Method, device, equipment, medium and product for pre-warning coal spontaneous combustion in super-long roadway

Abstract

This disclosure relates to the field of coal mine safety technology, and in particular provides a method, device, equipment, medium, and product for early warning of spontaneous combustion of coal in ultra-long roadways. In this disclosure, a temperature field inversion model of the ultra-long roadway is used to determine the temperature field inversion results; based on the temperature field inversion results, the extension direction of the ultra-long roadway is divided into sections to obtain borehole distribution results; based on the borehole distribution results and the temperature field inversion results, the coal wall temperature of the ultra-long roadway is determined; based on the coal wall temperature and the segmented temperature thresholds, the early warning result for spontaneous combustion of coal is determined. Through the temperature inversion model of the ultra-long roadway, the core temperature region and spatial distribution characteristics within the ultra-long roadway can be effectively identified, and monitoring sections can be scientifically divided for uniform drilling. The internal thermal evolution process of the coal seam within each borehole is determined, improving the ability to identify early signs of temperature rise, which is beneficial for the early identification and precise control of spontaneous combustion of coal. Therefore, the accuracy of early warning for spontaneous combustion of coal in ultra-long roadways can be improved.

Description

Technical Field

[0001] This disclosure belongs to the field of coal mine safety technology, specifically relating to a method, device, equipment, medium, and product for early warning of spontaneous combustion of coal in ultra-long roadways. Background Technology

[0002] During coal mining, ultra-long roadways, due to their unique structure and service characteristics, become high-risk areas for spontaneous combustion at each layer. Especially in mines with long working faces, favorable geological conditions at each layer, and intense mining disturbances, the coal is prone to self-heating accumulation due to air infiltration and oxidation, leading to spontaneous combustion. Such spontaneous combustion accidents not only disrupt the mine's safe production order but also seriously threaten the lives of miners, causing enormous economic losses. Summary of the Invention

[0003] This disclosure addresses some deficiencies mentioned in the background art by providing a method, apparatus, equipment, medium, and product for early warning of spontaneous combustion of coal in ultra-long tunnels, which can improve the accuracy of early warning of spontaneous combustion of coal in ultra-long tunnels.

[0004] In a first aspect, embodiments of this disclosure provide a method for early warning of spontaneous combustion of coal in ultra-long roadways, comprising: Based on the temperature field inversion model of ultra-long tunnels, the temperature field inversion results are determined. Based on the temperature field inversion results, the extension direction of the ultra-long tunnel is divided into sections to obtain the borehole distribution results; Based on the borehole distribution results and the temperature field inversion results, the coal wall temperature of the ultra-long roadway is determined. Based on the coal wall temperature and segmented temperature thresholds, the coal natural early warning result is determined.

[0005] Optionally, the temperature field inversion model based on ultra-long tunnels determines the temperature field inversion results by including: Based on the first temperature and the temperature field inversion model, the temperature field inversion result is generated. The first temperature is temperature data obtained along the extension direction of the ultra-long tunnel. The first temperature is collected by multiple first temperature sensors, which are evenly spaced along the extension direction of the ultra-long tunnel.

[0006] Optionally, the temperature field inversion model is related to the first temperature data collected by the Mth first temperature sensor and the Euclidean distance of the Mth first temperature sensor, where M is a positive integer.

[0007] Optionally, the step of dividing the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results to obtain borehole distribution results includes: Based on the temperature field inversion results and the preset risk level, the extension direction of the ultra-long tunnel is divided into sections to obtain the monitoring area; For each of the monitoring areas, the thermal anomaly diffusion radius is determined based on the thermal anomaly diffusion model; For each monitoring area, based on the thermal anomaly diffusion radius, boreholes are drilled in the extension direction of the ultra-long tunnel to obtain the borehole distribution results.

[0008] Optionally, determining the thermal anomaly diffusion radius for each monitored area based on a thermal anomaly diffusion model includes: Based on the coal body parameters and inherent thermal conductivity of the ultra-long roadway, the effective thermal conductivity of each monitoring area is determined. The coal body parameters include at least the degree of development of fractures and pores. Based on the environmental parameters and coal oxidation heat potential of the ultra-long tunnel, the heat release intensity per unit volume of coal in each monitoring area is determined, and the environmental parameters include at least the local oxygen concentration. The thermal anomaly diffusion radius is determined based on the heat release intensity per unit volume of the coal in each monitoring area, the effective thermal conductivity, and the natural critical temperature rise threshold of the coal.

[0009] Optionally, determining the coal wall temperature of the ultra-long roadway based on the borehole distribution results and the temperature field inversion results includes: For each borehole in the borehole distribution results, based on the temperature field inversion results, the monitoring point for the coal wall temperature is determined along the axial direction of the borehole. Based on each of the monitoring points, the coal wall temperature is determined. The coal wall temperature is acquired by setting a second temperature sensor at each of the monitoring points, wherein the number of monitoring points is a positive integer greater than or equal to 2.

[0010] Optionally, determining the coal natural early warning result based on the coal wall temperature and the segmented temperature threshold includes: Based on the coal wall temperature and the preset segmented temperature thresholds, the abnormal area of ​​the coal wall temperature is determined, and the coal natural early warning result is obtained; wherein, the segmented temperature thresholds include at least one of the following: critical temperature threshold, dry cracking temperature threshold, and ignition temperature threshold.

[0011] In a second aspect, embodiments of this disclosure provide an early warning device for spontaneous combustion of coal in ultra-long tunnels, comprising: The first determining module is used to determine the temperature field inversion results based on the temperature field inversion model of ultra-long tunnels; The region division module is used to divide the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results, and obtain the borehole distribution results. The second determining module is used to determine the coal wall temperature of the ultra-long roadway based on the borehole distribution results and the temperature field inversion results. The third determining module is used to determine the coal natural early warning result based on the coal wall temperature and the segmented temperature threshold.

[0012] In a third aspect, embodiments of this disclosure provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for early warning of spontaneous combustion of coal in ultra-long tunnels.

[0013] In a fourth aspect, embodiments of this disclosure provide a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the above-described method for early warning of spontaneous combustion of coal in ultra-long tunnels.

[0014] In a fifth aspect, embodiments of this disclosure provide a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device executes the above-described method for early warning of spontaneous combustion of coal in ultra-long tunnels.

[0015] This disclosure utilizes a temperature field inversion model for ultra-long roadways to determine the temperature field inversion results. Based on these results, the extension direction of the ultra-long roadway is divided into sections, yielding borehole distribution results. The coal wall temperature of the ultra-long roadway is determined based on the borehole distribution and temperature field inversion results. Finally, based on the coal wall temperature and segmented temperature thresholds, a coal spontaneous combustion early warning result is determined. The ultra-long roadway temperature inversion model effectively identifies the core temperature region and spatial distribution characteristics within the roadway, allowing for the scientific division of monitoring sections and uniform borehole drilling. Determining the internal thermal evolution process of the coal seam within each borehole enhances the ability to identify early signs of temperature rise, facilitating early identification and precise control of coal spontaneous combustion. Therefore, it can improve the accuracy of early warning for coal spontaneous combustion in ultra-long roadways.

[0016] It should be understood that both the foregoing general description and the following detailed description are exemplary and intended to provide further illustration of the claimed technology. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for early warning of spontaneous combustion of coal in ultra-long tunnels, as disclosed in this publication.

[0018] Figure 2 This is a schematic diagram of the borehole distribution provided in this disclosure.

[0019] Figure 3 A schematic diagram showing the temperature trend inside the borehole before and after the implementation of the prevention and control measures provided in this disclosure.

[0020] Figure 4 This is another flowchart of a method for early warning of spontaneous combustion of coal in ultra-long tunnels provided in this disclosure.

[0021] Figure 5 This is a schematic diagram of the structure of an early warning device for spontaneous combustion of coal in an ultra-long tunnel, as provided in this disclosure.

[0022] Figure 6 This is a hardware block diagram of an electronic device provided in this disclosure.

[0023] Figure 7 This is a schematic diagram of a computer program product provided in this disclosure. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solution of this application, the application scenario of this application will be described first below.

[0025] Currently, traditional methods for monitoring spontaneous coal combustion mainly rely on manual inspections, single-point temperature detection, infrared thermal imaging, and gas concentration analysis. While these methods have some practicality in conventional roadways, they generally suffer from problems such as small monitoring coverage, slow response times, low spatial resolution, and inability to accurately locate temperature rise areas in mining roadways with ultra-long distances, complex ventilation, and long cycles. They are particularly inadequate under the specific conditions of ultra-long roadways. Furthermore, existing monitoring systems are mostly concentrated on single-point sampling or vertical borehole depth monitoring, which cannot meet the needs for identifying and issuing early warnings of large-scale, multi-point synchronous temperature change trends along the roadway.

[0026] As coal mines expand in scale and increase in mining depth, more and more operations face scenarios involving "ultra-long tunnels," typically exceeding 3,000 meters in length. These tunnels are characterized by long service cycles, challenging temperature control, and difficult inspections, placing higher demands on the coverage, sensing density, and early warning response time of monitoring systems. Existing technologies struggle to balance spatial resolution and temporal response efficiency in such complex scenarios, exhibiting significant limitations in adaptability.

[0027] To address the aforementioned technical problems, this disclosure provides an inventive concept: combining coal seam structural characteristics with a temperature inversion model for ultra-long roadways, it can effectively identify the core temperature region and spatial distribution characteristics within ultra-long roadways, and scientifically divide monitoring sections for uniform drilling. This determines the internal thermal evolution process of the coal seam within each borehole, improving the ability to identify early signs of temperature rise, which is beneficial for the early identification and precise control of coal spontaneous combustion. Therefore, it can improve the accuracy of early warning for coal spontaneous combustion in ultra-long roadways.

[0028] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present disclosure and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the drawings, not the entire structure.

[0029] Figure 1 This is a flowchart illustrating a method for early warning of spontaneous combustion of coal in ultra-long roadways, as disclosed in this publication. Figure 1 As shown, the method includes: S101: Determine the temperature field inversion results based on the temperature field inversion model of ultra-long tunnels.

[0030] Specifically, by using a pre-built temperature field inversion model, a two-dimensional temperature field distribution result of the entire ultra-long tunnel can be generated, i.e., the temperature field inversion result, thereby macroscopically identifying high-temperature anomaly areas in the tunnel.

[0031] S102: Based on the temperature field inversion results, the extension direction of the ultra-long tunnel is divided into sections to obtain the borehole distribution results.

[0032] Specifically, based on the temperature field inversion results, monitoring sections are divided along the extension direction of the ultra-long roadway. Within each monitoring section, based on the thermal anomaly diffusion, boreholes are uniformly drilled along the roadway extension direction to obtain the borehole distribution results. By combining the temperature inversion results of the ultra-long roadway with its engineering geology and prevention and control measures, high-risk temperature anomaly areas are identified through the temperature field inversion results, enabling fixed-point temperature monitoring of the ultra-long roadway. This completes the process from data acquisition, spatial modeling, and regional selection, improving the understanding of the spatial distribution of the temperature field in ultra-long roadways and providing more targeted decision-making basis for coal spontaneous combustion prevention and control.

[0033] S103: Based on borehole distribution results and temperature field inversion results, determine the coal wall temperature of ultra-long roadways.

[0034] Specifically, within each monitoring section, for each borehole, the coal wall temperature is obtained along the borehole axis based on the temperature field inversion results. In other words, based on the temperature field inversion results, the temperature gradient along the axial direction of each borehole is identified and delineated. In the model of ultra-long roadways, high-temperature points are explicitly marked along the vertical direction of the coal wall, enabling temperature monitoring of different coal seams in the vertical direction of the coal wall.

[0035] S104: Determine the natural early warning result of coal based on coal wall temperature and segmented temperature thresholds.

[0036] Specifically, through experiments, the segmented temperature thresholds for different stages of coal spontaneous combustion in each monitoring section are determined. Based on the coal wall temperature and the segmented temperature thresholds, segmented comparisons are made to determine the temperature anomalies of different monitored coal seams within each monitoring section, thereby achieving three-dimensional dynamic monitoring of temperature anomalies in ultra-long roadways and assessing the risk of coal spontaneous combustion.

[0037] This disclosure utilizes a temperature field inversion model for ultra-long roadways to determine the temperature field inversion results. Based on these results, the extension direction of the ultra-long roadway is divided into sections, yielding borehole distribution results. The coal wall temperature of the ultra-long roadway is determined based on the borehole distribution and temperature field inversion results. Finally, based on the coal wall temperature and segmented temperature thresholds, a coal spontaneous combustion early warning result is determined. The ultra-long roadway temperature inversion model effectively identifies the core temperature region and spatial distribution characteristics within the roadway, allowing for the scientific division of monitoring sections and uniform borehole drilling. Determining the internal thermal evolution process of the coal seam within each borehole enhances the ability to identify early signs of temperature rise, facilitating early identification and precise control of coal spontaneous combustion. Therefore, it can improve the accuracy of early warning for coal spontaneous combustion in ultra-long roadways.

[0038] In one possible implementation, an exemplary method for determining the temperature field inversion results based on a temperature field inversion model for ultra-long tunnels includes: Based on the first temperature and the temperature field inversion model, the temperature field inversion results are generated.

[0039] The first temperature is temperature data obtained along the extension direction of the ultra-long tunnel; the first temperature is collected by multiple first temperature sensors, which are evenly spaced along the extension direction of the ultra-long tunnel.

[0040] Specifically, to mitigate the spontaneous combustion risk of coal seams in ultra-long roadways, the key lies in identifying the hidden high-temperature core area within the roadway. However, in reality, observation conditions inside ultra-long roadways are limited, making it difficult to achieve comprehensive coverage through numerous sensors or boreholes; only discrete and limited observation data can be relied upon. Therefore, in this embodiment, along the extension direction of the ultra-long roadway, multiple first temperature sensors are deployed within the coal seam to acquire discrete temperature data, i.e., the first temperature, of the ultra-long roadway. The extension direction can be understood as the axial direction of the ultra-long roadway.

[0041] For example, the temperature field inversion model is related to the first temperature data collected by the Mth first temperature sensor and the Euclidean distance of the Mth first temperature sensor, where M is a positive integer.

[0042] By using a limited number of discrete temperature data, the overall temperature field of the ultra-long tunnel is constructed using an ultra-long tunnel temperature field inversion model, in order to reflect the internal temperature distribution characteristics of the ultra-long tunnel.

[0043] The following formula is an exemplary formula expression for the temperature field inversion model:

[0044] in, Coordinates The inversion temperature at that location, It is the temperature of the m-th sensor. It is a point The Euclidean distance to the m-th sensor.

[0045] In one possible implementation, temperature data at discrete points within the ultra-long roadway are acquired using a first temperature sensor. Combined with the spatial coordinates of the first temperature sensor, a grid coordinate system covering the entire ultra-long roadway is generated. To ensure the inversion results remain consistent with the actual coal seam boundaries, a point-in-polygon mask function can be used on the Matlab platform to trim grid points outside the boundaries, retaining only valid inversion (predicted) values ​​within the study area. Simultaneously, a scattered interpolant function is invoked to use the temperature field inversion model for temperature prediction, thus inverting the temperature field of the ultra-long roadway.

[0046] In one possible implementation, an exemplary method for dividing the extension direction of an ultra-long tunnel into sections based on temperature field inversion results to obtain borehole distribution results includes: Based on the temperature field inversion results and the preset risk level, the extension direction of the ultra-long tunnel is divided into sections to obtain the monitoring area; for each monitoring area, the thermal anomaly diffusion radius is determined based on the thermal anomaly diffusion model; for each monitoring area, based on each thermal anomaly diffusion radius, boreholes are drilled in the extension direction of the ultra-long tunnel to obtain the borehole distribution results.

[0047] Specifically, based on the temperature field inversion results, high-temperature points are explicitly marked along the extension direction of the ultra-long tunnel in the model to identify and delineate high-temperature anomaly areas within the tunnel. In other words, based on the inverted temperature field of the ultra-long tunnel, monitoring sections are divided according to the temperature gradient along the tunnel's extension direction. Combined with preset risk levels, the tunnel is divided into high, medium, and low-risk monitoring sections. Areas with significant high-temperature anomalies and drastic temperature gradient changes within the ultra-long tunnel are designated as high-risk monitoring sections; areas with only slight temperature increases or gentle temperature gradients are designated as medium-risk monitoring sections; and areas with temperatures close to background values ​​are designated as low-risk monitoring sections. By dividing the ultra-long tunnel into different monitoring areas along its extension direction through temperature field inversion, temperature zoning of the entire ultra-long tunnel along its extension direction is achieved.

[0048] Within each monitoring section, based on the constructed thermal anomaly diffusion model, the thermal anomaly diffusion radius within each monitoring section is determined according to the inherent thermal conductivity of the coal and the heat release intensity per unit volume of the coal. This guides the borehole layout along the roadway extension direction within that monitoring section, forming a scientific and reasonable borehole layout scheme.

[0049] For example, for each monitoring area, based on the thermal anomaly diffusion model, the thermal anomaly diffusion radius is determined as follows: Based on the coal body parameters and inherent thermal conductivity of the ultra-long roadway, the effective thermal conductivity of each monitoring area is determined; based on the environmental parameters of the ultra-long roadway and the coal oxidation exothermic potential, the heat release intensity per unit volume of the coal in each monitoring area is determined; based on the heat release intensity per unit volume of the coal, the effective thermal conductivity, and the natural critical temperature rise threshold of the coal in each monitoring area, the thermal anomaly diffusion radius is determined.

[0050] Among them, coal body parameters include at least the degree of development of fractures and pores; environmental parameters include at least the local oxygen concentration.

[0051] Specifically, the following formula is an exemplary formula expression for the temperature field inversion model:

[0052] in, Let be the effective thermal conductivity of the i-th segment. The inherent thermal conductivity of the coal body, For coal body parameters, Let be the heat release intensity per unit volume of the coal in the i-th section. The heat release potential of coal oxidation. For environmental parameters; The natural critical temperature rise threshold for coal. The radius of thermal anomaly diffusion.

[0053] Within each monitoring section, boreholes are drilled uniformly along the direction of the roadway extension. It should be noted that the maximum spacing between boreholes within a monitoring section is the thermal anomaly diffusion radius; that is, the maximum spacing between two adjacent boreholes within the same monitoring section is the thermal anomaly diffusion radius of that monitoring section.

[0054] Within ultra-long tunnels, geological and ventilation conditions vary across monitoring sections. For monitoring sections exhibiting existing temperature rise anomalies, disrupted ventilation, stress concentration, or structures such as temperature rise trend zones, face sections, mining areas, and interaction points, the borehole spacing can be appropriately increased. For identified high-risk areas, borehole density can be increased as appropriate.

[0055] In one possible implementation, an exemplary method for determining the coal wall temperature of an ultra-long roadway based on borehole distribution results and temperature field inversion results includes: For each borehole with the borehole distribution results, based on the temperature field inversion results, the monitoring points for coal wall temperature are determined along the borehole axis; and based on each monitoring point, the coal wall temperature is determined.

[0056] Specifically, the coal seam temperature is acquired by setting up a second temperature sensor at each monitoring point, where the number of monitoring points is a positive integer greater than or equal to 2. The second temperature sensor is used to directly obtain the actual temperature at different depths inside the coal seam.

[0057] Within each borehole, N key locations are selected as monitoring points based on the temperature gradient curve along the borehole axis obtained from the temperature field inversion results. Examples include: shallow (1-2 meters) monitoring points, temperature-changing layer monitoring points, and deep high-temperature zone monitoring points. For instance, the temperature gradient curve along the borehole axis is extracted from the temperature field inversion results to characterize the temperature change characteristics from the surface to the interior of the coal seam. Based on the temperature gradient curve of each borehole, N secondary temperature sensors are used to sense the cooling effect of ventilation convection and the temperature changes of the surface coal body within a 1-2 meter range within the coal wall surface (shallow monitoring points); to capture the activity of oxidation and exothermic processes within the coal body in the depth range with the largest temperature gradient (temperature-changing layer monitoring points); and to monitor the temperature evolution of the core thermal anomaly zone of the coal seam in the depth range where the predicted temperature is highest or has reached the warning threshold (deep high-temperature zone monitoring points). Figure 2 This is a schematic diagram of the borehole distribution provided in this disclosure, such as... Figure 2 As shown, the middle of the coal wall is an ultra-long roadway, the long strip area in the coal wall is a borehole, the circular area in the borehole is the second temperature sensor, and the area divided by the dashed line is the monitoring section determined based on the temperature field inversion results.

[0058] In addition, for boreholes with obvious temperature stratification and multiple high-temperature risk layers, the number of monitoring points will be increased; for boreholes with uniform temperature distribution and low risk, a minimum number of key monitoring points will be set up.

[0059] By dividing the roadway into different monitoring sections along its extension direction and determining the monitoring points along the vertical direction of the coal face within each monitoring section, a three-dimensional monitoring network for spontaneous combustion of coal in ultra-long roadways is constructed. This allows for a comprehensive understanding of the thermal evolution process within the coal seam, enhances the ability to identify early signs of temperature rise, and provides an effective technical path and support for the early identification and precise control of spontaneous combustion of coal.

[0060] In one possible implementation, an exemplary method for determining coal natural early warning results based on coal wall temperature and segmented temperature thresholds includes: Based on the coal wall temperature and preset segmented temperature thresholds, abnormal areas of coal wall temperature are determined, and natural early warning results for coal are obtained.

[0061] Specifically, the coal wall temperature measured by the second temperature sensor is compared with preset segmented temperature thresholds. These segmented temperature thresholds include at least one of the following: critical temperature threshold, cracking temperature threshold, and ignition temperature threshold. Based on the threshold level exceeded by the monitored coal wall temperature, temperature anomalies in different coal seams within each monitoring segment are determined, enabling three-dimensional dynamic monitoring of temperature anomalies in ultra-long roadways and assessing the risk of spontaneous combustion. When temperature monitoring shows that the coal wall temperature exceeds the segmented warning threshold, different levels of warning signals are triggered, and corresponding emergency response procedures are initiated (such as on-site verification and borehole grouting). For example, on-site verification is conducted, and effective prevention and control measures (such as borehole grouting) are implemented to prevent the spread of spontaneous combustion and ensure safe production in ultra-long roadways. Figure 3 A schematic diagram illustrating the temperature trend within the borehole before and after the implementation of the prevention and control measures provided in this disclosure is shown below. Figure 3 As shown, the temperature drops significantly after grouting, which can effectively prevent the natural spread of coal.

[0062] Figure 4 This is another flowchart of a method for early warning of spontaneous combustion of coal in ultra-long roadways provided in this disclosure. Figure 4 As shown, the method includes: S401: Install the first temperature sensor.

[0063] Specifically, M first temperature sensors are arranged at certain intervals along the extension direction of the ultra-long tunnel. The first temperature sensors are used to collect discrete temperature data along the axial direction of the tunnel.

[0064] S402: Construct a temperature field inversion model.

[0065] Specifically, the data from M sensors are input into the temperature field inversion model of the ultra-long tunnel. The temperature field inversion model has been described in detail above and will not be repeated here.

[0066] S403: Obtain the temperature field inversion results.

[0067] Specifically, a two-dimensional temperature field distribution map of the entire tunnel is generated based on the temperature field inversion model, thus obtaining the temperature field inversion result and macroscopically identifying high-temperature anomaly areas in the tunnel.

[0068] S404: Based on the temperature field inversion results, the monitoring sections are divided in the roadway.

[0069] Specifically, based on the temperature field obtained in step S403, the temperature gradient change along the direction of the roadway is analyzed. The roadway is divided into monitoring sections with three risk levels: high, medium, and low.

[0070] S405: Drilling layout.

[0071] Specifically, for each monitoring section, the thermal anomaly diffusion radius, i.e., the borehole spacing, is calculated using a thermal anomaly diffusion model based on its coal seam conditions (such as the degree of fracture and pore development) and environmental conditions (such as local oxygen concentration). Within each monitoring section, boreholes are drilled uniformly along the roadway extension direction. Within the same section, the spacing between adjacent boreholes is no greater than the calculated thermal anomaly diffusion radius for that section.

[0072] S406: Install the second temperature sensor.

[0073] Specifically, within each borehole, based on the temperature gradient curve along the borehole axis obtained from the temperature field inversion results, N (N≥2) key locations are selected as monitoring points. Second temperature sensors are deployed at these selected points to directly acquire the actual temperature at different depths within the coal seam.

[0074] S407: Natural early warning for coal mining.

[0075] Specifically, the temperature measured by the second temperature sensor is compared with preset segmented temperature thresholds. These segmented temperature thresholds include at least: a critical temperature threshold, a drying / cracking temperature threshold, and an ignition temperature threshold. Based on the threshold level exceeded by the monitored temperature, different levels of warning signals are triggered, and corresponding emergency response procedures are initiated.

[0076] Figure 5 This is a structural schematic diagram of an early warning device for spontaneous combustion of coal in ultra-long tunnels, as provided in this disclosure. Figure 5 As shown, the device 500 includes: a first determining module 510, a region dividing module 520, a second determining module 530, and a third determining module 540.

[0077] The first determining module 510 is used to determine the temperature field inversion results based on the temperature field inversion model of ultra-long tunnels; The region division module 520 is used to divide the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results, and obtain the borehole distribution results. The second determining module 530 is used to determine the coal wall temperature of the ultra-long roadway based on the borehole distribution results and the temperature field inversion results. The third determining module 540 is used to determine the coal natural early warning result based on the coal wall temperature and the segment temperature threshold.

[0078] Optionally, the first determining module is used to: Based on the first temperature and the temperature field inversion model, the temperature field inversion result is generated. The first temperature is temperature data obtained along the extension direction of the ultra-long tunnel. The first temperature is collected by multiple first temperature sensors, which are evenly spaced along the extension direction of the ultra-long tunnel.

[0079] Optionally, the region division module includes: The segmentation submodule is used to divide the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results and the preset risk level, so as to obtain the monitoring area; The first determining submodule is used to determine the thermal anomaly diffusion radius for each of the monitoring areas based on the thermal anomaly diffusion model. The drilling submodule is used to drill holes in the extension direction of the ultra-long tunnel for each of the monitoring areas, based on the thermal anomaly diffusion radius, to obtain the drilling distribution results.

[0080] Optionally, the first determining submodule is used to: Based on the coal body parameters and inherent thermal conductivity of the ultra-long roadway, the effective thermal conductivity of each monitoring area is determined. The coal body parameters include at least the degree of development of fractures and pores. Based on the environmental parameters and coal oxidation heat potential of the ultra-long tunnel, the heat release intensity per unit volume of coal in each monitoring area is determined, and the environmental parameters include at least the local oxygen concentration. The thermal anomaly diffusion radius is determined based on the heat release intensity per unit volume of the coal in each monitoring area, the effective thermal conductivity, and the natural critical temperature rise threshold of the coal.

[0081] Optionally, the second determining module is used to: For each borehole in the borehole distribution results, based on the temperature field inversion results, the monitoring point for the coal wall temperature is determined along the axial direction of the borehole. Based on each of the monitoring points, the coal wall temperature is determined. The coal wall temperature is acquired by setting a second temperature sensor at each of the monitoring points, wherein the number of monitoring points is a positive integer greater than or equal to 2.

[0082] Optionally, the third determining module is used to: Based on the coal wall temperature and the preset segmented temperature thresholds, the abnormal area of ​​the coal wall temperature is determined, and the coal natural early warning result is obtained; wherein, the segmented temperature thresholds include at least one of the following: critical temperature threshold, dry cracking temperature threshold, and ignition temperature threshold.

[0083] This application also provides an electronic device for implementing the above-described method for early warning of spontaneous combustion of coal in ultra-long tunnels. Please refer to... Figure 6 It illustrates a schematic diagram of an electronic device provided by some embodiments of this application. For example... Figure 6 As shown, the electronic device 6 includes: a processor 600, a memory 601, a bus 602, and a communication interface 603. The processor 600, the communication interface 603, and the memory 601 are connected via the bus 602. The memory 601 stores a computer program that can run on the processor 600. When the processor 600 runs the computer program, it executes the ultra-long tunnel coal spontaneous combustion early warning method provided in any of the foregoing embodiments of this application.

[0084] The memory 601 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between the device network element and at least one other network element is achieved through at least one communication interface 603 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0085] Bus 602 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory 601 is used to store programs. After receiving an execution instruction, the processor 600 executes the program. The ultra-long tunnel coal spontaneous combustion early warning method disclosed in any of the foregoing embodiments of this application can be applied to the processor 600, or implemented by the processor 600.

[0086] The processor 600 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 600 or by instructions in software form. The processor 600 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 601. Processor 600 reads the information in memory 601 and, in conjunction with its hardware, completes the steps of the above method.

[0087] The electronic device provided in this application embodiment and the coal spontaneous combustion early warning method for ultra-long tunnels provided in this application embodiment are based on the same inventive concept and have the same beneficial effects as the methods they adopt, operate or implement.

[0088] This application also provides a computer-readable storage medium corresponding to the ultra-long tunnel coal spontaneous combustion early warning method provided in the aforementioned embodiments. The computer-readable storage medium shown can be an optical disc, on which a computer program is stored. When the computer program is run by a processor, it will execute the ultra-long tunnel coal spontaneous combustion early warning method provided in any of the aforementioned embodiments.

[0089] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0090] The computer-readable storage medium provided in the above embodiments of this application and the method for early warning of spontaneous combustion of coal in ultra-long tunnels provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application stored therein.

[0091] This application also provides a computer program product 700, such as... Figure 7 As shown. This computer program product carries a computer program 701. The instructions included in the program code can be used to execute the steps of the ultra-long roadway coal spontaneous combustion early warning method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0092] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0093] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0094] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0095] Additionally, as used herein, the "or" used in a list of items beginning with "at least one" indicates a separate list, such that a list of, for example, "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not imply that the described example is preferred or better than other examples.

[0096] It should also be noted that in the systems and methods of this disclosure, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions to this disclosure.

[0097] Various changes, substitutions, and modifications can be made to the technology described herein without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, events, means, methods, and actions described above. Currently existing or later-developed processes, machines, manufactures, events, means, methods, or actions that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein can be utilized. Therefore, the appended claims include such processes, machines, manufactures, events, means, methods, or actions within their scope.

[0098] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0099] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A super-long roadway coal spontaneous combustion early warning method, characterized in that, include: Based on the temperature field inversion model of ultra-long tunnels, the temperature field inversion results are determined. Based on the temperature field inversion results, the extension direction of the ultra-long tunnel is divided into sections to obtain the borehole distribution results; Based on the borehole distribution results and the temperature field inversion results, the coal wall temperature of the ultra-long roadway is determined. Based on the coal wall temperature and segmented temperature thresholds, the coal natural early warning result is determined.

2. The method of claim 1, wherein, The temperature field inversion model based on ultra-long tunnels determines the temperature field inversion results, including: Based on the first temperature and the temperature field inversion model, the temperature field inversion result is generated. The first temperature is temperature data obtained along the extension direction of the ultra-long tunnel. The first temperature is collected by multiple first temperature sensors, which are evenly spaced along the extension direction of the ultra-long tunnel.

3. The method according to claim 2, characterized in that, The temperature field inversion model is related to the first temperature data collected by the Mth first temperature sensor and the Euclidean distance of the Mth first temperature sensor, where M is a positive integer.

4. The method according to claim 1, characterized in that, The process of dividing the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results to obtain borehole distribution results includes: Based on the temperature field inversion results and the preset risk level, the extension direction of the ultra-long tunnel is divided into sections to obtain the monitoring area; For each of the monitoring areas, the thermal anomaly diffusion radius is determined based on the thermal anomaly diffusion model; For each monitoring area, based on the thermal anomaly diffusion radius, boreholes are drilled in the extension direction of the ultra-long tunnel to obtain the borehole distribution results.

5. The method according to claim 4, characterized in that, For each of the monitored areas, the radius of thermal anomaly diffusion is determined based on a thermal anomaly diffusion model, including: Based on the coal body parameters and inherent thermal conductivity of the ultra-long roadway, the effective thermal conductivity of each monitoring area is determined. The coal body parameters include at least the degree of development of fractures and pores. Based on the environmental parameters and coal oxidation heat potential of the ultra-long tunnel, the heat release intensity per unit volume of coal in each monitoring area is determined, and the environmental parameters include at least the local oxygen concentration. The thermal anomaly diffusion radius is determined based on the heat release intensity per unit volume of the coal in each monitoring area, the effective thermal conductivity, and the natural critical temperature rise threshold of the coal.

6. The method according to claim 1, characterized in that, The determination of the coal wall temperature of the ultra-long roadway based on the borehole distribution results and the temperature field inversion results includes: For each borehole in the borehole distribution results, based on the temperature field inversion results, the monitoring point for the coal wall temperature is determined along the axial direction of the borehole. Based on each of the monitoring points, the coal wall temperature is determined. The coal wall temperature is acquired by setting a second temperature sensor at each of the monitoring points, wherein the number of monitoring points is a positive integer greater than or equal to 2.

7. The method according to claim 1, characterized in that, The determination of the coal natural early warning result based on the coal wall temperature and segmented temperature thresholds includes: Based on the coal wall temperature and the preset segmented temperature thresholds, the abnormal area of ​​the coal wall temperature is determined, and the coal natural early warning result is obtained; wherein, the segmented temperature thresholds include at least one of the following: critical temperature threshold, dry cracking temperature threshold, and ignition temperature threshold.

8. A coal spontaneous combustion early warning device for ultra-long tunnels, characterized in that, include: The first determining module is used to determine the temperature field inversion results based on the temperature field inversion model of ultra-long tunnels; The region division module is used to divide the extension direction of the ultra-long tunnel into sections based on the temperature field inversion results, and obtain the borehole distribution results. The second determining module is used to determine the coal wall temperature of the ultra-long roadway based on the borehole distribution results and the temperature field inversion results. The third determining module is used to determine the coal natural early warning result based on the coal wall temperature and the segmented temperature threshold.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by a processor to implement the method as described in any one of claims 1-7.

11. A computer program product, characterized in that, Includes computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the method as described in any one of claims 1-7.

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