collaborative monitoring system, mining-induced stress and microseismic information are collected and processed simultaneously, generating a state data sequence synchronized with the mining timeline. This solves the problem of accurately identifying precursors of rock mass instability in deep, thick, three-dimensional orebody panels, and improves the timeliness of early warnings and the accuracy of risk assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SINOSTEEL MAANSHAN INST OF MINING RES CO LTD
- Filing Date
- 2026-03-19
- Publication Date
- 2026-07-21
AI Technical Summary
In existing technologies, the mining monitoring methods for deep, thick, three-dimensional ore bodies lack the spatiotemporal synchronous integration of multi-field data, making it impossible to accurately identify precursors of rock mass instability, resulting in poor early warning timeliness and inaccurate risk assessment.
A multi-field collaborative monitoring system is deployed, including a distributed mining-induced stress monitoring system and an independent microseismic monitoring array. Data is collected synchronously and matched with time and spatial references to generate a panel state data sequence synchronized with the mining timeline. The stress concentration factor and microseismic activity index are calculated, and the precursors of rock mass instability are identified based on their temporal coupling evolution characteristics.
It has achieved effective integration of multi-source data, accurately captured complex spatiotemporal coupling characteristics, improved the timeliness of early warning and the accuracy of risk assessment, and ensured safe production in the three-dimensional mining of deep and thick ore bodies.
Smart Images
Figure CN122430892A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of ore body mining technology, and more specifically, to a mining monitoring device and method for a three-dimensional panel spatial arrangement of a deep, thick ore body. Background Technology
[0002] In the mining of deep, thick ore bodies, with the increase in ore body burial depth and the expansion of mining scale, the use of three-dimensional panel spatial layout has become a common practice. This layout involves the simultaneous mining of multiple intermediate sections, resulting in a highly complex spatiotemporal coupling evolution of the mining-induced stress field and rock mass fracturing activity. This can easily induce local rock mass instability events, such as roof collapse or pillar failure, thereby threatening the safe production of the mine.
[0003] While existing technologies include single monitoring methods such as mining stress monitoring or microseismic monitoring, these methods often operate independently and lack the spatiotemporal synchronization of multi-field data. They cannot accurately capture the temporal coupling characteristics of stress concentration and microseismic activity, making it difficult to effectively identify local rock mass instability precursors in three-dimensional panels, resulting in poor early warning timeliness and inaccurate risk assessment. Summary of the Invention
[0004] This application provides a mining monitoring device and method for a three-dimensional panel layout of a deep, thick ore body, which can solve the technical problem in the prior art that the lack of spatiotemporal synchronization and integration of multiple monitoring data makes it impossible to accurately identify the precursors of rock mass instability.
[0005] In a first aspect, this application provides a method for monitoring mining activity in a three-dimensional panel layout of a deep, thick ore body, comprising the following steps: For the three-dimensional mining panel of deep and thick ore bodies, a multi-field collaborative monitoring system is deployed. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously collects mining stress data and microseismic information throughout the entire mining process of the panel. The mining-induced stress data and microseismic information are synchronized in time and matched with spatial references to generate a panel state data sequence synchronized with the mining timeline; From the state data sequence, stress concentration factor and microseismic activity index are calculated and generated; Based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index, the precursors of local rock mass instability in the three-dimensional disk area are identified.
[0006] Furthermore, calculating and generating stress concentration factors from the state data sequence specifically includes: The original rock stress reference value is obtained at each monitoring point in the three-dimensional panel area. The original rock stress reference value is determined in advance by the original rock stress test experiment independent of the mining monitoring system before the panel area is mined. Simultaneously extract the real-time maximum principal stress value of each monitoring point in the state data sequence; For each monitoring point, the ratio of the real-time maximum principal stress value to its corresponding original rock stress benchmark value is calculated to generate a sequence of point stress concentration coefficients that change with the mining time. By using spatial interpolation methods, the stress concentration coefficient sequence of all monitoring points within the three-dimensional panel area is collected to generate three-dimensional stress concentration coefficient field distribution data for the panel area.
[0007] Furthermore, the process of synchronizing the mining-induced stress data and microseismic information in time and matching them with spatial references to generate a panel state data sequence synchronized with the mining timeline specifically includes: The mining-induced stress data is used to generate a single-point stress time series with timestamps based on the monitoring points; Microseismic information is used to generate event data records with timestamps and spatial coordinates. The single-point stress time series and the microseismic event data are recorded, aligned based on a unified time axis, and jointly associated with a pre-divided three-dimensional spatial analysis grid of the disk area, forming a multi-source state sequence dataset of the disk area that simultaneously contains stress state and microseismic activity within each time-space grid.
[0008] Furthermore, based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index, the specific methods for identifying local rock mass instability precursors in the three-dimensional disk area include: On the three-dimensional spatial model of the three-dimensional panel, several potential instability risk carriers are delineated as monitoring and analysis units. The risk carriers include at least the middle section pillar, the stope roof and the fault fracture zone. The three-dimensional stress concentration coefficient field distribution data of the disk area is mapped to each risk carrier, and the maximum stress concentration coefficient and its rate of change inside each risk carrier are extracted. Spatial clustering of microseismic information is performed, and microseismic events whose spatial locations fall within the preset influence range of the risk carrier are associated with the corresponding risk carrier. The microseismic activity index of each risk carrier within a preset time window is statistically analyzed. The microseismic activity index includes at least the frequency of microseismic events and the energy release rate. The preset time window is set based on the cyclic advance of panel mining and the intermediate mining step distance. For each risk carrier, the temporal correspondence between the rate of change of its maximum stress concentration factor and the microseismic activity index is analyzed. When the maximum stress concentration factor of a certain risk carrier continues to increase and the rate of change exceeds the first threshold, and the associated microseismic activity index changes from calm to active and exceeds the second threshold, it is determined that there are precursors to rock mass instability in this local risk carrier.
[0009] Furthermore, the distributed mining stress monitoring system includes distributed optical fiber sensing units deployed along the main roadways or orebody strike of the three-dimensional panel, used to acquire mining strain / stress data continuously distributed along the sensing path.
[0010] Furthermore, the independent microseismic monitoring array consists of multiple seismic sensors arranged in different layers and regions of the three-dimensional disk area. By analyzing the waveforms and time differences received by each seismic sensor, the spatial location and energy parameters of the microseismic events can be retrieved.
[0011] Furthermore, after identifying the precursors of rock mass instability in the local area of the three-dimensional panel, it also includes: Based on the identified precursors of rock mass instability and their location on the risk carrier, early warning information is generated, including the risk level, the expected instability type, and the scope of impact. The expected instability type corresponds one-to-one with the risk carrier type. The early warning information is then visualized and integrated with the three-dimensional mining progress model of the three-dimensional panel before being output.
[0012] Secondly, this application provides a mining monitoring device with a spatial arrangement of a three-dimensional panel in a deep, thick ore body, comprising: The acquisition module is used to deploy a multi-field collaborative monitoring system for the three-dimensional mining panel of deep and thick ore bodies. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously acquires mining stress data and microseismic information throughout the entire mining process of the panel. The processing module is used to synchronize the mining stress data and microseismic information in time and match them with spatial references to generate a panel state data sequence synchronized with the mining time sequence. The processing module is also used to calculate and generate stress concentration factor and microseismic activity index from the state data sequence; The execution module is used to identify the precursors of rock mass instability in the three-dimensional disk area based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index.
[0013] Thirdly, this application provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described method for monitoring mining activity in the spatial arrangement of a deep, thick ore body in a three-dimensional panel.
[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-mentioned method for monitoring the mining activity of a three-dimensional panel layout in a deep, thick ore body.
[0015] The technical solution of this application has the following beneficial effects: This application utilizes a multi-field collaborative monitoring system to simultaneously acquire mining-induced stress data and microseismic information, performing temporal synchronization and spatial benchmark matching to generate a panel state data sequence synchronized with the mining timeline. Furthermore, it calculates stress concentration factors and microseismic activity indices, and identifies precursors to rock mass instability based on their temporal coupling evolution characteristics. This method effectively integrates multi-source data, accurately captures complex spatiotemporal coupling characteristics, improves the timeliness of early warning and the accuracy of risk assessment, and ensures safe production in the three-dimensional mining of deep, thick ore bodies. Attached Figure Description
[0016] Figure 1 This is an exemplary flowchart of a mining monitoring method for a three-dimensional panel spatial arrangement of a deep, thick ore body, according to some embodiments of this application. Figure 2 This is a schematic diagram of the structure of a mining monitoring device arranged in a three-dimensional panel of a deep, thick ore body, according to some embodiments of this application. Figure 3 This is a schematic diagram of the structure of a computer device for monitoring mining activity in a three-dimensional panel layout of a deep, thick ore body, according to some embodiments of this application. Detailed Implementation
[0017] To better understand the above technical solutions, a detailed description of the solutions will be provided below in conjunction with the accompanying drawings and specific implementation methods. (Reference) Figure 1 The figure is an exemplary flowchart of a mining activity monitoring method for a three-dimensional panel layout of a deep, thick ore body, according to some embodiments of this application. The method mainly includes the following steps: In step 101, a multi-field collaborative monitoring system is deployed for the three-dimensional mining panel of the deep and thick ore body. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously collects mining stress data and microseismic information throughout the entire mining process of the panel.
[0018] Among them, the three-dimensional mining panel refers to the spatial arrangement structure adopted by deep and thick ore bodies. For example, according to the occurrence conditions of the ore body, the ore body is divided into multiple intermediate panels and mined in a three-dimensional arrangement. This will not be elaborated here.
[0019] In some embodiments, the distributed mining-induced stress monitoring system may include distributed fiber optic sensing units deployed along the main roadways or orebody strike of the three-dimensional panel, used to acquire mining-induced strain / stress data continuously distributed along the sensing path. The independent microseismic monitoring array may consist of multiple seismic sensors arranged at different layers and regions of the three-dimensional panel; by analyzing the waveforms and time differences received by each seismic sensor, the spatial location and energy parameters of microseismic events can be inverted.
[0020] In step 102, the mining stress data and microseismic information are synchronized in time and matched with spatial references to generate a panel state data sequence synchronized with the mining time sequence.
[0021] In some embodiments, the time synchronization and spatial reference matching of the mining-induced stress data and microseismic information to generate a panel state data sequence synchronized with the mining time sequence can be specifically carried out in the following manner: The mining-induced stress data is used to generate a single-point stress time series with timestamps based on the monitoring points; Microseismic information is used to generate event data records with timestamps and spatial coordinates. The single-point stress time series and the microseismic event data are recorded, aligned based on a unified time axis, and jointly associated with a pre-divided three-dimensional spatial analysis grid of the disk area, forming a multi-source state sequence dataset of the disk area that simultaneously contains stress state and microseismic activity within each time-space grid.
[0022] The unified timeline can be achieved using a high-precision GPS clock or a unified clock system for the mining area, ensuring millisecond-level alignment accuracy between stress data and microseismic events. The pre-divided three-dimensional spatial analysis grid for the ore body can be set based on the ore body geometry model and mining step distance, for example, a grid size of 5m × 5m × 5m, which will not be elaborated further here.
[0023] In step 103, stress concentration factor and microseismic activity index are calculated and generated from the state data sequence.
[0024] Among them, the stress concentration factor reflects the local amplification effect of the stress field during mining, and the microseismic activity index reflects the dynamic process of micro-fracture in the rock mass. The original rock stress reference values at each monitoring point within the three-dimensional panel used in this step were pre-determined through original rock stress testing experiments independent of the mining monitoring system before panel mining and during the deployment stage of the monitoring system, and serve as fixed reference parameters for calculation in this step. In some embodiments, the stress concentration factor can be calculated from the state data sequence in the following specific manner: Retrieve the original rock stress baseline values at each monitoring point within the three-dimensional panel area; Simultaneously extract the real-time maximum principal stress value of each monitoring point in the state data sequence; For each monitoring point, the ratio of the real-time maximum principal stress value to its corresponding original rock stress benchmark value is calculated to generate a sequence of point stress concentration coefficients that change with the mining time. By using spatial interpolation methods, the stress concentration coefficient sequence of all monitoring points within the three-dimensional panel area is collected to generate three-dimensional stress concentration coefficient field distribution data for the panel area.
[0025] Among them, the calculation of microseismic activity index focuses on the potential instability risk carriers of the three-dimensional panel. Based on the mining sequence, it statistically quantifies effective microseismic events within the defined spatiotemporal boundaries, and finally generates standardized indicators that can be used for time-series coupling analysis with stress concentration coefficients. Specifically, the calculation of microseismic activity index can be based on event statistics within a preset time window. For example, the event frequency is the total number of microseismic events within the time window, and the energy release rate is the cumulative value of event energy. That is, for each risk carrier's specific event set, the core index calculation is completed within a single time window. The core covers two basic indicators: microseismic event frequency, which is used to directly count the total number of effective microseismic events associated with the risk carrier within the time window, reflecting the active frequency of rock mass fracturing; and energy release rate, which is obtained by first accumulating the total energy of microseismic radiation from all associated events within the time window, and then dividing by the time window duration to obtain the energy release rate per unit time, reflecting the intensity and severity of rock mass fracturing. Slide a preset time window along a unified mining time axis, repeat the index calculation steps within the single time window, and generate a time series sequence of microseismic activity indexes for each risk carrier that changes continuously with the mining time sequence. Then, align this time series sequence with the synchronous stress concentration factor sequence in time and space to ensure that the time series benchmarks of the two types of indicators are completely unified.
[0026] In step 104, based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index, the precursors of local rock mass instability in the three-dimensional disk area are identified.
[0027] In some embodiments, the following methods can be used to determine the precursors of local rock mass instability in a three-dimensional disk based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index: On the three-dimensional spatial model of the three-dimensional panel, several potential instability risk carriers are delineated as monitoring and analysis units. The risk carriers include at least the middle section pillar, the stope roof and the fault fracture zone. The three-dimensional stress concentration coefficient field distribution data of the disk area is mapped to each risk carrier, and the maximum stress concentration coefficient and its rate of change inside each risk carrier are extracted. Spatial clustering of microseismic information is performed, and microseismic events whose spatial locations fall within the preset influence range of the risk carrier are associated with the corresponding risk carrier. The microseismic activity index of each risk carrier within a preset time window is statistically analyzed. The microseismic activity index includes at least the frequency of microseismic events and the energy release rate. The preset time window is set based on the cyclic advance of panel mining and the intermediate mining step distance. For each risk carrier, the temporal correspondence between the rate of change of its maximum stress concentration factor and the microseismic activity index is analyzed. When the maximum stress concentration factor of a certain risk carrier continues to increase and the rate of change exceeds the first threshold, and the associated microseismic activity index changes from calm to active and exceeds the second threshold, it is determined that there are precursors to rock mass instability in this local risk carrier.
[0028] In practice, the three-dimensional spatial model of the three-dimensional panel can be constructed based on GB / T 33444-2016 "Specification for Three-Dimensional Modeling of Metal and Non-metal Mines". The first threshold and the second threshold can be set based on historical data or rock mechanics experiments. For example, the first threshold is 1.5 and the second threshold is twice the preset baseline. This is only an example and is not intended to limit the specific application.
[0029] It should be noted that mine monitoring and early warning systems often provide general alarm signals without clearly defined risk levels, instability types, or affected areas. This makes it difficult for on-site personnel to quickly develop targeted prevention and control measures, easily leading to delayed responses and improper handling. Therefore, this application, after identifying precursors to rock mass instability, may also include: Based on the identified precursors of rock mass instability and their location on the risk carrier, early warning information is generated, including the risk level, the expected instability type, and the scope of impact. The expected instability type corresponds one-to-one with the risk carrier type. The early warning information is then visualized and integrated with the three-dimensional mining progress model of the three-dimensional panel before being output.
[0030] Furthermore, in another aspect of this application, in some embodiments, this application provides a mining monitoring device with a spatial arrangement of a three-dimensional panel in a deep, thick ore body, with reference to... Figure 2 The figure is a schematic diagram of the structure of a mining activity monitoring device arranged in a three-dimensional panel of a deep, thick ore body according to some embodiments of this application. The mining activity monitoring device 200 arranged in a three-dimensional panel of a deep, thick ore body includes: a data acquisition module 201, a processing module 202, and an execution module 203, which are described below: The acquisition module 201 in this application is mainly used to deploy a multi-field collaborative monitoring system for the three-dimensional mining panel of deep and thick ore bodies. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously acquires mining stress data and microseismic information throughout the entire mining process of the panel. Processing module 202, in this application, is mainly used to synchronize the mining stress data and microseismic information in time and match them with spatial references to generate a panel state data sequence synchronized with the mining time sequence. The processing module 202 is further configured to calculate and generate stress concentration factor and microseismic activity index from the state data sequence; The execution module 203 in this application is mainly used to determine the precursors of rock mass instability in the local area of the three-dimensional disk based on the temporal coupling evolution characteristics of the stress concentration coefficient and the microseismic activity index.
[0031] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described method for monitoring mining activity in the spatial arrangement of a three-dimensional panel of a deep, thick ore body.
[0032] In some embodiments, reference Figure 3 This figure is a schematic diagram of the structure of a computer device for monitoring mining activity in a three-dimensional panel layout of a deep, thick ore body, according to some embodiments of this application. The methods described in the above embodiments can be implemented through... Figure 3 The computer device shown is used to implement this, and the computer device 300 includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.
[0033] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more mining monitoring methods for controlling the spatial arrangement of the deep, thick orebody three-dimensional panel in this application.
[0034] The communication bus 302 may include a path for transmitting information between the aforementioned components.
[0035] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.
[0036] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the calculation of the stress concentration factor can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.
[0037] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.
[0038] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).
[0039] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.
[0040] In addition, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for monitoring the spatial arrangement of a three-dimensional panel in a deep, thick ore body.
[0041] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.
[0042] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of the invention. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.
Claims
1. A method for monitoring mining activity in a three-dimensional spatial arrangement of a deep, thick ore body, characterized in that, Includes the following steps: For the three-dimensional mining panel of deep and thick ore bodies, a multi-field collaborative monitoring system is deployed. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously collects mining stress data and microseismic information throughout the entire mining process of the panel. The mining-induced stress data and microseismic information are synchronized in time and matched with spatial references to generate a panel state data sequence synchronized with the mining timeline; From the state data sequence, stress concentration factor and microseismic activity index are calculated and generated; Based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index, the precursors of local rock mass instability in the three-dimensional disk area are identified.
2. The method according to claim 1, characterized in that, Calculating the stress concentration factor from the state data sequence specifically includes: The original rock stress reference value is obtained at each monitoring point in the three-dimensional panel area. The original rock stress reference value is determined in advance by the original rock stress test experiment independent of the mining monitoring system before the panel area is mined. Simultaneously extract the real-time maximum principal stress value of each monitoring point in the state data sequence; For each monitoring point, the ratio of the real-time maximum principal stress value to its corresponding original rock stress benchmark value is calculated to generate a sequence of point stress concentration coefficients that change with the mining time. By using spatial interpolation methods, the stress concentration coefficient sequence of all monitoring points within the three-dimensional panel area is collected to generate three-dimensional stress concentration coefficient field distribution data for the panel area.
3. The method according to claim 1, characterized in that, Synchronizing the mining-induced stress data and microseismic information in time and matching them with spatial references to generate a panel state data sequence synchronized with the mining timeline specifically includes: The mining-induced stress data is used to generate a single-point stress time series with timestamps based on the monitoring points; Microseismic information is used to generate event data records with timestamps and spatial coordinates. The single-point stress time series and microseismic event data are recorded, aligned based on a unified time axis, and jointly associated with a pre-divided three-dimensional spatial analysis grid of the disk area, forming a multi-source state sequence dataset of the disk area that simultaneously contains stress state and microseismic activity within each time-space grid.
4. The method according to claim 2, characterized in that, Based on the temporal coupling evolution characteristics of the stress concentration factor and microseismic activity index, the specific methods for identifying precursors of local rock mass instability in the three-dimensional disk area include: On the three-dimensional spatial model of the three-dimensional panel, several potential instability risk carriers are delineated as monitoring and analysis units. The risk carriers include at least the middle section pillar, the stope roof and the fault fracture zone. The three-dimensional stress concentration coefficient field distribution data of the disk area is mapped to each risk carrier, and the maximum stress concentration coefficient and its rate of change inside each risk carrier are extracted. Spatial clustering of microseismic information is performed, and microseismic events whose spatial locations fall within the preset influence range of the risk carrier are associated with the corresponding risk carrier. The microseismic activity index of each risk carrier within a preset time window is statistically analyzed. The microseismic activity index includes at least the frequency of microseismic events and the energy release rate. The preset time window is set based on the cyclic advance of panel mining and the intermediate mining step distance. For each risk carrier, the temporal correspondence between the rate of change of its maximum stress concentration factor and the microseismic activity index is analyzed. When the maximum stress concentration factor of a certain risk carrier continues to increase and the rate of change exceeds the first threshold, and the associated microseismic activity index changes from calm to active and exceeds the second threshold, it is determined that there are precursors to rock mass instability in this local risk carrier.
5. The method according to claim 1, characterized in that, The distributed mining stress monitoring system includes distributed optical fiber sensing units deployed along the main roadways or ore body strike of the three-dimensional panel, used to acquire mining strain / stress data continuously distributed along the sensing path.
6. The method according to claim 1, characterized in that, The independent microseismic monitoring array consists of multiple seismic sensors arranged in different layers and regions of the three-dimensional disk area. By analyzing the waveforms and time differences received by each seismic sensor, the spatial location and energy parameters of microseismic events can be retrieved.
7. The method according to claim 1, characterized in that, After identifying the precursors of local rock mass instability in the three-dimensional panel area, the following steps are also included: Based on the identified precursors of rock mass instability and their location on the risk carrier, early warning information is generated, including the risk level, the expected instability type, and the scope of impact. The expected instability type corresponds one-to-one with the risk carrier type. The early warning information is then visualized and integrated with the three-dimensional mining progress model of the three-dimensional panel before being output.
8. A mining monitoring device with a three-dimensional spatial arrangement in a deep, thick ore body panel, characterized in that, include: The acquisition module is used to deploy a multi-field collaborative monitoring system for the three-dimensional mining panel of deep and thick ore bodies. The multi-field collaborative monitoring system includes a distributed mining stress monitoring system and an independent microseismic monitoring array, which simultaneously acquires mining stress data and microseismic information throughout the entire mining process of the panel. The processing module is used to synchronize the mining stress data and microseismic information in time and match them with spatial references to generate a panel state data sequence synchronized with the mining time sequence. The processing module is also used to calculate and generate stress concentration factor and microseismic activity index from the state data sequence; The execution module is used to identify the precursors of rock mass instability in the three-dimensional disk area based on the temporal coupling evolution characteristics of the stress concentration factor and the microseismic activity index.
9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the mining monitoring method for the spatial arrangement of a three-dimensional panel of a deep, thick ore body as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the mining monitoring method for the spatial arrangement of a three-dimensional panel of a deep, thick ore body as described in any one of claims 1 to 7.