Coal mine post-activity methane emission patrol method and device and electronic equipment

Abstract

This application discloses a method, device, and electronic equipment for monitoring methane emissions from post-mine coal mining activities. It utilizes a drone equipped with a methane detection module to conduct large-scale continuous monitoring along a planned route. When anomalies are detected, multi-height detection is used to obtain the three-dimensional spatial distribution of methane concentration, and real-time wind field information is combined to correct the concentration data. This forms a complete emission area identification link from planar screening and vertical distribution characterization to wind field interference correction, overcoming the limitations of insufficient spatial coverage of fixed sites, low resolution of satellite remote sensing, and the difficulty of conventional drone detection adapting to the low-concentration, non-uniform, and wind-affected characteristics of post-mine methane emissions. Therefore, it can solve the technical problems of existing monitoring technologies failing to meet the needs of rapid monitoring of post-mine methane emissions and accurately identifying emission areas, achieving the technical effect of rapid and accurate identification of post-mine coal methane emission areas.

Description

Technical Field

[0001] This disclosure relates to the field of methane emission monitoring technology in coal mine post-operation activities, and in particular to a method, apparatus and electronic equipment for monitoring methane emissions from coal mine post-operation activities. Background Technology

[0002] Post-mining activities are a significant component of methane emissions throughout the coal lifecycle. After coal is mined underground and brought to the surface, a certain amount of adsorbed and free methane remains inside the coal seam. During coal washing, crushing, screening, storage, transportation, and transshipment, methane desorption and release continue to occur due to factors such as coal structure disturbance, particle size changes, ambient temperature changes, and pressure release.

[0003] Currently, monitoring methods for methane emissions from post-coal mine activities mainly include fixed monitoring, satellite remote sensing, and drone-based surveillance. Fixed monitoring equipment is typically installed at fixed ground locations and can only acquire localized methane concentration changes, making it difficult to comprehensively reflect the continuous changes in methane release patterns in open spaces such as coal yards, transportation corridors, and washing areas. Satellite remote sensing monitoring is limited by resolution and influenced by multiple factors, making it difficult to meet the monitoring needs of post-coal mine methane emissions. Existing drone-based gas detection technology is mainly used in ground-based atmospheric environment monitoring and is typically designed for detecting high-concentration gas leaks or stationary pollution sources. However, post-coal mine methane emissions are characterized by low concentrations, long durations, uneven spatial distribution, and significant influence from wind fields, making existing technologies insufficient for rapid surveillance of post-coal mine methane emissions. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and electronic equipment for monitoring methane emissions from coal mine post-operation activities.

[0005] According to a first aspect of this disclosure, a method for monitoring methane emissions from post-mine activities in coal mines is provided, comprising: The inspection area is determined based on the post-coal mine activity process, and the drone inspection route is planned. The drone equipped with an organic methane detection module is controlled to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time. When an abnormal methane concentration area is detected, the drone is controlled to perform detection at different altitudes in the abnormal area to obtain the spatial distribution characteristics of the methane concentration. The methane concentration data is corrected based on the real-time wind field information of the survey area, and the methane emission area is identified based on the corrected concentration change pattern and spatial distribution characteristics.

[0006] Optionally, determining the survey area includes: Based on the washing, storage, transportation and transshipment processes involved in coal mining post-mining activities, the boundaries of the corresponding work areas for each process are determined, and the boundaries of the work areas are superimposed on the base map of the mining area geographic information to generate a vector layer of the survey area. Based on the vector layer of the survey area, and combined with the UAV's endurance and no-fly zone constraints, a survey route covering the survey area is planned. The survey route includes parallel routes and hovering sampling points.

[0007] Optionally, the planned survey route includes: Based on the work area boundary in the vector layer of the survey area, the survey area is divided into multiple survey sub-areas using a rasterization method. The size of each survey sub-area is determined according to the coverage range of a single UAV survey. Multiple parallel routes are planned according to the bow-shaped path, and hovering sampling points are set at the center of each survey sub-region to generate a survey route covering all survey sub-regions.

[0008] Optionally, the continuous survey includes: The drone is controlled to fly along a preset survey route, and the gas collection unit in the airborne methane detection module continuously collects the ambient gas in the survey area and delivers the collected ambient gas to the methane detection unit. The methane detection unit is used to detect the ambient gas in real time, obtain methane concentration data at each sampling point, and store the methane concentration data in association with the corresponding sampling point location information and sampling time information.

[0009] Optionally, the real-time detection of ambient gases using the methane detection unit includes: A laser beam of a specific wavelength is emitted by a laser emitting component, and the laser beam is reflected multiple times in a long optical path multiple reflection detection cell to form an enhanced absorption optical path. The gas absorption signal that has passed through the enhanced absorption optical path is photoelectrically converted and demodulated using a signal processing component to obtain methane concentration data in the ambient gas.

[0010] Optionally, obtaining the spatial distribution characteristics of methane concentration includes: When the methane concentration data exceeds the preset concentration threshold, the corresponding location is determined to be an abnormal methane concentration area, and the location information of the abnormal area and the corresponding methane concentration data are recorded. The drone is controlled to hover at multiple preset detection heights in the abnormal area in ascending order. At each preset detection height, ambient gas is continuously collected and corresponding methane concentration data is obtained to form a vertical methane concentration profile. The vertical methane concentration profile is used to characterize the variation of methane concentration with altitude.

[0011] Optionally, the step of correcting the methane concentration data based on the real-time wind field information of the survey area includes: The system acquires real-time wind speed and direction information within the survey area, which is obtained by airborne meteorological sensors and / or ground meteorological stations. Based on the real-time wind speed and wind direction information, determine the wind direction correction coefficient and wind speed attenuation coefficient at each sampling point; Based on the wind direction correction coefficient and wind speed attenuation coefficient, the methane concentration data is spatially interpolated to eliminate the influence of airflow diffusion on the concentration distribution, thus obtaining the corrected methane concentration data.

[0012] Optionally, the identification of methane emission areas includes: Based on the corrected methane concentration data, continuous spatial regions with methane concentrations higher than the preset emission identification threshold are extracted as candidate methane emission regions. Spatial cluster analysis was performed on the candidate methane emission areas to identify post-coal mine methane emission areas based on the spatial continuity and concentration gradient characteristics of methane concentration distribution.

[0013] According to a second aspect of this disclosure, a methane emission monitoring device for post-mine activities in coal mines is provided, comprising: The unit is used to determine the survey area based on the post-coal mine activity process and plan the drone survey route. The control unit is used to control the UAV equipped with an organic methane detection module to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time. The detection unit is used to control the UAV to perform detection at different altitudes in the abnormal area when an abnormal methane concentration is detected, so as to obtain the spatial distribution characteristics of the methane concentration. The correction unit is used to correct the methane concentration data based on the real-time wind field information of the survey area, and to identify the methane emission area based on the corrected concentration change pattern and spatial distribution characteristics.

[0014] Optionally, the determining unit is further configured to: Based on the washing, storage, transportation and transshipment processes involved in coal mining post-mining activities, the boundaries of the corresponding work areas for each process are determined, and the boundaries of the work areas are superimposed on the base map of the mining area geographic information to generate a vector layer of the survey area. Based on the vector layer of the survey area, and combined with the UAV's endurance and no-fly zone constraints, a survey route covering the survey area is planned. The survey route includes parallel routes and hovering sampling points.

[0015] Optionally, the determining unit is further configured to: Based on the work area boundary in the vector layer of the survey area, the survey area is divided into multiple survey sub-areas using a rasterization method. The size of each survey sub-area is determined according to the coverage range of a single UAV survey. Multiple parallel routes are planned according to the bow-shaped path, and hovering sampling points are set at the center of each survey sub-region to generate a survey route covering all survey sub-regions.

[0016] Optionally, the control unit is further configured to: The drone is controlled to fly along a preset survey route, and the gas collection unit in the airborne methane detection module continuously collects the ambient gas in the survey area and delivers the collected ambient gas to the methane detection unit. The methane detection unit is used to detect the ambient gas in real time, obtain methane concentration data at each sampling point, and store the methane concentration data in association with the corresponding sampling point location information and sampling time information.

[0017] Optionally, the control unit is further configured to: A laser beam of a specific wavelength is emitted by a laser emitting component, and the laser beam is reflected multiple times in a long optical path multiple reflection detection cell to form an enhanced absorption optical path. The gas absorption signal that has passed through the enhanced absorption optical path is photoelectrically converted and demodulated using a signal processing component to obtain methane concentration data in the ambient gas.

[0018] Optionally, the detection unit is further configured to: When the methane concentration data exceeds the preset concentration threshold, the corresponding location is determined to be an abnormal methane concentration area, and the location information of the abnormal area and the corresponding methane concentration data are recorded. The drone is controlled to hover at multiple preset detection heights in the abnormal area in ascending order. At each preset detection height, ambient gas is continuously collected and corresponding methane concentration data is obtained to form a vertical methane concentration profile. The vertical methane concentration profile is used to characterize the variation of methane concentration with altitude.

[0019] Optionally, the correction unit is further configured to: The system acquires real-time wind speed and direction information within the survey area, which is obtained by airborne meteorological sensors and / or ground meteorological stations. Based on the real-time wind speed and wind direction information, determine the wind direction correction coefficient and wind speed attenuation coefficient at each sampling point; Based on the wind direction correction coefficient and wind speed attenuation coefficient, the methane concentration data is spatially interpolated to eliminate the influence of airflow diffusion on the concentration distribution, thus obtaining the corrected methane concentration data.

[0020] Optionally, the correction unit is further configured to: Based on the corrected methane concentration data, continuous spatial regions with methane concentrations higher than the preset emission identification threshold are extracted as candidate methane emission regions. Spatial cluster analysis was performed on the candidate methane emission areas to identify post-coal mine methane emission areas based on the spatial continuity and concentration gradient characteristics of methane concentration distribution.

[0021] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0022] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0023] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0024] The method, apparatus, and electronic equipment for monitoring methane emissions from post-mine activities provided in this disclosure utilize a drone equipped with a methane detection module to conduct large-scale continuous monitoring along a planned route. When anomalies are detected, the three-dimensional spatial distribution of methane concentration is further obtained through multi-height detection, and the concentration data is corrected by combining real-time wind field information. This forms a complete emission area identification link from planar screening and vertical distribution characterization to wind field interference correction, overcoming the limitations of insufficient spatial coverage of fixed sites, low resolution of satellite remote sensing, and the inability of conventional drone detection to adapt to the low-concentration, non-uniform, and wind-affected characteristics of post-mine methane emissions. Therefore, it can solve the technical problems of existing monitoring technologies being unable to meet the needs of rapid monitoring of post-mine methane emissions and accurately identify emission areas, achieving the technical effect of rapid and accurate identification of post-mine coal methane emission areas.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0026] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 This is a schematic flowchart of a method for monitoring methane emissions from coal mine activities provided in an embodiment of this disclosure. Figure 2 This is a schematic diagram of the structure of a coal mine post-operation methane emission monitoring device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0027] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0028] The following description, with reference to the accompanying drawings, outlines a method, apparatus, and electronic equipment for monitoring methane emissions from coal mine activities according to embodiments of this disclosure.

[0029] Figure 1 This is a schematic flowchart of a method for monitoring methane emissions from coal mine activities, provided in an embodiment of this disclosure.

[0030] like Figure 1 As shown, the method includes the following steps: Step 101: Determine the inspection area based on the coal mine post-operation process and plan the drone inspection route; Before conducting a survey, the survey scope needs to be determined based on the types and spatial layout of post-mining activities within the target area. After coal is mined and brought to the surface, it undergoes multiple post-processing stages, which are typically distributed across different functional zones, thus forming several potential monitoring areas with different emission characteristics. Including these areas as a whole within the survey coverage area, based on the technological processes of post-mining activities and on-site conditions, ensures the spatial completeness and representativeness of subsequent monitoring data.

[0031] Based on this, and considering the geometry and area of ​​the survey area, as well as the UAV's endurance and flight parameters, a reasonable survey route is planned. The survey route should be designed to ensure that the flight path systematically covers the identified functional areas, while also taking into account factors such as flight altitude, waypoint spacing, and flight path direction. This will allow for the acquisition of spatially uniform and reasonably densely distributed environmental gas sampling data within a limited flight time, providing sufficient data support for subsequent methane concentration analysis and emission area identification.

[0032] Step 102: Control the drone equipped with an onboard methane detection module to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time. As the UAV flies along its predetermined survey route, its onboard methane detection module operates synchronously, continuously collecting and analyzing ambient gas data at various waypoints along the route. The gas collection unit continuously draws in ambient air from around the UAV during flight and directs it into the detection gas path of the methane detection unit. The methane detection unit then analyzes the imported gas sample online to obtain methane concentration data at the current location. During the data collection and detection process, the control unit coordinates the work of each unit according to a preset sampling frequency and detection sequence, ensuring that gas collection, concentration detection, and data recording are synchronized in time.

[0033] The acquired methane concentration data, along with the corresponding flight location information, is stored and transmitted back to the ground data processing terminal in real time or near real time via a wireless transmission unit. This allows for the gradual construction of a spatial distribution dataset of methane concentration covering the entire survey area during the survey process. This continuous survey method enables the system to acquire concentration information at multiple points and over multiple time periods along the flight trajectory in a single flight, laying a data foundation for subsequent anomaly area identification and emission characteristic analysis.

[0034] Step 103: When an abnormal methane concentration area is detected, control the UAV to perform detection at different altitudes in the abnormal area to obtain the spatial distribution characteristics of methane concentration. During continuous monitoring, when the system determines, based on real-time methane concentration data, that the concentration in a certain area is significantly higher than the background level or exceeds a preset threshold, an abnormal methane concentration area is identified. At this point, the control system automatically adjusts the UAV's flight plan, guiding it into the abnormal area and hovering or flying at low speed at multiple different altitudes to collect ambient gas data at each altitude and detect methane concentrations. By acquiring concentration data at multiple discrete altitudes in the vertical direction, the gradient variation of methane concentration along the altitude direction can be characterized, thus representing the diffusion and distribution characteristics of methane gas in three-dimensional space within that area.

[0035] The significance of this multi-height detection strategy lies in the fact that methane release sources in post-mining activity areas are typically located at or near the ground. During upward diffusion, the released methane is affected by atmospheric turbulence and its own buoyancy, resulting in a specific concentration decay pattern along the vertical direction. By acquiring concentration distribution information on the vertical profile, we can not only more accurately determine the source and diffusion range of abnormal concentrations, but also provide crucial spatial data support for subsequent source location and emission intensity estimation by combining wind field information.

[0036] Step 104: Correct the methane concentration data based on the real-time wind field information of the survey area, and identify the methane emission area based on the corrected concentration change pattern and spatial distribution characteristics.

[0037] In open environments, the diffusion of methane gas from its emission source to the detection point is significantly affected by the local wind speed and direction. This means the methane concentration collected at the detection point is not solely determined by the emission source intensity, but rather by the combined effects of airflow transport and turbulent diffusion. Therefore, directly relying on raw detection data to determine the location and extent of the emission area may lead to inaccuracies. The system simultaneously acquires real-time wind field information, including wind speed and direction data, during the monitoring process and uses this information as an environmental correction parameter to systematically correct the methane concentration data at each detection point.

[0038] The correction process aims to eliminate the interference of wind fields on methane diffusion paths and concentration distribution, restoring the concentration values ​​at each measuring point to the equivalent concentration levels under near-field conditions of the emission source, thus more accurately reflecting the spatial distribution pattern of methane emissions. Based on the wind-corrected concentration data, the variation patterns, spatial diffusion morphologies, and distribution characteristics of methane concentrations in each region are further analyzed. According to the directionality of the concentration gradient and spatial aggregation patterns, the boundaries and locations of concentrated methane emission areas are identified. This correction and identification process enables the system to accurately determine methane emission areas from post-mining activities under complex meteorological conditions, providing a reliable spatial location basis for subsequent emission accounting and reduction management.

[0039] In some embodiments, determining the survey area includes: Based on the washing, storage, transportation and transshipment processes involved in coal mining post-mining activities, the boundaries of the corresponding work areas for each process are determined, and the boundaries of the work areas are superimposed on the base map of the mining area geographic information to generate a vector layer of the survey area. Based on the vector layer of the survey area, and combined with the UAV's endurance and no-fly zone constraints, a survey route covering the survey area is planned. The survey route includes parallel routes and hovering sampling points.

[0040] The determination of the survey area is based on the various technological processes involved in coal mining post-operation. From the moment coal is brought to the surface until it is transported, it involves washing, storage, transportation, and transshipment. Each process occupies a different functional area within the mining area, and the scope and form of its operational area are constrained by factors such as site layout, equipment configuration, and technological processes. By defining the boundaries of the operational areas corresponding to each process, the spatial scope of each functional area is clarified. These defined boundaries are then overlaid onto the mining area's geographic information base map to form a survey area vector layer containing the spatial location and scope information of each functional area. This vector layer provides a unified spatial reference benchmark for subsequent route planning.

[0041] Based on the obtained vector map layer of the survey area, and considering the UAV's endurance parameters and no-fly zone constraints, flight routes covering the entire survey area are planned. The route design must comprehensively consider the geometry and area scale of the survey area, employing a combination of parallel routes and hovering sampling points. Parallel routes are evenly spaced along the main axis of the survey area to ensure sufficient lateral coverage density, enabling the UAV to perform a systematic strip-like scan of the survey area during flight. Hovering sampling points are located at critical operational positions or areas with complex spatial structures requiring denser sampling. The UAV hovers at these waypoints and performs fixed-point environmental gas sampling to obtain methane concentration data at these precise locations, thus balancing spatial coverage with sampling accuracy in key areas.

[0042] In some embodiments, the planned survey route includes: Based on the work area boundary in the vector layer of the survey area, the survey area is divided into multiple survey sub-areas using a rasterization method. The size of each survey sub-area is determined according to the coverage range of a single UAV survey. Multiple parallel routes are planned according to the bow-shaped path, and hovering sampling points are set at the center of each survey sub-region to generate a survey route covering all survey sub-regions.

[0043] The specific process of route planning begins with rasterizing the vector layer of the survey area. Based on the boundary range of each operational area in the vector layer, the entire survey area is divided into multiple regularly arranged raster units, each constituting an independent survey sub-region. The size of the raster unit is not arbitrarily selected, but determined according to the effective coverage range of the methane detection module carried by the UAV in a single flight. That is, the area of ​​each sub-region should match the spatial range in which the UAV can complete gas collection and concentration detection under single flight conditions, thereby ensuring that each survey sub-region can be completely covered in a single flight mission, avoiding data loss or flight interruption due to an excessively large sub-region area.

[0044] After completing the grid division, specific flight routes are planned for each survey sub-region. Parallel routes are laid out in a bow-shaped pattern, meaning that the flight directions of adjacent routes alternate in opposite directions, allowing the UAV to transition to the next reverse route with the shortest transition distance after completing one route. This bow-shaped routing method effectively reduces the total route length and the number of flight turns while ensuring the integrity of the survey coverage, thus reducing unnecessary endurance consumption. A hovering sampling point is set at the geometric center of each survey sub-region. After the UAV reaches this point, it hovers to perform fixed-point environmental gas sampling, obtaining the baseline data of methane concentration at the center of the sub-region. The bow-shaped routes of all sub-regions are then stitched together with the central hovering sampling point to generate a complete survey route covering all survey sub-regions.

[0045] In some embodiments, the continuous survey includes: The drone is controlled to fly along a preset survey route, and the gas collection unit in the airborne methane detection module continuously collects the ambient gas in the survey area and delivers the collected ambient gas to the methane detection unit. The methane detection unit is used to detect the ambient gas in real time, obtain methane concentration data at each sampling point, and store the methane concentration data in association with the corresponding sampling point location information and sampling time information.

[0046] During the drone's flight along the pre-set survey route, the onboard methane detection module mounted on the fuselage operates continuously. The gas sampling unit continuously draws ambient air from the drone's flight altitude through the air intake pipe and delivers the gas sample to the methane detection unit's detection gas path at a stable flow rate. The air intake of the air intake pipe is positioned at a location with minimal interference from the drone's rotor airflow to reduce disturbances to the sampled gas composition caused by the rotor downwash, ensuring that the collected gas accurately represents the true atmospheric composition at that location.

[0047] After the gas sample enters the methane detection unit, it undergoes optical detection via a long-path, multi-reflection detection cell. Inside the detection cell, a laser emitting component outputs a laser beam of a specific wavelength. This beam undergoes multiple reflections between the multi-reflector array within the cell before reaching the signal receiver, forming an effective absorption optical path far exceeding the physical length of the detection cell. Methane molecules in the gas sample selectively absorb the characteristic wavelength laser light within this optical path. The signal processing component calculates the methane concentration at the current sampling point based on the received light intensity attenuation signal and the Lambert-Beer law. This detection process continues at a preset sampling frequency during the UAV's flight, acquiring methane concentration data point-by-point along the flight path.

[0048] After each concentration detection, the system correlates the acquired methane concentration data with the current location information provided by the UAV flight control system and the sampling timestamp recorded by the onboard clock, forming a structured data set containing the concentration value, three-dimensional position coordinates, and sampling time, which is then stored in the onboard storage module. This spatiotemporal correlated storage method enables subsequent data analysis to accurately trace the spatial location and acquisition sequence corresponding to each concentration data point, providing a reliable data foundation for concentration spatial distribution modeling and wind field correction.

[0049] In some embodiments, the real-time detection of ambient gases using a methane detection unit includes: A laser beam of a specific wavelength is emitted by a laser emitting component, and the laser beam is reflected multiple times in a long optical path multiple reflection detection cell to form an enhanced absorption optical path. The gas absorption signal that has passed through the enhanced absorption optical path is photoelectrically converted and demodulated using a signal processing component to obtain methane concentration data in the ambient gas.

[0050] The core detection process of the methane detection unit is based on tunable semiconductor laser absorption spectroscopy technology. The semiconductor laser in the laser emission assembly outputs a tunable laser beam, the center wavelength of which is precisely aligned with the characteristic absorption line of the methane molecule in the near-infrared band. The laser drive circuit applies low-frequency sawtooth wave modulation to the injection current of the laser, causing the output laser wavelength to periodically scan near the characteristic absorption line, thereby covering the complete absorption profile of the methane molecule.

[0051] After the laser beam enters the long-path, multi-reflection detection cell, it undergoes multiple reflections between concave mirror groups positioned at both ends of the cell. The curvature radius and spacing of the mirrors are precisely designed so that the laser spot positions on the mirror surfaces shift sequentially according to a preset pattern without overlapping, ensuring that each reflection utilizes the effective reflective area of ​​the mirror surface. After dozens of reflections, the laser beam finally exits the detection cell and reaches the photodetector. The actual absorption optical path through the gas sample far exceeds the physical cavity length of the detection cell, reaching several meters or even tens of meters. This significant increase in optical path greatly enhances the total absorption effect of low-concentration methane molecules on the laser, thus improving the system's response sensitivity to ppm-level concentration changes.

[0052] The signal processing component performs transimpedance amplification, analog-to-digital conversion, and digital demodulation on the electrical signal output from the photodetector. The demodulation process employs a second harmonic detection method to extract the second harmonic component proportional to the methane concentration from the modulated absorption signal, effectively suppressing baseline drift and low-frequency noise interference. Finally, based on the established correspondence between the harmonic signal amplitude and the methane concentration, the methane concentration at the current sampling point is calculated.

[0053] In some embodiments, obtaining the spatial distribution characteristics of methane concentration includes: When the methane concentration data exceeds the preset concentration threshold, the corresponding location is determined to be an abnormal methane concentration area, and the location information of the abnormal area and the corresponding methane concentration data are recorded. The drone is controlled to hover at multiple preset detection heights in the abnormal area in ascending order. At each preset detection height, ambient gas is continuously collected and corresponding methane concentration data is obtained to form a vertical methane concentration profile. The vertical methane concentration profile is used to characterize the variation of methane concentration with altitude.

[0054] When processing the methane concentration data transmitted back from continuous monitoring, the system compares the measured concentration values ​​at each sampling point with a preset concentration threshold point by point. This concentration threshold is set by comprehensively considering the background methane concentration level in the ambient atmosphere of the monitoring area and the typical concentration range of methane emissions from post-mining activities. When the methane concentration data at a certain sampling point exceeds this threshold, the system identifies the location of that sampling point as an abnormal methane concentration area, automatically records the three-dimensional coordinates of the abnormal area and the corresponding methane concentration value, and triggers a special detection program for the abnormal area.

[0055] After the specialized detection procedure is initiated, the UAV adjusts from its current flight altitude to the anomaly area and hovers sequentially at multiple preset detection altitudes in ascending order. Each preset detection altitude covers a vertical range from near-ground level to the UAV's safe flight limit, with the spacing between adjacent altitudes determined based on the spatial scale of the anomaly area and the expected methane diffusion characteristics. The UAV hovers at each preset detection altitude, and the gas sampling unit continuously collects ambient gas data at that altitude and transmits it to the methane detection unit for concentration detection, obtaining methane concentration data for that altitude layer. After completing detection at all preset altitudes, the methane concentration data at each altitude are arranged in ascending order to form a vertical profile of methane concentration in the anomaly area. This vertical profile visually reflects the change in methane concentration with increasing altitude; the decay rate and morphological characteristics of the concentration gradient are closely related to the location, release intensity, and atmospheric diffusion conditions of the methane release source, providing crucial vertical dimensional information for determining the location of the emission source and estimating the emission flux.

[0056] In some embodiments, correcting the methane concentration data based on real-time wind field information of the survey area includes: The system acquires real-time wind speed and direction information within the survey area, which is obtained by airborne meteorological sensors and / or ground meteorological stations. Based on the real-time wind speed and wind direction information, determine the wind direction correction coefficient and wind speed attenuation coefficient at each sampling point; Based on the wind direction correction coefficient and wind speed attenuation coefficient, the methane concentration data is spatially interpolated to eliminate the influence of airflow diffusion on the concentration distribution, thus obtaining the corrected methane concentration data.

[0057] The wind field correction process is based on real-time wind speed and direction data. Wind field information within the survey area is collected through two methods: first, miniature meteorological sensors mounted on the UAV can measure instantaneous wind speed and direction at the UAV's location in real time during flight; second, ground-based meteorological stations deployed around the survey area record average wind speed and direction data at the ground level at fixed time intervals. These two methods can be used independently or networked together to obtain more complete wind field information covering the entire survey area.

[0058] After acquiring wind field data, wind direction correction coefficients and wind speed attenuation coefficients were calculated for each sampling point. The wind direction correction coefficient reflects the angle between the prevailing wind direction at the sampling point and the diffusion direction of methane from the release source to the sampling point. When the sampling point is downwind of the release source, the correction coefficient approaches 1, and when it is crosswind or upwind, the correction coefficient decreases accordingly, thus characterizing the directional influence of airflow transport on the spatial distribution of methane. The wind speed attenuation coefficient is related to the local wind speed. The higher the wind speed, the farther methane is transported horizontally, and the concentration in the near-source region decreases due to dilution. This coefficient is used to quantify the concentration attenuation effect caused by this wind speed.

[0059] Substituting the two coefficients mentioned above into the spatial interpolation correction model, the original methane concentration data at each sampling point is corrected point by point. The core idea of ​​the correction process is to reversely restore the actual concentration distribution after wind disturbance to the equivalent concentration distribution under windless or uniform diffusion conditions, thereby eliminating the interference of gas transport and turbulent diffusion on the spatial pattern of concentration. The corrected methane concentration data can more realistically reflect the intensity distribution of the release source, making the emission area determination results based on concentration gradient and spatial accumulation characteristics more accurate.

[0060] In some embodiments, identifying methane emission zones includes: Based on the corrected methane concentration data, continuous spatial regions with methane concentrations higher than the preset emission identification threshold are extracted as candidate methane emission regions. Spatial cluster analysis was performed on the candidate methane emission areas to identify post-coal mine methane emission areas based on the spatial continuity and concentration gradient characteristics of methane concentration distribution.

[0061] The process of identifying emission areas begins with methane concentration data corrected for wind field variations. The system performs threshold determination on a pixel-by-pixel basis, marking spatial locations where methane concentrations exceed a preset emission identification threshold as valid emission signal points. This emission identification threshold must be set higher than the environmental background concentration level of the monitored area to eliminate interference from natural background fluctuations. Spatially adjacent or continuously distributed valid emission signal points are then grouped into several candidate methane emission areas. These candidate areas spatially appear as continuous patches of a certain area and shape, covering the spatial range where methane release from post-mining activities may occur.

[0062] Spatial clustering analysis was further conducted on the extracted candidate methane emission regions. The clustering process comprehensively considered the spatial continuity and concentration gradient characteristics of methane concentration distribution within each candidate region. Spatial continuity reflects the degree of contiguousness of high-concentration areas in geographic space; stronger continuity indicates a more concentrated distribution of methane emission sources within the region. Concentration gradient characteristics describe the decreasing pattern of concentration values ​​from the center to the edge of the region; different types of methane emission sources exhibit differences in concentration gradient decay rates and spatial morphology. By using spatial continuity and concentration gradient characteristics as input parameters for clustering analysis, each candidate region was classified and its boundaries optimized. Ultimately, emission regions with a clear correspondence to methane emissions from coal mine post-activities were identified, and the spatial boundaries and location information of each emission region were output.

[0063] Corresponding to the aforementioned method for monitoring methane emissions from coal mine activities, this invention also proposes a device for monitoring methane emissions from coal mine activities. Since the device embodiments of this invention correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to in the method embodiments, and will not be repeated here.

[0064] Figure 2 This is a schematic diagram of the structure of a coal mine post-construction methane emission monitoring device provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: Unit 21 is used to determine the survey area based on the coal mine post-operation process and plan the drone survey route. Control unit 22 is used to control the UAV equipped with an organic methane detection module to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time; The detection unit 23 is used to control the UAV to perform detection at different heights in the abnormal area when an abnormal methane concentration area is detected, so as to obtain the spatial distribution characteristics of methane concentration. The correction unit 24 is used to correct the methane concentration data based on the real-time wind field information of the survey area, and to identify the methane emission area based on the corrected concentration change pattern and spatial distribution characteristics.

[0065] Furthermore, in one possible implementation of this disclosure, the determining unit 21 is further configured to: Based on the washing, storage, transportation and transshipment processes involved in coal mining post-mining activities, the boundaries of the corresponding work areas for each process are determined, and the boundaries of the work areas are superimposed on the base map of the mining area geographic information to generate a vector layer of the survey area. Based on the vector layer of the survey area, and combined with the UAV's endurance and no-fly zone constraints, a survey route covering the survey area is planned. The survey route includes parallel routes and hovering sampling points.

[0066] Furthermore, in one possible implementation of this disclosure, the determining unit 21 is further configured to: Based on the work area boundary in the vector layer of the survey area, the survey area is divided into multiple survey sub-areas using a rasterization method. The size of each survey sub-area is determined according to the coverage range of a single UAV survey. Multiple parallel routes are planned according to the bow-shaped path, and hovering sampling points are set at the center of each survey sub-region to generate a survey route covering all survey sub-regions.

[0067] Furthermore, in one possible implementation of this disclosure, the control unit 22 is further configured to: The drone is controlled to fly along a preset survey route, and the gas collection unit in the airborne methane detection module continuously collects the ambient gas in the survey area and delivers the collected ambient gas to the methane detection unit. The methane detection unit is used to detect the ambient gas in real time, obtain methane concentration data at each sampling point, and store the methane concentration data in association with the corresponding sampling point location information and sampling time information.

[0068] Furthermore, in one possible implementation of this disclosure, the control unit 22 is further configured to: A laser beam of a specific wavelength is emitted by a laser emitting component, and the laser beam is reflected multiple times in a long optical path multiple reflection detection cell to form an enhanced absorption optical path. The gas absorption signal that has passed through the enhanced absorption optical path is photoelectrically converted and demodulated using a signal processing component to obtain methane concentration data in the ambient gas.

[0069] Furthermore, in one possible implementation of this disclosure, the detection unit 23 is further configured to: When the methane concentration data exceeds the preset concentration threshold, the corresponding location is determined to be an abnormal methane concentration area, and the location information of the abnormal area and the corresponding methane concentration data are recorded. The drone is controlled to hover at multiple preset detection heights in the abnormal area in ascending order. At each preset detection height, ambient gas is continuously collected and corresponding methane concentration data is obtained to form a vertical methane concentration profile. The vertical methane concentration profile is used to characterize the variation of methane concentration with altitude.

[0070] Furthermore, in one possible implementation of this disclosure, the correction unit 23 is further configured to: The system acquires real-time wind speed and direction information within the survey area, which is obtained by airborne meteorological sensors and / or ground meteorological stations. Based on the real-time wind speed and wind direction information, determine the wind direction correction coefficient and wind speed attenuation coefficient at each sampling point; Based on the wind direction correction coefficient and wind speed attenuation coefficient, the methane concentration data is spatially interpolated to eliminate the influence of airflow diffusion on the concentration distribution, thus obtaining the corrected methane concentration data.

[0071] Furthermore, in one possible implementation of this disclosure, the correction unit 24 is further configured to: Based on the corrected methane concentration data, continuous spatial regions with methane concentrations higher than the preset emission identification threshold are extracted as candidate methane emission regions. Spatial cluster analysis was performed on the candidate methane emission areas to identify post-coal mine methane emission areas based on the spatial continuity and concentration gradient characteristics of methane concentration distribution.

[0072] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0073] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0074] Figure 3A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0075] like Figure 3 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0076] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0077] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the coal mine post-active methane emission survey method. For example, in some embodiments, the coal mine post-active methane emission survey method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned coal mine post-activity methane emission monitoring method by any other suitable means (e.g., by means of firmware).

[0078] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0079] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0080] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0081] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0082] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0083] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0084] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0085] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0086] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for monitoring methane emissions from coal mine post-construction activities, characterized in that, include: The inspection area is determined based on the post-coal mine activity process, and the drone inspection route is planned. The drone equipped with an organic methane detection module is controlled to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time. When an abnormal methane concentration area is detected, the drone is controlled to perform detection at different altitudes in the abnormal area to obtain the spatial distribution characteristics of the methane concentration. The methane concentration data is corrected based on the real-time wind field information of the survey area, and the methane emission area is identified based on the corrected concentration change pattern and spatial distribution characteristics.

2. The method according to claim 1, characterized in that, The determined survey area includes: Based on the washing, storage, transportation and transshipment processes involved in coal mining post-mining activities, the boundaries of the corresponding work areas for each process are determined, and the boundaries of the work areas are superimposed on the base map of the mining area geographic information to generate a vector layer of the survey area. Based on the vector layer of the survey area, and combined with the UAV's endurance and no-fly zone constraints, a survey route covering the survey area is planned. The survey route includes parallel routes and hovering sampling points.

3. The method according to claim 2, characterized in that, The planned survey route includes: Based on the work area boundary in the vector layer of the survey area, the survey area is divided into multiple survey sub-areas using a rasterization method. The size of each survey sub-area is determined according to the coverage range of a single UAV survey. Multiple parallel routes are planned according to the bow-shaped path, and hovering sampling points are set at the center of each survey sub-region to generate a survey route covering all survey sub-regions.

4. The method according to claim 3, characterized in that, The continuous survey includes: The drone is controlled to fly along a preset survey route, and the gas collection unit in the airborne methane detection module continuously collects the ambient gas in the survey area and delivers the collected ambient gas to the methane detection unit. The methane detection unit is used to detect the ambient gas in real time, obtain methane concentration data at each sampling point, and store the methane concentration data in association with the corresponding sampling point location information and sampling time information.

5. The method according to claim 4, characterized in that, The real-time detection of ambient gases using a methane detection unit includes: A laser beam of a specific wavelength is emitted by a laser emitting component, and the laser beam is reflected multiple times in a long optical path multiple reflection detection cell to form an enhanced absorption optical path. The gas absorption signal that has passed through the enhanced absorption optical path is photoelectrically converted and demodulated using a signal processing component to obtain methane concentration data in the ambient gas.

6. The method according to claim 1, characterized in that, The spatial distribution characteristics of methane concentration obtained include: When the methane concentration data exceeds the preset concentration threshold, the corresponding location is determined to be an abnormal methane concentration area, and the location information of the abnormal area and the corresponding methane concentration data are recorded. The drone is controlled to hover at multiple preset detection heights in the abnormal area in ascending order. At each preset detection height, ambient gas is continuously collected and corresponding methane concentration data is obtained to form a vertical methane concentration profile. The vertical methane concentration profile is used to characterize the variation of methane concentration with altitude.

7. The method according to claim 1, characterized in that, The step of correcting the methane concentration data based on real-time wind field information in the survey area includes: The system acquires real-time wind speed and direction information within the survey area, which is obtained by airborne meteorological sensors and / or ground meteorological stations. Based on the real-time wind speed and wind direction information, determine the wind direction correction coefficient and wind speed attenuation coefficient at each sampling point; Based on the wind direction correction coefficient and wind speed attenuation coefficient, the methane concentration data is spatially interpolated to eliminate the influence of airflow diffusion on the concentration distribution, thus obtaining the corrected methane concentration data.

8. The method according to claim 1, characterized in that, The identified methane emission areas include: Based on the corrected methane concentration data, continuous spatial regions with methane concentrations higher than the preset emission identification threshold are extracted as candidate methane emission regions. Spatial cluster analysis was performed on the candidate methane emission areas to identify post-coal mine methane emission areas based on the spatial continuity and concentration gradient characteristics of methane concentration distribution.

9. A coal mine post-operation methane emission monitoring device, characterized in that, include: The unit is used to determine the survey area based on the post-coal mine activity process and plan the drone survey route. The control unit is used to control the UAV equipped with an onboard methane detection module to continuously patrol the patrol area along the patrol route, collect ambient gas data and obtain methane concentration data in real time. The detection unit is used to control the UAV to perform detection at different altitudes in the abnormal area when an abnormal methane concentration is detected, so as to obtain the spatial distribution characteristics of the methane concentration. The correction unit is used to correct the methane concentration data based on the real-time wind field information of the survey area, and to identify the methane emission area based on the corrected concentration change pattern and spatial distribution characteristics.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

Images