Coal mine curtain grouting early warning system and method

Abstract

This application discloses a coal mine curtain grouting early warning system and method, belonging to the field of coal mine spontaneous combustion prevention and curtain grouting technology. The system includes a fiber optic temperature measurement module, a temperature identification and risk assessment module, a curtain grouting response module, and a control platform module, which are connected in sequence via communication. The temperature identification and risk assessment module and the control platform module are also connected. The fiber optic temperature measurement module continuously collects and outputs temperature data from each monitoring point within the monitoring area; the temperature identification and risk assessment module determines and outputs the location information of abnormal areas; the curtain grouting response module includes at least one grouting terminal device for receiving grouting control commands and performing fixed-point grouting operations; the control platform module receives the location information of abnormal areas, generates grouting control commands and sends them to the corresponding grouting terminal devices, and determines the sealing effect after the grouting operation is completed. The embodiments of this application can improve the accuracy of identifying abnormal temperature risks in coal mines.

Description

Technical Field

[0001] This application relates to the field of coal mine spontaneous combustion prevention and curtain grouting technology, and in particular to a coal mine curtain grouting early warning system and method. Background Technology

[0002] With the increasing depth of coal mining and the growing complexity of ventilation systems, safety hazards such as high temperatures, spontaneous combustion, and gas leakage within mines are becoming increasingly prominent. This is particularly true in areas like fault zones, old goaf areas, and enclosed roadways, where heat accumulation and oxidation reactions are prone to occur, posing unpredictable risks of spontaneous combustion. Traditional methods of hazard identification, combining manual inspections with infrared point measurements, are not only inaccurate and have limited coverage, but are also prone to delays in judgment and response. Existing fiber optic temperature monitoring technologies are mostly single-point sensing or simple threshold alarm modes, resulting in low accuracy in judging temperature rise trends and making precise hazard identification difficult. Summary of the Invention

[0003] The purpose of this application is to provide a coal mine curtain grouting early warning system and method, which can effectively improve the accuracy of identifying abnormal temperature risks in coal mines, and at the same time achieve the timeliness of grouting response and the precision of grouting operation.

[0004] To achieve the above objectives, a first aspect of this application provides a coal mine curtain grouting early warning system, comprising: The fiber optic temperature measurement module includes a distributed fiber optic temperature sensing line deployed in the monitoring area of ​​the coal mine, and a temperature data acquisition host connected to the distributed fiber optic temperature sensing line. The fiber optic temperature measurement module is used to continuously collect and output the temperature data of each monitoring point in the monitoring area. The temperature identification and risk assessment module is communicatively connected to the temperature data acquisition host and control platform module. The temperature identification and risk assessment module is used to receive the temperature data, process the temperature data based on a preset anomaly judgment model, determine whether there is a temperature anomaly in the monitoring area, and output the location information of the anomaly area to the control platform module. The curtain grouting response module is communicatively connected to the temperature identification and risk assessment module. The curtain grouting response module includes at least one grouting terminal device preset in the monitoring area. The grouting terminal device is used to receive grouting control commands and perform fixed-point grouting operations. The control platform module is communicatively connected to the temperature identification and risk assessment module and the curtain grouting response module, respectively. The control platform module is used to receive the location information of the abnormal area, generate grouting control commands and send the grouting control commands to the grouting terminal device corresponding to the abnormal area, and continuously acquire the temperature data of the abnormal area after the grouting operation is completed to determine the sealing effect.

[0005] Compared with the prior art, the coal mine curtain grouting early warning system provided in this application has the following advantages: This coal mine curtain grouting early warning system, through the distributed fiber optic temperature sensing line of the fiber optic temperature measurement module and the temperature data acquisition host, can realize the continuous acquisition and output of temperature data at various monitoring points in the underground monitoring area of ​​the coal mine, providing comprehensive and continuous data source support for temperature anomaly judgment; relying on the preset anomaly judgment model of the temperature identification and risk assessment module to process the temperature data, it can effectively judge the temperature anomaly in the monitoring area and accurately output the location information of the anomaly area, realizing the effective identification and location of temperature anomalies; and leveraging the inter-module... Through communication connections, the control platform module can quickly generate grouting control commands based on the location information of abnormal areas and send them to the corresponding grouting terminal devices. The grouting terminal devices of the curtain grouting response module can promptly execute fixed-point grouting operations, improving the timeliness of grouting response and the accuracy of grouting operations. At the same time, after the grouting operation is completed, the control platform module can continuously acquire temperature data of abnormal areas to judge the sealing effect, forming a complete closed-loop operation from temperature monitoring, abnormal identification and location to fixed-point grouting and sealing effect verification. This ensures the effectiveness of curtain grouting sealing operations in coal mines and improves the overall curtain grouting early warning and emergency response capabilities of underground monitoring areas in coal mines.

[0006] In some embodiments, the distributed optical fiber temperature sensing lines are laid on the roof and side walls of the tunnel using a multi-path staggered layout, and are fixed by dustproof sleeves and anti-interference guide clips.

[0007] In some embodiments, the grouting terminal device includes a housing, a quick-connect grouting interface disposed on the housing, and a support device for temporarily or permanently deploying the grouting terminal device in a target area.

[0008] In some embodiments, the control platform module includes a sealing effect judgment unit, which is used to continuously receive temperature data of the abnormal area after the grouting operation is completed, compare the temperature change trend before and after grouting with a preset cooling trend model, and generate a secondary grouting control command if the sealing effect is not up to standard.

[0009] In some embodiments, the anomaly detection model includes at least one of the following: The temperature rise rate model is used to determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during a continuous sampling period. The hot zone expansion trend model is used to determine whether a region formed by multiple adjacent monitoring points has formed a hot zone due to temperature anomalies, and whether the area of ​​the hot zone is expanding and the area of ​​the hot zone expansion exceeds a second preset threshold. The multi-point temperature rise co-occurrence model is used to determine whether there are more than a preset number of monitoring points simultaneously exceeding a third preset threshold within a preset spatial range.

[0010] To achieve the above objectives, a second aspect of this application provides a coal mine curtain grouting early warning method. This method is applied to the coal mine curtain grouting early warning system described in the first aspect. The coal mine curtain grouting early warning system includes a fiber optic temperature measurement module, a temperature identification and risk assessment module, a curtain grouting response module, and a control platform module. The temperature identification and risk assessment module is communicatively connected to the fiber optic temperature measurement module, the curtain grouting response module, and the control platform module. The control platform module is communicatively connected to the curtain grouting response module. The curtain grouting response module includes at least one grouting terminal device preset in the monitoring area. The coal mine curtain grouting early warning method includes: A distributed optical fiber temperature sensing line and a temperature data acquisition host connected to the distributed optical fiber temperature sensing line are deployed in the monitoring area of ​​the coal mine to form an optical fiber temperature measurement module. The optical fiber temperature measurement module continuously collects temperature data of each monitoring point in the monitoring area of ​​the coal mine. The temperature data is received by the temperature identification and risk assessment module, and the temperature data is processed based on the preset anomaly judgment model to determine whether there is a temperature anomaly in the monitoring area and to determine the location of the anomaly area. When an abnormal temperature occurs, the control platform module sends a grouting control command to the grouting terminal device corresponding to the abnormal area. The grouting terminal device is used to perform a fixed-point grouting operation. After the grouting operation is completed, temperature data of the abnormal area is continuously collected, and the sealing effect is judged through the control platform module.

[0011] In some embodiments, the step of determining whether there is a temperature anomaly within the monitoring area specifically includes at least one of the following determination methods: Determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during the continuous sampling period; Determine whether the area of ​​the hot zone formed by multiple adjacent abnormal monitoring points is expanding and whether the area of ​​the hot zone expansion exceeds the second preset threshold. Determine whether, within a preset space range, there are more than a preset number of monitoring points simultaneously exhibiting a temperature exceeding a third preset threshold.

[0012] In some embodiments, before deploying distributed fiber optic temperature sensing lines in the underground monitoring area of ​​the coal mine, the coal mine curtain grouting early warning method further includes: Based on at least one of the following: mine geological structure, historical heat records and gas distribution information, a risk level assessment is conducted on the monitoring area to obtain the risk level assessment results. Based on the risk level assessment results, the deployment path and monitoring node spacing of the distributed optical fiber temperature sensing line are determined.

[0013] In some embodiments, when multiple abnormal areas exist simultaneously, the coal mine curtain grouting early warning method further includes: The grouting priority of each abnormal region is calculated based on the temperature rise rate, hot zone expansion speed, and spatial importance of each abnormal region. The control platform module sends grouting control commands to the corresponding grouting terminal devices in sequence according to the grouting priority.

[0014] In some embodiments, the coal mine curtain grouting early warning method further includes: Based on the temperature data of each monitoring point in the underground monitoring area of ​​the coal mine, the temperature fluctuation trend of each monitoring point is analyzed. Based on the temperature fluctuation trend, a comprehensive risk assessment is conducted in conjunction with the geological structure, ventilation conditions, and historical event records of the monitored area to identify potential risk areas. A preventative grouting command is sent to the grouting terminal device corresponding to the potential risk area to perform a local curtain grouting operation. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of a coal mine curtain grouting early warning system according to an embodiment of this application; Figure 2 This is a temperature-time variation curve of a monitoring point in a coal mine provided in an embodiment of this application; Figure 3 This is a flowchart of a coal mine curtain grouting early warning method provided in an embodiment of this application; Figure reference numerals: Fiber optic temperature measurement module 100, temperature identification and risk assessment module 200, curtain grouting response module 300, control platform module 400. Detailed Implementation

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0017] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0018] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0020] First, let's analyze some of the terms used in this application: Curtain grouting technology is a grouting technique that improves the physical and mechanical properties of rock and soil by injecting grout into the rock and soil to form a continuous waterproof curtain. This technology is mainly used in scenarios such as mine water hazard prevention and tunnel fissure sealing.

[0021] With the increasing depth of coal mining and the growing complexity of ventilation systems, safety hazards such as high temperatures, spontaneous combustion, and gas leakage within mines are becoming increasingly prominent. This is particularly true in areas like fault zones, old goaf areas, and enclosed roadways, where heat accumulation and oxidation reactions are prone to occur, posing unpredictable risks of spontaneous combustion. Traditional methods of hazard identification, combining manual inspections with infrared point measurements, are not only inaccurate and have limited coverage, but are also prone to delays in judgment and response. Existing fiber optic temperature monitoring technologies are mostly single-point sensing or simple threshold alarm modes, resulting in low accuracy in judging temperature rise trends and making precise hazard identification difficult.

[0022] Based on this, the embodiments of this application provide a coal mine curtain grouting early warning system and method, which can effectively improve the accuracy of identifying abnormal temperature risks in coal mines, and at the same time realize the timeliness of grouting response and the precision of grouting operation.

[0023] See Figure 1 This is a schematic diagram of a coal mine curtain grouting early warning system provided in an embodiment of this application. The coal mine curtain grouting early warning system includes: The fiber optic temperature measurement module 100 includes a distributed fiber optic temperature sensing line deployed in the monitoring area of ​​the coal mine, and a temperature data acquisition host connected to the distributed fiber optic temperature sensing line. The fiber optic temperature measurement module 100 is used to continuously collect and output temperature data of each monitoring point in the monitoring area. The temperature identification and risk assessment module 200 is communicatively connected to the temperature data acquisition host and control platform module 400. The temperature identification and risk assessment module 200 is used to receive temperature data, process the temperature data based on a preset anomaly judgment model, determine whether there is a temperature anomaly in the monitoring area, and output the location information of the anomaly area to the control platform module 400. The curtain grouting response module 300 is communicatively connected to the temperature identification and risk assessment module 200. The curtain grouting response module 300 includes at least one grouting terminal device preset in the monitoring area. The grouting terminal device is used to receive grouting control commands and perform fixed-point grouting operations. The control platform module 400 is communicatively connected to the temperature identification and risk assessment module 200 and the curtain grouting response module 300, respectively. The control platform module 400 is used to receive the location information of the abnormal area, generate grouting control commands and send grouting control commands to the grouting terminal device corresponding to the abnormal area, and continuously acquire the temperature data of the abnormal area after the grouting operation is completed to judge the sealing effect.

[0024] This coal mine curtain grouting early warning system, through the distributed fiber optic temperature sensing lines of the fiber optic temperature measurement module and the temperature data acquisition host, can continuously collect and output temperature data from various monitoring points in the underground coal mine monitoring area, providing comprehensive and continuous data source support for temperature anomaly judgment. Relying on the preset anomaly judgment model of the temperature identification and risk assessment module, the system processes the temperature data, effectively identifying temperature anomalies within the monitoring area and accurately outputting the location information of the anomaly area, achieving effective identification and location of temperature anomalies. Through the communication connections between modules, the control platform module can quickly generate grouting control commands based on the location information of the anomaly area and send them to the corresponding grouting terminal device. The grouting terminal device of the curtain grouting response module can promptly execute fixed-point grouting operations, improving the timeliness of grouting response and the accuracy of grouting operations. Simultaneously, after the grouting operation is completed, the control platform module continuously acquires temperature data from the anomaly area to judge the sealing effect, forming a complete closed-loop operation from temperature monitoring, anomaly identification and location to fixed-point grouting and sealing effect verification. This ensures the effectiveness of coal mine curtain grouting sealing operations and comprehensively improves the early warning and emergency response capabilities of curtain grouting in the underground coal mine monitoring area.

[0025] In some embodiments, the distributed optical fiber temperature sensing lines are laid on the roof and side walls of the tunnel using a multi-path staggered layout and are fixed by dustproof sleeves and anti-interference guide clips.

[0026] For example, distributed fiber optic temperature sensing lines are typically deployed in monitoring areas such as goaf areas, old roadways, corner coal seams, and fracture zones in underground coal mines. These lines are connected to a temperature data acquisition host. The distributed fiber optic temperature sensing lines are made of passive distributed temperature sensing optical cables, preferably multimode fiber or fiber cores with metal cladding. To ensure stable and reliable data acquisition in the complex electromagnetic environment of coal mine roadways, the distributed fiber optic temperature sensing lines preferably feature an anti-interference fiber structure, with an anti-interference shielding layer added to the outer layer of the standard communication fiber or distributed fiber optic sensing unit. This shielding layer can be constructed using braided copper wire mesh, stainless steel fiber shielding tape, or a metal-coated flame-retardant PVC cladding layer, providing excellent electromagnetic interference suppression and high-temperature resistance, significantly improving the working stability of the fiber optic sensor near interference sources such as cables, mine lamps, and signal lines. The shielding layer does not affect the fiber's temperature sensing sensitivity. Its material thickness is preferably controlled between 0.2mm and 0.6mm, and it is coaxially bonded to the outer sheath via epoxy coating, providing moisture-proof, anti-static, and damage-resistant properties. Simultaneously, this fiber structure is compatible with harsh environments such as high humidity and high dust levels underground. It can be configured in sections according to the risk level of the deployment area, achieving full shielding coverage in critical areas and lightweight deployment in general areas, balancing performance and cost. Furthermore, to avoid safety hazards caused by the shielding material's own conductivity, an insulating transition layer can be added to prevent direct contact between the shielding layer and the underground power system, thus meeting the intrinsically safe cabling requirements of coal mines.

[0027] This distributed fiber optic temperature sensing line is staggered at fixed intervals along the tunnel roof, side walls, and key inflection points to form a comprehensive temperature sensing network. It is fixed to the support structure by dustproof sleeves and dedicated anti-interference clips with limiting guide grooves that connect to the metal-coated inner wall. This effectively reduces the impact of electromagnetic interference from cables, mechanical heat sources, or high-pressure pipelines on the optical signal. To ensure that the fiber optic temperature monitoring line can conform to the rock wall structure for high-precision temperature measurement in complex tunnel environments, while also possessing good fixation stability and anti-disturbance capabilities, the anti-interference guide clips preferably adopt a "U-shaped," "Ω-shaped," or "slide rail snap-fit" groove structure. They are integrally injection molded from wear-resistant and flame-retardant polymer materials (such as polyimide, reinforced nylon, or TPU), providing elastic fixation and anti-displacement capabilities, and are compatible with snap-fit ​​installations of various sizes of optical cables. The clip structure is fixed to the tunnel rock wall or support grid by pre-embedded anchors or expansion bolts. Limit protrusions are provided inside the clip groove to prevent longitudinal slippage of the optical fiber under vibration or wind pressure disturbance. Meanwhile, the clips are equipped with shielding plates on the outside, which can effectively reduce the corrosive effects of environmental factors such as dust and moisture on the exposed parts of the optical fiber, improving line life and signal stability. In specific high-interference sections (such as near cable tunnels or electromechanical equipment), the guide clips can also be embedded with micro anti-interference layers, such as high dielectric constant rubber pads or low-resistance carbon fiber films, to further block local induced interference. This works in conjunction with the shielding structure of the optical fiber body to achieve a distributed sensing and local anti-interference cabling solution.

[0028] The temperature data acquisition host is a DTS host, which is connected to the distributed fiber optic temperature sensing line. It reads the Rayleigh scattering or Raman scattering signals reflected in the distributed fiber optic temperature sensing line and converts them into temperature values ​​corresponding to spatial locations. The fiber optic temperature measurement module 100 supports periodic sampling every 1 to 3 minutes. The spatial resolution is preferably controlled between 1 and 2 meters, and the temperature accuracy is controlled within ±0.2℃. The acquired temperature data is stored synchronously with the location coordinates according to the time sequence, which can be called by the subsequent anomaly judgment model. At the same time, the temperature data of each monitoring point in the monitoring area is continuously output.

[0029] The temperature identification and risk assessment module 200 is communicatively connected to the temperature data acquisition host and control platform module 400. The temperature identification and risk assessment module 200 is used to receive multi-point continuous temperature data transmitted by the fiber optic temperature measurement module 100, and to perform time-series analysis and spatial comparison processing on the temperature data based on a variety of preset anomaly judgment models in order to determine whether there is a temperature anomaly in the monitoring area, and output the location information of the abnormal area and the judgment results of whether it is abnormal and the type of anomaly to the control platform module 400.

[0030] In some embodiments, the anomaly detection model includes at least one of the following: The temperature rise rate model is used to determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during a continuous sampling period. The hot zone expansion trend model is used to determine whether a region formed by multiple adjacent monitoring points has formed a hot zone due to temperature anomalies, and whether the area of ​​the hot zone is expanding and the area of ​​the hot zone expansion exceeds a second preset threshold. The multi-point temperature rise co-occurrence model is used to determine whether there are more than a preset number of monitoring points simultaneously exceeding a third preset threshold within a preset spatial range.

[0031] In other words, the anomaly detection models built into the temperature identification and risk assessment module 200 include a temperature rise rate model, a hot zone expansion trend model, and a multi-point temperature rise co-occurrence model. The temperature rise rate model is defined by the formula... The determination is made using the formula parameters shown in Table 1 below. If the temperature rise rate of the monitoring point within a continuous cycle is greater than the first preset threshold (e.g., 2℃ / h), it is marked as a "rapid temperature rise point".

[0032] Table 1. Parameters of the Temperature Rise Rate Model Formula

[0033] In practical applications, the system uses a temperature rise rate model to perform real-time analysis of fiber optic temperature monitoring data, mainly employing the following mathematical expression: ,in, It represents the rate of temperature change per unit time at time point t (in °C / h). Indicates the temperature at the current time. The set time window width is typically 30 minutes to 2 hours, and can be flexibly adjusted according to the on-site sampling frequency. Specific grading standards are shown in Table 2 below: Table 2 Classification criteria for temperature rise rate range

[0034] The aforementioned grading standards are constructed based on coal seam oxidation and heating experiments and historical data backtesting, and are applicable to various coal types and ventilation conditions. If the calculation results of a certain monitoring point are continuously within the moderate or high anomaly range for multiple times, the system will automatically determine it as a "continuously abnormal" state, triggering a higher-level response assessment. To prevent misjudgment, the system can also incorporate a moving average correction algorithm to smooth short-term temperature rise fluctuations, avoiding false responses caused by sensing errors or local disturbances.

[0035] The hot zone expansion trend model uses the formula The formula parameters for the judgment are shown in Table 3 below.

[0036] Table 3 Formula Parameters for the Hot Zone Expansion Trend Model

[0037] It should be noted that the area of ​​the hot zone can be estimated from the distribution range of adjacent monitoring points forming the hot zone, and is calculated by multiplying the distance between monitoring points by the coverage width.

[0038] The multi-point temperature rise co-occurrence model is based on the formula. and The formula parameters for the judgment are shown in Table 4 below.

[0039] Table 4. Formula parameters for the multi-point temperature rise co-occurrence model

[0040] It should be noted that spatial clustering is the essential difference between this multi-point temperature rise co-occurrence model and single-point anomaly detection. This multi-point temperature rise co-occurrence model is determined by the formula... These abnormal monitoring points whose temperature exceeds the third preset threshold are within a preset spatial range.

[0041] During temperature monitoring in high-risk areas underground, short-term temperature rises at isolated points may not have any real hazard value. Therefore, the system uses a spatial co-occurrence mechanism to synchronously cluster adjacent monitoring points to identify thermal anomaly areas with a physical spread trend. This spatial co-occurrence model is based on the physical location relationship of optical fibers deployed along the roadway, using a three-point grouping or sliding window segmenting method to calculate the temperature rise consistency between adjacent sampling points. When three or more sampling points in the same spatial segment have a temperature rise rate R(t) higher than the moderate anomaly threshold in Table 2 (e.g., ≥4.0℃ / h) simultaneously, and the duration exceeds a set time threshold (e.g., 20 min), the area is identified as a "co-occurring hot zone". To enhance the anti-interference and adaptability of the judgment, the system can also combine a spatial adjacency model (e.g., point-edge graph construction based on graph structure) to calculate the thermal zone connectivity and local density indicators (e.g., local clustering coefficient, connectivity ratio, resonance area) between temperature rise points, thereby filtering out occasional isolated point interference and retaining only high-risk segments with contiguous characteristics. This mechanism is suitable for constructing grouting block identification logic: the system can quickly locate abnormal cluster areas based on spatial co-occurrence results and delineate response sealing boundaries as input data for subsequent grouting scheduling.

[0042] The first preset threshold involved in all the above anomaly detection models Second preset threshold Third preset threshold Upper limit of average distance between anomaly monitoring points All parameters can be set according to the specific conditions of the mining area, and this application does not impose any specific limitations on them. After the temperature identification and risk assessment module 200 calculates and judges by any one or more of the above-mentioned anomaly judgment models, it determines the temperature anomaly situation in the monitoring area and generates anomaly area location information containing anomaly type (such as temperature rise rate anomaly corresponding to the temperature rise rate model, thermal zone expansion trend anomaly corresponding to the thermal zone expansion trend model, and multi-point temperature rise co-occurrence anomaly corresponding to the multi-point temperature rise co-occurrence model) and spatial coordinates, which is synchronously transmitted to the control platform module 400.

[0043] The temperature rise rate anomaly corresponding to the temperature rise rate model can be as follows: Figure 2 As shown. Figure 2 The temperature-time variation curve at a monitoring point in a coal mine shows that when the slope of the curve (i.e., the rate of temperature change per unit time) exceeds the temperature rise rate threshold... When the temperature reaches the first preset threshold, it indicates that the temperature rise rate corresponding to the temperature rise rate model at the monitoring point is abnormal.

[0044] To enhance the system's adaptability under different climate cycles and changes in mine ventilation conditions, this system incorporates a historical data comparison mechanism in the temperature anomaly detection process, constructing a "time-series feature baseline database." Furthermore, it uses a sliding window algorithm to continuously adjust the detection threshold in real time, improving the generalization ability and accuracy of the early warning model. During implementation, the system continuously records the daily temperature variation curves of each monitoring point, using "monitoring point-time period" as the basic unit, and automatically calculates its long-term trend mean. The system uses the variance rate σ and typical periodic indicators (such as daily maximum difference and three-day fluctuation range) to construct a historical characteristic baseline for that point. When real-time monitoring data T(t) arrives, the system automatically matches the corresponding historical data for the current time period for comparison and calculates the deviation index.

[0045] If the deviation D(t) continuously exceeds a set threshold (e.g., |D(t)|≥2), the system will consider it an "abnormal offset" and, in conjunction with factors such as rate and persistence, will determine the response level. Furthermore, the system supports updating the historical baseline database using a "7-day rolling window" to avoid judgment failures caused by long-term static baselines. For example, the earliest day's data is automatically removed at the end of each week, and the mean and volatility are updated to maintain the dynamic validity of the baseline. Further, the system can integrate a self-learning module based on lightweight neural networks (such as GRU) or cluster analysis (such as K-Means) to extract change patterns from long-term history, predict and provide early warnings of abnormal trends, achieving an intelligent judgment logic that is "based on history but not limited to history."

[0046] Specifically, to further improve the response accuracy of the early warning system and avoid response deviations caused by a single anomaly judgment model, the temperature identification and risk assessment module 200, based on the aforementioned temperature acquisition data and the judgment results of the three anomaly judgment models, additionally constructs a graded response index system. This system is used to distinguish the priority of handling different thermal risk levels, enabling precise resource allocation. This graded response index system closely integrates three major characteristics: temperature rise rate, spatial expansion trend, and multi-point co-occurrence. Relying on the calculation data from the aforementioned anomaly judgment models, it comprehensively judges through the following three dimensions, forming a complete closed-loop processing flow of "anomaly identification - grade classification - priority ranking": Temperature rise rate judgment: This dimension relies on the calculation results of the temperature rise rate model to further refine the risk classification. The temperature identification and risk assessment module 200 continuously records the temperature rise slope (i.e., ΔT / Δt) of each monitoring point in multiple consecutive sampling periods and compares and calibrates it with the historical average temperature rise slope of the monitoring point to avoid misjudgment caused by environmental fluctuations. When the temperature rise slope ΔT / Δt of the monitoring point exceeds the set threshold Ts (e.g., 3℃ / h, which can be adjusted according to the actual situation of the mining area and adapted to the first preset threshold θ1), it is regarded as a level 1 temperature rise risk, which only triggers basic early warning and routine monitoring enhancement. When ΔT / Δt exceeds a higher threshold (e.g., 6℃ / h), it is classified as a level 2 or higher temperature rise risk and is directly marked as a high-priority response target, and the analysis frequency of spatial expansion trend and multi-point co-occurrence characteristics is strengthened simultaneously.

[0047] Spatial Clustering Feature Identification: This dimension is based on the thermal area calculation results of the thermal zone expansion trend model. It focuses on analyzing the spatial distance and distribution density between multiple thermal anomaly points to further quantify the risk level of thermal zone expansion. When the system detects more than n (n≥3, which is compatible with the minimum number of co-occurring points m in the multi-point temperature rise co-occurrence model) adjacent monitoring points that form a continuous temperature rise band in 3D space (such as a continuous thermal zone with a point spacing of less than 10m), and the temperature of these monitoring points rises synchronously in a short period of time (such as 1-2 sampling cycles), it is determined that a clear thermal zone expansion trend has been formed. At this time, the temperature identification and risk assessment module 200 will perform weighted processing on the thermal zone to increase its disposal priority and ensure that it can be given key attention and rapid response in the early stage of thermal zone expansion.

[0048] Multi-point co-occurrence aggregation model: This dimension integrates the calculated data from the previous two dimensions. By constructing a co-occurrence matrix of temperature rise events, it quantifies the degree of coordinated warming at multiple abnormal monitoring points. Simultaneously, combining the relative positions of each abnormal monitoring point with the temporal synchronicity of temperature rise, a comprehensive risk scoring formula is used for quantitative classification, accurately distinguishing the risk differences between different abnormal areas. The formula is as follows:

[0049] in: The response level score is given for the i-th monitoring point (or abnormal area); This represents the actual temperature rise rate at the monitoring point over a continuous time period (derived from the calculation results of the temperature rise rate model). The spatial expansion intensity index of the hot zone where the monitoring point is located (the area of ​​hot zone expansion based on the hot zone expansion trend model). The result is the thermal clustering score. The temperature rise co-occurrence coefficient between this monitoring point and surrounding abnormal monitoring points (taken from the co-occurrence matrix analysis results of the multi-point temperature rise co-occurrence model, i.e., the thermal zone synchronicity score); , , These are the weighting coefficients for each indicator, which can be flexibly adjusted according to the actual geological conditions, ventilation, and safety management requirements of the mining area. It is recommended that the initial values ​​be set to 0.4, 0.3, and 0.3 respectively, with the temperature rise rate having the highest weight, prioritizing the treatment of areas with rapid temperature rise.

[0050] The temperature recognition and risk assessment module 200 uses the above comprehensive risk score as a basis. The values ​​are used to classify all abnormal monitoring points and abnormal areas into three response levels, each corresponding to a different handling strategy: low response level (Ri<30), medium response level (30≤Ri≤60), and high response level (Ri>60). The corresponding grouting response strategies are also differentiated according to this level. For low response levels, only the frequency of temperature monitoring is increased, and grouting operations are not initiated temporarily. For medium response levels, conventional grouting responses are initiated. For high response levels, the corresponding grouting terminal devices are prioritized to perform rapid, targeted sealing grouting operations, ensuring that limited grouting resources are used primarily for areas with the most significant potential risks, further improving the response accuracy and resource utilization efficiency of the entire early warning system. Simultaneously, all scoring data and level classification results of this graded response index system, along with abnormal area location information and abnormality type determination results, are transmitted to the control platform module 400, providing accurate data support for the grouting priority scheduling of the control platform module 400, achieving the safety management goal of "accurate identification, graded response, and scientific scheduling."

[0051] The curtain grouting response module 300 is communicatively connected to the temperature identification and risk assessment module 200. The curtain grouting response module 300 is a key component for performing fixed-point sealing actions. Its structure includes at least one grouting terminal device pre-installed in the monitoring area, and is also equipped with an external grouting pipeline interface and a connection control interface. The grouting terminal device is used to receive grouting control commands issued by the control platform module 400 and perform fixed-point grouting operations.

[0052] In some embodiments, the grouting terminal device includes a housing, a quick-connect grouting interface disposed on the housing, and a support device for temporarily or permanently deploying the grouting terminal device in a target area.

[0053] The outer shell is made of metal or engineering plastic and has the characteristics of pressure resistance and explosion resistance. At the same time, as the shell unit of the grouting terminal, the outer shell also has the ability to resist pressure and corrosion. The interior is divided into grouting cavity, interface chamber and communication chamber. The overall size is set according to the tunnel width and grouting pressure, and the diameter is usually 80-150mm. The outer casing also houses a grouting bag structure, which can be unfolded to form a comprehensive seal for targeted sealing. The grouting bag structure is unfoldable and made of fiberglass-reinforced rubber or high-polymer expandable material. After grouting begins, it is released from the grouting chamber. Through injection pressure and bag expansion, it achieves comprehensive sealing of roadway cracks or coal seam fissures. Depending on the sealing area, a flat bag structure can be selected for planar areas, or a directional nozzle bag can be selected for irregular cracks. A quick-connect grouting interface facilitates connection to the ground grouting pump pipeline. This interface uses standard threads and a quick-lock structure to securely connect to the ground high-pressure grouting pump. The interface also features a self-sealing chip to effectively prevent backflow of impurities when not connected to a pipeline. An internal check valve mechanism ensures unidirectional grout flow, preventing backflow or backflow during grouting. An electrical or pneumatic control is also provided between the grouting terminal device and the control platform module 400. The communication interface can receive grouting control commands issued by the control platform module 400, and also supports remote grouting activation and mid-grouting cutoff command reception. The communication interface can be selected from RS485, CAN bus, LoRa low-power wireless module, etc. With the help of the support device, the grouting terminal device can be temporarily deployed or permanently deployed in high-risk areas of the monitoring area. The fixing method of the support device can be flexibly selected according to the deployment scenario. On rock walls or support structures, the grouting terminal can be quickly positioned and fixed by inserting a pre-set support frame with sliding rails. On steel supports or pipes, magnetic or expansion plug fixing methods can be used for convenient deployment. Each grouting terminal device is equipped with an independent number or NFC / RFID tag, which can be remotely addressed, making it easy for the control platform module 400 to quickly identify and establish a control link when performing grouting, without relying on manual operation. It can be used in grouting operation scenarios such as unmanned area grouting and continuous grouting linkage. Its remote control logic is as follows: the control platform module 400 first identifies the target location coordinates of the abnormal area, then matches the corresponding numbered grouting terminal device, sends an activation signal to it to open the valve or start the electromagnetic drive, and then performs the grouting operation according to the grouting time and grouting pressure preset by the platform. After the grouting is completed, the valve is automatically closed and the grouting data is recorded synchronously. This structural design also enables the system to realize remote multi-point collaborative operation, adapting to the grouting operation needs of unattended working faces or work areas.

[0054] The control platform module 400 is communicatively connected to the temperature identification and risk assessment module 200 and the curtain grouting response module 300, respectively. As the information integration and action command output center of the entire system, the control platform module 400 is used to receive the location information of the abnormal area transmitted by the temperature identification and risk assessment module 200, generate grouting control commands based on the location information, and accurately send the grouting control commands to the grouting terminal device corresponding to the abnormal area. At the same time, after the grouting operation is completed, the temperature data of the abnormal area is continuously acquired to determine the sealing effect.

[0055] The control platform module 400 not only possesses local deployment capabilities underground but also supports remote deployment and remote control operations to meet the scheduling needs of different coal mine deployment scenarios. In practical implementation, the control platform can establish a high-speed data channel with the underground platform through a dedicated server system in the ground dispatch center. Using an industrial VPN leased line or fiber optic communication link, it uploads collected temperature data in real time and supports sending control commands from the ground to the underground grouting terminal. The remote deployment module is integrated into the control platform's dispatch unit, featuring encrypted data communication, secure breakpoint resume, and remote firmware upgrade functions, ensuring critical control tasks can be maintained even under complex conditions such as network interruptions and fluctuations. Remote control command priorities can be set, and a permission management mechanism authorizes only specific users to issue grouting commands, ensuring the security and controllability of remote operations. This remote function is applicable not only to normal grouting scheduling but also to remote manual intervention in pre-grouting and emergency grouting modes. Especially in highly enclosed and hazardous areas, ground platform personnel can intervene in advance based on real-time analysis results, achieving a high degree of separation between grouting response decision-making and execution.

[0056] In some embodiments, the control platform module includes a sealing effect judgment unit. The sealing effect judgment unit is used to continuously receive temperature data of abnormal areas after the grouting operation is completed, compare the temperature change trend before and after grouting with a preset cooling trend model, and generate a secondary grouting control command if the sealing effect is not up to standard.

[0057] Specifically, the control platform module 400 internally includes a data receiving and processing unit, a graph visualization module, a linkage control unit, and a sealing effect judgment unit. The sealing effect judgment unit continuously receives temperature data from the abnormal area after the grouting operation is completed, compares the temperature change trend before and after grouting with a preset cooling trend model, and if the sealing effect is deemed unsatisfactory, generates a secondary grouting control command and sends it to the corresponding grouting terminal device. Its judgment logic is as follows: it continuously collects the temperature change curve of the target area and compares it with the temperature decrease trend model set before grouting. A judgment standard could be, for example, a temperature decrease rate of 0.5℃ / 10 minutes within 30 minutes after grouting, or a continuous reduction in the hot zone area within three cycles. If the judgment is "sealing unsatisfactory," the control platform module 400 will generate a secondary grouting scheduling command and select a backup grouting terminal device or reactivate the original grouting terminal device.

[0058] Specifically, after the grouting terminal device completes the sealing grouting operation, the control platform module 400 will designate the target abnormal area as a "key tracking area" and continue to collect temperature data of this area through distributed fiber optic temperature sensing lines. This ensures that the data collection method is consistent with the previous monitoring to guarantee data comparability. The monitoring cycle is set every 5–10 minutes, and the tracking duration is preferably 30–60 minutes, which can be flexibly adjusted according to the sealing volume and regional thermal inertia. The sealing effect judgment unit will first calculate the actual cooling rate. Through formula (in The temperature at the instant the grouting is completed. The temperature at a certain time point after grouting (νcool is the average cooling rate) is used to determine the cooling situation. Then, a comprehensive judgment is made in combination with the preset three-stage cooling trend model. That is, in the T1 time period (0-10min), it is determined whether the temperature has stopped rising; in the T2 time period (10-30min), it is determined whether the temperature has entered the continuous slow cooling zone; and in the T3 time period (after 30min), it is determined whether the temperature has stabilized and cooled down and tended to the safe temperature zone.

[0059] If the temperature continues to rise after grouting, or the cooling rate is significantly lower than the preset value (e.g., <0.3℃ / 10min), it is considered that the sealing effect is poor and the expected temperature control and insulation effects have not been achieved. At this time, the sealing effect judgment unit will generate a secondary grouting control command, and the control platform module 400 will raise the alarm level to remind relevant personnel to pay attention and start the secondary grouting process simultaneously. After the sealing failure is determined, the control platform module 400 can automatically start the secondary grouting process, or it can be started after manual review. The specific scheduling logic is as follows: if the original grouting terminal device is still available, the terminal will be directly activated to perform the secondary grouting operation; if the original grouting terminal device malfunctions or the grouting pressure is insufficient, the system will start the nearby backup terminal device (the control platform module 400 has established a "grouting backup chain" in advance to achieve rapid matching of backup terminals); at the same time, the parameters of the secondary grouting can be automatically adjusted by the control platform module 400, such as extending the grouting time and increasing the grouting pressure, to improve the sealing effect of the supplementary grouting.

[0060] In addition, the control platform module 400 can also include an auxiliary judgment mechanism, which can combine the grouting pressure sensor feedback curve to help determine whether the grout has not completely covered the target area due to obstructed grouting path. It can also combine the thermal shrinkage ratio diagram (comparison of hot zone area before and after sealing) to further verify the sealing effect. At the same time, it supports the insertion of a manual review mechanism, which allows relevant personnel to confirm the review report before starting the secondary grouting. This is suitable for the strict handling needs of high-risk key areas. During the entire secondary grouting process, the control platform module 400 will completely record all data from "initial grouting result - secondary grouting start point - final cooling trend", including grouting parameters, injection... Data such as grouting duration, temperature change curves, and sealing effect assessment results will be used to update the risk level of the target area, as well as optimize and adjust the system's grouting priority scheduling strategy, temperature anomaly judgment model, and cooling trend model, thereby achieving system self-learning and improved scenario adaptability. This secondary grouting process can effectively avoid the problem of "false grouting" (grouting completed but without substantial sealing effect), and achieve "tiered response." Instead of performing a single grouting indiscriminately, the grouting intensity is flexibly adjusted according to the sealing effect, which not only ensures the sealing effect but also avoids resource waste, further enhancing the reliability and practicality of the entire early warning system.

[0061] The data receiving and processing unit communicates with the temperature identification and risk assessment module 200, and is specifically used to receive temperature anomaly data and related monitoring data transmitted by the temperature identification and risk assessment module 200. Specifically, this unit can communicate with the DTS host or edge processor, and supports continuous high-frequency data access (such as reporting once per minute), breakpoint resume, and historical data backtracking. The communication protocol can be selected according to the deployment method, such as TCP / IP, RS485, MODBUS, or LoRa network.

[0062] The map visualization module displays real-time temperature, hot zone expansion trends, historical fluctuation curves, and other information for each monitoring point downhole in the form of two-dimensional or three-dimensional maps. Furthermore, the module can intuitively present the temperature distribution of the monitoring area in the form of heat maps, profile maps, or three-dimensional tunnel maps. It supports display of hot zone expansion trends, highlighting of key points, alarm markers, and overlay of historical curves. It can also set multi-level and multi-state displays such as "potential anomalies," "early warning points," and "grouting pending confirmation."

[0063] The linkage control unit is used to match the corresponding grouting terminal device based on the target coordinates of the abnormal area and send grouting start and stop commands to it. Specifically, this unit integrates the judgment logic of multiple temperature anomaly identification models, such as the temperature rise rate model, the hot zone expansion trend model, and the multi-point temperature rise co-occurrence model. After identifying the target area, it automatically matches the corresponding grouting terminal number and can also call the grouting scheduling logic based on priority sorting, such as prioritizing the sealing of areas with fast temperature rise rate, high spatial concentration, or close to the work surface. Its control logic is as follows: first, it determines whether there is a terminal to be grouted in the target area, then generates a grouting plan table containing control parameters such as grouting pressure, time, and flow rate, and then sends control commands to the target terminal to start grouting. During grouting, feedback data such as grouting status and pressure fluctuations are transmitted back in real time (if the terminal has a detection module). After grouting is completed, a grouting log (terminal number, location, time, sealing volume, etc.) is recorded for subsequent traceability. Furthermore, the control platform module 400 can be flexibly deployed in the ground command center or underground node station. It supports an automatic control and manual verification operation mode, and also has the function of operation record backtracking. All units work together to achieve full control of the entire grouting early warning process.

[0064] Please see Figure 3 This application also discloses a method for early warning of curtain grouting in coal mines. This method is applied to a curtain grouting early warning system, which includes a fiber optic temperature measurement module 100, a temperature identification and risk assessment module 200, a curtain grouting response module 300, and a control platform module 400. The temperature identification and risk assessment module 200 is communicatively connected to the fiber optic temperature measurement module 100, the curtain grouting response module 300, and the control platform module 400. The control platform module 400 is communicatively connected to the curtain grouting response module 300. The curtain grouting response module 300 includes at least one grouting terminal device preset in the monitoring area. The method for early warning of curtain grouting in coal mines may include, but is not limited to, steps S1 to S5. Step S1: Deploy distributed optical fiber temperature sensing lines and temperature data acquisition host connected to the distributed optical fiber temperature sensing lines in the underground monitoring area of ​​the coal mine to form an optical fiber temperature measurement module and continuously collect temperature data of each monitoring point in the underground monitoring area of ​​the coal mine through the optical fiber temperature measurement module. Step S2: Receive temperature data through the temperature identification and risk assessment module, process the temperature data based on the preset anomaly judgment model, determine whether there is a temperature anomaly in the monitoring area, and determine the location of the anomaly area. Step S3: When there is a temperature anomaly, a grouting control command is sent to the grouting terminal device corresponding to the abnormal area through the control platform module. Step S4: Perform fixed-point grouting operation through the grouting terminal device; Step S5: After the grouting operation is completed, temperature data of the abnormal area is continuously collected, and the sealing effect is judged through the control platform module.

[0065] The specific implementation method of the coal mine curtain grouting early warning method is basically the same as the specific implementation of the coal mine curtain grouting early warning system, and will not be repeated here.

[0066] This coal mine curtain grouting early warning method uses a distributed fiber optic temperature measurement module to achieve continuous and accurate acquisition of underground coal mine temperature. Relying on an anomaly judgment model, it accurately identifies and locates areas with abnormal temperatures. Through the linkage between the control platform and the grouting terminal, it achieves rapid and accurate grouting. After grouting, the temperature is continuously monitored to verify the sealing effect, forming a closed-loop operation of monitoring-identification-grouting-verification. This effectively improves the timeliness, accuracy, and effectiveness of early warning for coal mine curtain grouting and reduces underground safety risks.

[0067] In some embodiments, before deploying distributed fiber optic temperature sensing lines in the underground monitoring area of ​​a coal mine, the coal mine curtain grouting early warning method further includes: Based on at least one of the following: mine geological structure, historical heat records and gas distribution information, a risk level assessment is conducted on the monitoring area to obtain the risk level assessment results. Based on the risk level assessment results, the deployment path and monitoring node spacing of the distributed fiber optic temperature sensing line are determined.

[0068] When assessing the risk level of a monitored area, one or more information sources can be selected for the assessment based on the availability of actual data. When only mine geological structure information is used, areas with dense fractures and broken coal seams can be directly classified as high-risk areas by identifying geological anomalies such as faults, fissures, and weak coal seam zones, while other areas are classified as medium- or low-risk areas. When only historical heating records or spontaneous combustion event records are used, areas where overheating anomalies or spontaneous combustion have occurred can be classified as high-risk areas, adjacent areas as medium-risk areas, and other areas as low-risk areas. When only gas distribution information is used, areas with gas concentrations exceeding a preset threshold can be classified as high-risk areas, while other areas are classified as medium- or low-risk areas based on concentration gradients. When accessing multi-source risk information from mine geological structure layers, historical heat records or spontaneous combustion event records, gas concentration distribution data, ventilation system model output, construction drawings, and mining path information, a weighted scoring method is used to conduct regional hierarchical assessments. The weighted scoring indicators include risk parameters such as gas concentration, historical spontaneous combustion, wind speed disturbance zones, and geological anomalies, and corresponding scoring rules are set, as shown in Table 5 below: Table 5. Example of scoring rules

[0069] Based on the total weighted score, the monitoring area is then divided into Level 1, Level 2, and Level 3 risk zones, as follows: Level 1 Risk Zone (High Risk): Total score ≥ 8; Level 2 risk area (medium risk): Total score 4–7; Level 3 risk zone (low risk): Total score ≤ 3.

[0070] The determined risk level assessment results can be used as the basis for deployment, and then the deployment path, path density and monitoring node spacing of the distributed optical fiber temperature sensing line can be determined in a targeted manner. Specifically: in the first-level risk area, the deployment spacing is ≤1 meter, and a two-way coverage method of top plate + two sides is adopted, and vertical jack optical fiber is introduced when necessary; in the second-level risk area, the deployment spacing is 1.5-3 meters, and a staggered coverage method of main path is adopted; in the third-level risk area, a through-type main line deployment or a node sampling coverage method of 50-100 meters is adopted.

[0071] Preferably, the distributed fiber optic temperature sensing line adopts an "interlaced + fixed spacing" layout, deployed along the goaf, roadway roof, and side walls of the coal mine. This includes a main line layout symmetrically laid along the roadway's central axis, and branch layouts interlaced in a sawtooth pattern along the side walls. Optional vertical deployment methods can also be added at roof cracks or gas outburst points. The determined deployment path must be secured with dustproof sleeves and anti-interference guide clips. These anti-interference guide clips are equipped with limiting guide grooves, anti-electromagnetic interference shielding layers, heat radiation resistant shells, and dustproof and drip-proof structures. They can be installed on the surface of the shaft wall or support structure using expansion bolts, adhesive tape, or magnetic structures. Furthermore, this deployment plan can be implemented through a control platform or manual design, and drawings can be exported. Alternatively, the platform can automatically annotate the map. Through this deployment strategy based on risk level assessment results, it is possible to achieve on-demand deployment and differentiated density of distributed fiber optic temperature sensing lines. This not only improves risk matching and enables key deployment in high-risk areas and resource conservation in low-risk areas, but also makes it more adaptable to construction. It can be deployed in advance according to the work schedule to avoid blind spots. At the same time, it can adjust the risk model and deployment strategy through subsequent data feedback to achieve self-iterative updates of the system. After being deployed in this way, the distributed fiber optic temperature sensing lines can also effectively improve the spatial resolution and anti-interference ability of temperature monitoring, enhance the structural adaptability in the humid, hot, vibrating and dusty environment of underground wells, improve the consistency and availability of temperature measurement data, and make subsequent maintenance, deployment adjustment and node expansion of the lines more convenient.

[0072] In some embodiments, the step of determining whether there is a temperature anomaly in the monitoring area specifically includes at least one of the following determination methods: Determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during the continuous sampling period; Determine whether the area of ​​the hot zone formed by multiple adjacent abnormal monitoring points is expanding and whether the area of ​​the hot zone expansion exceeds the second preset threshold. Determine whether, within a preset space range, there are more than a preset number of monitoring points simultaneously exhibiting a temperature exceeding a third preset threshold.

[0073] The specific implementation method of the step of determining whether there is a temperature anomaly in the monitoring area is basically the same as the specific implementation method of the corresponding anomaly judgment model mentioned above, and will not be repeated here.

[0074] In some embodiments, when multiple abnormal areas exist simultaneously, the coal mine curtain grouting early warning method further includes: The grouting priority of each abnormal region is calculated based on the temperature rise rate, hot zone expansion speed, and spatial importance of each abnormal region. The control platform module sends grouting control commands to the corresponding grouting terminal devices in sequence according to the grouting priority.

[0075] Specifically, the purpose of this step is to avoid problems such as simultaneous activation of grouting terminals, resource conflicts, or priority response for non-critical areas when multiple abnormal areas trigger grouting simultaneously, thus ensuring grouting effectiveness and system stability. Specifically, the control platform module 400 first groups multiple abnormal areas that simultaneously meet the conditions of exceeding the temperature rise rate limit, multi-point clustering anomalies, or simultaneous expansion of hot zones into a "set of points to be grouted." Then, based on a multi-index scoring model, it calculates the total risk score for each abnormal area to determine the grouting priority. In addition to the aforementioned temperature rise rate, hot zone expansion speed, and spatial location importance, the scoring indicators may also include spatial clustering and the number of existing grouting operations. Each indicator is assigned a suggested weight: temperature rise rate 30%, hot zone expansion speed 20%, spatial clustering 20%, spatial location importance 15%, and the number of existing grouting operations 15%, as shown in Table 6. Table 6 Scoring Indicators

[0076] The specific scoring logic is as follows: the rate of temperature rise is scored linearly according to the rate value (e.g., >3℃ / h gets full marks), the rate of hot zone expansion is scored linearly according to the area growth rate (e.g., >15 m² / h gets full marks), the spatial concentration is scored higher if the distance between abnormal monitoring points in the abnormal area is smaller, the spatial location importance is increased if the abnormal area is close to the mining face or the main ventilation area, and the number of times grouting has been performed is prioritized for abnormal areas that have not been grouted.

[0077] For each abnormal area, the overall risk score is... :

[0078] in, The control platform module 400 assigns weight coefficients to each indicator, P to the spatial location importance score, and Ni to the number of times the corresponding abnormal area has been grouted. After calculating the total risk score for each abnormal area, the module sorts all abnormal areas from highest to lowest score. It then determines the number of currently available grouting terminal devices (connected and unused). If the number of available terminals is insufficient, batch scheduling is performed. The module supports manually setting the "maximum number of simultaneous grouting points." Subsequently, based on the sorting results, grouting control commands are sent sequentially to the corresponding grouting terminal devices to activate them and perform fixed-point sealing grouting operations. After each grouting and sealing operation is completed, the control platform module 400 updates the assessment of the corresponding abnormal area. The system will re-evaluate whether an area is still considered an abnormal area to avoid repeated grouting operations. To further ensure smooth scheduling, a concurrency control and conflict avoidance mechanism is also in place. The grouting terminal supports a "queue mode," entering a waiting state if it is currently unavailable upon receiving an instruction. If the distance between grouting terminal devices corresponding to multiple abnormal areas is less than 3 meters (there is overlapping grouting impact range), the system will lock the terminal corresponding to the next abnormal area and delay execution. If the grouting terminal device corresponding to a high-risk abnormal area malfunctions, the system will skip that terminal and record alarm information to prevent the task from hanging and ensure the entire grouting scheduling process is orderly and efficient.

[0079] In some embodiments, the coal mine curtain grouting early warning method further includes: Based on the temperature data of each monitoring point in the underground monitoring area of ​​the coal mine, the temperature fluctuation trend of each monitoring point is analyzed. Based on temperature fluctuation trends, a comprehensive risk assessment was conducted in conjunction with the geological structure, ventilation conditions, and historical event records of the monitored area to identify potential risk areas. Send a preventative grouting command to the grouting terminal device corresponding to the potential risk area to perform local curtain grouting operation.

[0080] It should be noted that the temperature data is obtained by distributed fiber optic temperature sensing lines, which are pre-deployed in high-risk areas such as goaf, corner coal, or fracture zones, and fixed at the roof and sidewalls using a multi-path interlacing method. The data is continuously collected by a temperature data acquisition host (such as a DTS host or edge acquisition module) at a monitoring interval of 60s–180s, an accuracy of ±0.2℃, and a spatial resolution of 1–2m. The deployment density is set according to the risk level, with denser deployment in high-risk areas. The temperature fluctuation trend of each monitoring point is analyzed, specifically including whether the temperature rise rate of the monitoring point exceeds a preset threshold within the continuous sampling period, whether multiple adjacent monitoring points simultaneously show a temperature rise phenomenon and form a continuous hot zone expansion trend, and whether multiple thermal anomaly points form an expanding cluster in space to meet the condition of multi-point temperature rise co-occurrence. Temperature trend extrapolation can also be performed by combining LSTM models. Furthermore, a historical reference model of temperature changes is established based on this temperature data. Based on temperature fluctuation trends, combined with the geological structure of the monitoring area (such as faults, fissures, and weak coal seam zones), ventilation conditions (such as areas with low or turbulent airflow), and historical event records (such as historical records of heating or spontaneous combustion events), a weighted scoring method is used to conduct a comprehensive risk assessment. The weighted scoring indicators include risk parameters such as gas concentration, historical spontaneous combustion, wind speed disturbance areas, and geological anomalies, and corresponding scoring rules are set to identify potential risk areas that may not have triggered immediate temperature anomalies but have the potential for temperature rise.

[0081] Subsequently, a preventive grouting command is sent to the grouting terminal device corresponding to the potential risk area to perform local curtain grouting operation. The parameters of the preventive grouting (pressure, flow rate, time) can be preset or dynamically adjusted according to the risk level of the potential risk area. The grouting terminal device achieves directional sealing through an expandable grouting bag. This preventive grouting process can be fully automated and is suitable for unattended scenarios. After grouting, the temperature change in the area is continuously monitored, and the area risk level parameters are updated to provide a basis for subsequent deployment.

[0082] Furthermore, before sending the preventive grouting command, the control platform module 400 first determines the status of the grouting terminal device corresponding to the potential risk area. After confirming that the terminal has been deployed, is not occupied, and the grouting pipeline is connected, it then issues a command containing specific grouting parameters. During the grouting process, the terminal device will feed back the real-time status of grouting pressure, flow rate, etc., to the control platform through the communication interface, so that the platform can dynamically adjust the parameters according to the actual situation. After the grouting is completed, the system will continuously collect temperature data of the potential risk area at a preset monitoring interval. Combined with the established historical reference model (such as historical average model, temperature fluctuation model, regional difference model), the system compares the temperature fluctuation trend before and after grouting to determine the prevention and control effect of preventive grouting. If the temperature fluctuation tends to be stable and there is no obvious risk of temperature rise, the prevention and control is determined to be effective, and the risk level score of the area is updated synchronously. The fiber optic deployment density or monitoring frequency in the area can be appropriately reduced to optimize resource allocation. If abnormal temperature fluctuations are still detected and there is a risk of temperature rise, the preventive grouting command is sent again. The backup grouting terminal device can be activated or the grouting pressure can be adjusted or the grouting time extended for pressurized replenishment until the risk is eliminated.

[0083] Furthermore, all operational data related to preventive grouting (including grouting terminal number, grouting parameters, grouting time, coordinates of potential risk areas, post-grouting temperature monitoring data, and control effect assessment results) will be recorded and archived, supporting subsequent data traceability. This data will also be used to optimize the weighted scoring rules for comprehensive risk assessment and the preset thresholds for the temperature anomaly judgment model, enabling self-iterative updates to the system's risk assessment and control strategies. This will further improve the accuracy of potential risk area identification and the targeted nature of preventive grouting. This preventive grouting step is deeply integrated with the system's overall "monitoring-identification-grouting-verification" closed-loop process, ensuring that it does not affect the efficiency of emergency response to immediate temperature anomalies while proactively curbing potential temperature rises, reducing the frequency and workload of subsequent emergency grouting, effectively lowering safety risks in areas such as goaf and fracture zones in coal mines, adapting to the fully automated control needs of unmanned working faces, and balancing control effectiveness with resource utilization.

[0084] Specifically, the method of preventive grouting for potential risk areas differs from the aforementioned emergency grouting scheme based on automatic temperature anomaly triggering. The main purpose is to obtain the temperature fluctuation amplitude, fluctuation frequency, and spatial temperature difference distribution of each monitoring point by recording and analyzing long-term temperature data of the monitoring area when the monitoring system has not triggered a severe temperature rise warning. Under the premise that the temperature anomaly judgment conditions are not met, the comprehensive risk assessment process is further refined by combining multi-dimensional information such as regional geological structure, ventilation conditions, historical gas concentration records, or spontaneous combustion event distribution. The focus is on identifying areas with abnormal fluctuation characteristics but which have not yet formed a contiguous hot zone as potential risk areas. Specifically, it is applicable to scenarios where the temperature standard deviation is significantly high, the continuous slow upward trend is not drastic, multiple mild anomalies occur simultaneously, or the average temperature difference with the adjacent area is >2℃, the local hot zone is small but persistent, the location is close to the construction planning path or ventilation dead corner, and the hidden dangers such as poor sealing or grouting failure, roof fracture, or soft coal body in old roadways are prone to occur.

[0085] To achieve proactive safety control, this system not only provides an emergency grouting mechanism for sudden risks but also establishes a preventative grouting (pre-grouting) strategy based on risk assessment. This allows for the pre-sealing or structural reinforcement of suspected areas before actual hazards interfere with the work environment. The pre-grouting strategy uses "moderate anomaly + spatial co-occurrence + continuous displacement" as the main criteria for judgment: when a section continuously exhibits a moderate temperature rise rate (e.g., ≥4℃ / h), multiple spatial co-occurrence phenomena, and this continues for more than a set time (e.g., 30 minutes), but does not reach the high response threshold, the system will trigger the pre-grouting assessment process according to the rule base. Its execution process differs from the emergency grouting mechanism for high-level responses, as detailed below: Table 7. Examples of Comparison between Preventive Grouting and Emergency Grouting

[0086] During implementation, pre-grouting operations are still completed through the grouting response terminal, but scheduling instructions are issued after manual review by the control platform, and operations can be withdrawn after the sealing risk is confirmed, supporting a flexible "confirmation-based execution" strategy. Furthermore, the pre-grouting section typically covers a "risk transition zone," preferably located at the edge of high-temperature hotspots, to delay or block the further spread of potential heat sources. The method combines a scoring model, spatial clustering determination, and historical offset data in synergistic operation, exhibiting high adaptability and practicality. It can achieve local sealing or pretreatment in advance without affecting normal mine operations, thus playing a crucial role in the overall safety control system.

[0087] After identifying potential risk areas, the control platform module 400 pre-determines potentially high-risk grouting areas based on risk level classification and temperature fluctuation scores. After manual confirmation or platform-preset screening, these areas are marked as groutable zones that will not interfere with normal operations. Simultaneously, the availability of the grouting terminal device in this area and the current operating time are re-verified to ensure that grouting operations will not affect normal downhole production. Subsequently, during non-working hours or when avoiding operations, a pre-set grouting command is sent to the target grouting terminal device, triggering localized curtain grouting that does not rely on abnormal triggers. Grouting adopts a "low-pressure slow injection" mode, with the injection pressure typically 60-70% of the conventional emergency grouting pressure. During grouting, the system only automatically records grouting data without triggering alarms to avoid interfering with on-site operations. After grouting is completed, the system does not set "key tracking" for this area but instead switches to "slow monitoring," continuously collecting temperature change trends in the area at preset monitoring intervals as an assessment of grouting effectiveness and system risk. The system updates the risk level reference. If the temperature fluctuation in the area decreases, the system updates it to a "risk mitigation zone" to further optimize the monitoring resource allocation in the area. If the temperature continues to rise slowly, it is upgraded to an "abnormal candidate zone" and transferred to the formal monitoring queue for further handling. At the same time, the feedback results of the grouting effect will be used to correct the pre-grouting strategy parameters, such as the temperature fluctuation threshold and the accuracy of the cooling curve matching. Users can also set daily or weekly planned pre-grouting tasks according to production needs. The control platform module 400 can automatically execute according to the preset plan to achieve normalized pre-prevention and control. Through this preventive grouting method, "pre-intervention, safety reinforcement, and unmanned area protection" can be achieved in high-risk areas of coal mines, curbing the risk of temperature rise in advance and avoiding the waste of resources caused by large-scale and high-intensity emergency grouting in the later stage. At the same time, through the three-data closed-loop feedback of temperature-grouting-temperature recovery, the accuracy of the system's risk area prediction is further improved, and the system's scenario adaptability and fully automated prevention and control capabilities are strengthened.

[0088] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0089] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications are also considered to be within the scope of protection of this application.

Claims

1. A coal mine curtain grouting early warning system, characterized in that, include: The fiber optic temperature measurement module includes a distributed fiber optic temperature sensing line deployed in the monitoring area of ​​the coal mine, and a temperature data acquisition host connected to the distributed fiber optic temperature sensing line. The fiber optic temperature measurement module is used to continuously collect and output the temperature data of each monitoring point in the monitoring area. The temperature identification and risk assessment module is communicatively connected to the temperature data acquisition host and control platform module. The temperature identification and risk assessment module is used to receive the temperature data, process the temperature data based on a preset anomaly judgment model, determine whether there is a temperature anomaly in the monitoring area, and output the location information of the anomaly area to the control platform module. The curtain grouting response module is communicatively connected to the temperature identification and risk assessment module. The curtain grouting response module includes at least one grouting terminal device preset in the monitoring area. The grouting terminal device is used to receive grouting control commands and perform fixed-point grouting operations. The control platform module is communicatively connected to the temperature identification and risk assessment module and the curtain grouting response module, respectively. The control platform module is used to receive the location information of the abnormal area, generate grouting control commands and send the grouting control commands to the grouting terminal device corresponding to the abnormal area, and continuously acquire the temperature data of the abnormal area after the grouting operation is completed to determine the sealing effect.

2. The coal mine curtain grouting early warning system according to claim 1, characterized in that, The distributed optical fiber temperature sensing lines are laid on the roof and side walls of the tunnel using a multi-path staggered layout and are fixed by dustproof sleeves and anti-interference guide clips.

3. The coal mine curtain grouting early warning system according to claim 1, characterized in that, The grouting terminal device includes an outer shell, a quick-connect grouting interface disposed on the outer shell, and a support device for temporarily or permanently deploying the grouting terminal device in the target area.

4. The coal mine curtain grouting early warning system according to claim 1, characterized in that, The control platform module includes a sealing effect judgment unit. The sealing effect judgment unit is used to continuously receive temperature data of the abnormal area after the grouting operation is completed, compare the temperature change trend before and after grouting with the preset cooling trend model, and generate a secondary grouting control command if the sealing effect is not up to standard.

5. The coal mine curtain grouting early warning system according to claim 1, characterized in that, The anomaly detection model includes at least one of the following: The temperature rise rate model is used to determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during a continuous sampling period. The hot zone expansion trend model is used to determine whether a region formed by multiple adjacent monitoring points has formed a hot zone due to temperature anomalies, and whether the area of ​​the hot zone is expanding and the area of ​​the hot zone expansion exceeds a second preset threshold. The multi-point temperature rise co-occurrence model is used to determine whether there are more than a preset number of monitoring points simultaneously exceeding a third preset threshold within a preset spatial range.

6. A method for early warning of curtain grouting in coal mines, characterized in that, The coal mine curtain grouting early warning method is applied to the coal mine curtain grouting early warning system according to any one of claims 1 to 5. The coal mine curtain grouting early warning system includes a fiber optic temperature measurement module, a temperature identification and risk assessment module, a curtain grouting response module, and a control platform module. The temperature identification and risk assessment module is communicatively connected to the fiber optic temperature measurement module, the curtain grouting response module, and the control platform module, respectively. The control platform module is communicatively connected to the curtain grouting response module. The curtain grouting response module includes at least one grouting terminal device preset in the monitoring area. The coal mine curtain grouting early warning method includes: A distributed optical fiber temperature sensing line and a temperature data acquisition host connected to the distributed optical fiber temperature sensing line are deployed in the monitoring area of ​​the coal mine to form an optical fiber temperature measurement module. The optical fiber temperature measurement module continuously collects temperature data of each monitoring point in the monitoring area of ​​the coal mine. The temperature data is received by the temperature identification and risk assessment module, and the temperature data is processed based on the preset anomaly judgment model to determine whether there is a temperature anomaly in the monitoring area and to determine the location of the anomaly area. When an abnormal temperature occurs, the control platform module sends a grouting control command to the grouting terminal device corresponding to the abnormal area. The grouting terminal device is used to perform a fixed-point grouting operation. After the grouting operation is completed, temperature data of the abnormal area is continuously collected, and the sealing effect is judged through the control platform module.

7. The early warning method for curtain grouting in coal mines according to claim 6, characterized in that, The step of determining whether there is a temperature anomaly in the monitoring area specifically includes at least one of the following determination methods: Determine whether the temperature rise rate of the monitoring point exceeds the first preset threshold during the continuous sampling period; Determine whether the area of ​​the hot zone formed by multiple adjacent abnormal monitoring points is expanding and whether the area of ​​the hot zone expansion exceeds the second preset threshold. Determine whether, within a preset space range, there are more than a preset number of monitoring points simultaneously exhibiting a temperature exceeding a third preset threshold.

8. The early warning method for curtain grouting in coal mines according to claim 6, characterized in that, Before deploying distributed fiber optic temperature sensing lines in the underground monitoring area of ​​the coal mine, the coal mine curtain grouting early warning method further includes: Based on at least one of the following: mine geological structure, historical heat records and gas distribution information, a risk level assessment is conducted on the monitoring area to obtain the risk level assessment results. Based on the risk level assessment results, the deployment path and monitoring node spacing of the distributed optical fiber temperature sensing line are determined.

9. The early warning method for curtain grouting in coal mines according to claim 6, characterized in that, When multiple abnormal areas exist simultaneously, the coal mine curtain grouting early warning method further includes: The grouting priority of each abnormal region is calculated based on the temperature rise rate, hot zone expansion speed, and spatial importance of each abnormal region. The control platform module sends grouting control commands to the corresponding grouting terminal devices in sequence according to the grouting priority.

10. The early warning method for curtain grouting in coal mines according to claim 6, characterized in that, The coal mine curtain grouting early warning method also includes: Based on the temperature data of each monitoring point in the underground monitoring area of ​​the coal mine, the temperature fluctuation trend of each monitoring point is analyzed. Based on the temperature fluctuation trend, a comprehensive risk assessment is conducted in conjunction with the geological structure, ventilation conditions, and historical event records of the monitored area to identify potential risk areas. A preventative grouting command is sent to the grouting terminal device corresponding to the potential risk area to perform a local curtain grouting operation.

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