Mine production process monitoring management system and method based on digital twinning

Abstract

This invention discloses a mine production process monitoring and management system and method based on digital twins, belonging to the field of monitoring and management technology. It includes: a geometric matching module for obtaining matching results based on the geometric information of an underground centralized transfer station; a dust cluster identification module for comparing the dust quality of all internal dust areas in the underground centralized transfer station based on the matching results to obtain the main dust cluster area; a gap screening module for screening gap areas adjacent to the main dust cluster area to obtain the main injection gap; a process dust module for obtaining process dust indicators based on the main dust cluster area and the main injection gap; and a process monitoring module for obtaining production process monitoring results based on the process dust indicators. This invention improves the accuracy and stability of mine production process monitoring and management.

Description

Technical Field

[0001] This invention relates to the field of monitoring and management technology, and in particular to a monitoring and management system for mine production processes based on digital twins. Background Technology

[0002] In underground coal mine production, the centralized transfer station is a crucial node connecting the mining face with the subsequent conveying system, undertaking the task of transferring coal from upstream equipment to downstream conveying equipment. This working area typically includes structures such as chutes, guide skirts, conveyor belts, and enclosed hoods, inevitably generating a large amount of dust during the coal unloading, transfer, and conveying process.

[0003] With the improvement of the level of intelligence and informatization in mines, dust sensors are widely deployed in transfer stations and their surrounding areas for real-time monitoring of dust concentration. At the same time, digital twin technology is gradually being applied to mine production management, realizing the visualization monitoring and analysis of production process status by constructing a virtual mapping of underground equipment and working environment. Due to the complex internal structure, spatial enclosure and connectivity of transfer stations, the distribution of dust in space is obviously non-uniform, especially in local structural locations where dust is easily concentrated and discharged, resulting in strong spatial differences in dust monitoring data.

[0004] Under current technological conditions, mine production process monitoring usually focuses on the overall analysis of dust concentration or total dust volume. When an abnormal increase in dust reading occurs at a certain location in a transfer station, it is difficult to distinguish whether the abnormality is caused by changes in the production process itself or by dust leakage caused by changes in the sealing condition of a local structure. This can easily lead to the misjudgment of concentrated local dust discharge as a production process abnormality, thereby triggering unnecessary production control measures and affecting mine production efficiency and management accuracy. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies that trigger unnecessary production control measures, and to propose a mine production process monitoring and management system and method based on digital twins.

[0006] To address the problems existing in the prior art, the present invention adopts the following technical solution: A digital twin-based mine production process monitoring and management system includes: The geometric matching module is used to obtain matching results based on the geometric information of the underground centralized transfer station; The dust cluster identification module is used to compare the dust quality of all internal dust areas in the underground centralized transfer station based on the matching results, and to obtain the main area of ​​the dust cluster. The gap screening module is used to screen the gap areas adjacent to the main area of ​​the dust cluster to obtain the main jet gap; The process dust module is used to obtain process dust indicators based on the main area of ​​dust clusters and the main injection gap. The process monitoring module is used to obtain production process monitoring results based on process dust indicators.

[0007] Preferably, the specific steps to obtain the matching results are as follows: In the digital twin system of the mine, the geometric information of the underground centralized transfer station is acquired; the geometric information includes the three-dimensional spatial position data of the chute, guide skirt, conveyor belt and enclosure. Based on geometric information, the underground centralized transfer station is divided into an inner dust zone, a crevice zone, and an outer dust zone; Obtain the installation locations of each dust sensor at the underground centralized transfer station; The installation positions of each dust sensor are matched with the spatial positions of the inner dust area, the gap area, and the outer dust area to obtain the matching results.

[0008] Preferably, the specific steps for dividing the inner dust area, the gap area, and the outer dust area are as follows: Based on the three-dimensional spatial location data of the chute, the first spatial region located inside the chute is determined; The first spatial region is designated as the inner cavity dust zone; The gap area between the guide skirt and the conveyor belt is defined as the gap area. Based on the three-dimensional spatial location data of the chute and the enclosure, a second spatial region located outside the chute and connected to the mine roadway space is determined. The second space region is designated as the external dust region.

[0009] Preferably, the specific steps for obtaining the main region of the dust cluster are as follows: Based on the matching results, determine the total number of first sensors of the dust sensors corresponding to the dust area in the inner cavity; Based on the matching results, determine the first dust concentration of the dust sensor corresponding to the dust area in the inner cavity; The average dust concentration in the inner cavity dust area is determined based on the total number of first sensors and the first dust concentration. Multiply the average dust concentration by the volume of the inner dust zone to obtain the dust mass of the inner dust zone. The inner cavity dust area corresponding to the largest quantity of dust is taken as the main area of ​​the dust cluster.

[0010] Preferably, the specific steps for obtaining the main injection slot are as follows: Based on the spatial location of the main region of the dust cluster, the gap regions adjacent to the main region of the dust cluster are determined and defined as candidate gap regions; Based on the spatial adjacency relationship in the digital twin system, the external dust region connected to the candidate gap region is determined and defined as the candidate external dust region; Multiply the average dust concentration of the candidate external dust area by the volume of the candidate external dust area to obtain the dust mass of the candidate external dust area. Divide the dust mass of the candidate external dust area by the dust mass of the main dust cluster area to obtain the jet correlation ratio; select the candidate gap area with the largest jet correlation ratio as the main jet gap.

[0011] Preferably, the specific steps for obtaining the process dust index are as follows: Based on the main dust cluster area and the external dust area connected to the main jet gap, the structural dust leakage area is determined; the process dust area is determined based on the structural dust leakage area. Based on the matching results, determine the dust quality in the process dust area; The total dust mass is obtained by summing the dust masses in all process dust areas. Obtain the coal transport volume of the underground centralized transfer station; Divide the dust mass by the coal transport volume to obtain the process dust index.

[0012] Preferably, the process dust area is determined based on the structural dust leakage area, including: Remove the internal dust areas from the structural dust leakage areas from all internal dust areas to obtain the process internal dust area set; Remove the external dust areas from the structural dust leakage areas from all external dust areas to obtain the process external dust area set; The dust areas in the process are determined based on the set of dust areas inside the process cavity and the set of dust areas outside the process.

[0013] Preferably, the specific steps for obtaining production process monitoring results are as follows: Set threshold ranges for indicators based on historical production data from the mine; Define threshold comparison rules; Input the process dust index into the process monitoring unit of the digital twin system; The process monitoring unit performs threshold comparison on the process dust index according to the threshold comparison rules to obtain the production process monitoring results.

[0014] To address the aforementioned problems, this invention also provides a method for monitoring and managing mining production processes based on digital twins, the method comprising: The matching results are obtained based on the geometric information of the underground centralized transfer station; Based on the matching results, the dust quality of all internal dust zones in the underground centralized transfer station is compared to obtain the main area of ​​dust clusters. The gap regions adjacent to the main area of ​​the dust cluster are screened to obtain the main jet gaps; Process dust indicators are obtained based on the main area of ​​dust clusters and the main jet gaps. Production process monitoring results are obtained based on process dust indicators.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention introduces geometric information of the underground centralized transfer station into the digital twin system, subdividing the transfer station space into an inner dust zone, a gap zone, and an outer dust zone, and establishing a correspondence between dust sensors and each spatial region. This gives the dust monitoring data a clear spatial basis. By comparing the dust quality in the inner dust zone, the main area of ​​highly concentrated dust clusters is identified. Combined with spatial adjacency relationships, the main jet gap is selected, and the dust concentration and discharge path is depicted from the spatial structure level. This allows dust anomalies to be accurately mapped to specific structural locations, effectively improving the spatial interpretability of dust monitoring results.

[0016] 2. This invention constructs a structural dust leakage area based on the main dust cluster area and the main injection gap, and then eliminates the influence of structural dust leakage on dust data to determine the process dust area directly related to the production process. This achieves an effective distinction between structural dust leakage and production process dust, and avoids interference with the overall dust monitoring results caused by the concentrated discharge of dust due to local structural gaps. This makes the dust data in the process dust area more accurately reflect the dust situation generated during coal transfer and transportation.

[0017] 3. This invention constructs a process dust index by correlating the total dust volume in the process dust area with the coal transport volume of the underground centralized transfer station. This makes the dust monitoring results correspond to the production scale and maintain good comparability even under changes in production load. By setting the threshold range of the index in combination with historical production data and comparing the thresholds, the operating status of the production process can be accurately judged. This avoids misjudging local anomalies caused by centralized dust discharge as production process anomalies, thereby reducing unnecessary production control operations and improving the accuracy and stability of mine production process monitoring and management. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating a mining production process monitoring and management method based on digital twins, as provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] This embodiment provides a mine production process monitoring and management system based on digital twins, specifically including: a geometric matching module, used to obtain matching results based on the geometric information of the underground centralized transfer station; In an embodiment of the present invention, the specific steps for obtaining the matching result are as follows: In the digital twin system of the mine, the geometric information of the underground centralized transfer station is acquired; the geometric information includes the three-dimensional spatial position data of the chute, guide skirt, conveyor belt and enclosure. An underground centralized transfer station is an operational area located underground in a mine, used to transfer coal between different conveying equipment. It includes chutes to guide the coal flow, guide skirts to limit the overflow of coal flow, conveyor belts to carry and transport coal, and a closed cover to enclose the transfer area. The geometric information refers to the three-dimensional spatial position data of the above-mentioned physical structures in the underground space of the mine. This three-dimensional spatial position data reflects the relative positional relationship and spatial boundaries of each physical structure in space, and is used to describe the spatial morphology inside and around the transfer station.

[0021] A chute is a channel structure located in an underground centralized transfer station, used to guide coal or other bulk materials from upstream conveying equipment to downstream conveying equipment, forming a relatively enclosed material flow space inside. Guide skirts are plate-like structures located at the chute outlet and on both sides of the conveyor belt loading area, used to limit material overflow to both sides of the conveyor belt during unloading and loading. The conveyor belt is a strip-shaped conveying component arranged in the underground roadway, used to carry and continuously transport coal, achieving material transport along a predetermined direction through a drive device. A hood is an enclosed structure located around the chute and guide skirts, used to enclose the transfer area, thereby forming a closed space isolated from the roadway space.

[0022] In the digital twin system of the mine, the built-in spatial data acquisition function is first activated. A data interaction link is established with the mine's underground 3D geographic information system, accessing the original spatial data of the underground centralized transfer station's physical structure acquired by 3D laser scanning equipment. This original spatial data includes the spatial location information of various physical structures such as the chute, guide skirt, conveyor belt, and enclosure. Then, using the coordinate calibration module in the digital twin system, based on the unified spatial coordinate system of the mine, coordinate transformation and deviation correction are performed on the acquired original spatial data to eliminate spatial position offsets caused by equipment measurement errors and environmental interference. Finally, the data is processed through the system... The 3D modeling engine performs structured processing on the calibrated spatial data, extracting the spatial distribution relationship and boundary range parameters of the contour features, dimensions, and structures of each entity. This generates 3D spatial position data for the chute, the guide skirt, the conveyor belt, and the enclosure. Finally, the system's data verification module checks the completeness and consistency of the generated 3D spatial position data to ensure that the 3D spatial position data of each entity accurately reflects its actual installation position and relative spatial relationship in the underground centralized transfer station, thus completing the acquisition of geometric information for the underground centralized transfer station.

[0023] A mine digital twin system is a virtual digital system built on digital twin technology that precisely maps all elements of the mine. Based on the geometric information, attribute parameters, and operational data of physical entities such as underground geological conditions, roadway layout, production equipment, and production processes, it constructs a virtual mapping model of the entire mine, including key production nodes such as underground centralized transfer stations, using 3D modeling technology. It integrates real-time data collected by various sensing devices such as dust sensors and belt conveyor monitoring equipment, and combines spatial analysis, data processing, and simulation technologies to achieve dynamic perception, real-time monitoring, data interaction, and simulation analysis of the mine's production environment, equipment operating status, and production process progress. It can accurately reproduce the spatial morphology, relative positional relationships, and operational patterns of the mine's physical entities, providing digital, visual, and intelligent technical support for mine production process monitoring and management, risk warning, and decision optimization, thus helping mines achieve safe, efficient, intelligent, and precise production operations.

[0024] Based on geometric information, the underground centralized transfer station is divided into an inner dust zone, a crevice zone, and an outer dust zone; In an embodiment of the present invention, the specific steps for dividing the inner dust area, the gap area, and the outer dust area are as follows: Based on the three-dimensional spatial location data of the chute, the first spatial region located inside the chute is determined; The three-dimensional spatial location data of the chute refers to the shape range, spatial boundary, and relative positional relationship of the chute with the surrounding structures in the underground space of the mine. The spatial range enclosed inside the chute can be determined through this three-dimensional spatial location data. The first spatial region refers to the space that is completely located inside the chute and is defined by the chute structure itself. This space is used for coal falling and flowing during the transfer operation, and it is also the main spatial region where dust is first generated and accumulated.

[0025] In the digital twin system of the mine, the three-dimensional spatial location data of the chute is first processed in depth to extract the inner wall contour feature points, spatial boundary coordinates and structural morphology parameters of the chute. Based on these data, a complete three-dimensional solid model of the chute is constructed. Then, using the spatial region determination algorithm built into the system, with the inner wall boundary of the chute's three-dimensional solid model as a constraint, all spatial points within the corresponding spatial range in the mine are traversed. All continuous spatial point sets that are completely enclosed by the inner wall of the chute and do not exceed the spatial boundary of the chute are selected. The spatial topology of this point set is reconstructed to form a closed spatial region. This closed spatial region is the first spatial region located inside the chute. Throughout the process, multiple rounds of spatial point verification and boundary consistency verification are conducted to ensure that the determined first spatial region completely matches the actual internal space of the chute and can accurately reflect the real spatial range inside the chute used for coal falling, flowing and dust generation and accumulation.

[0026] The first spatial region is designated as the inner cavity dust zone; The first spatial region is designated as the inner cavity dust zone to characterize the presence and distribution of dust in the air space inside the chute. This inner cavity dust zone corresponds to the relatively enclosed spatial environment inside the transfer station.

[0027] The gap area between the guide skirt and the conveyor belt is defined as the gap area. The gap area between the guide skirt and the conveyor belt refers to the narrow space formed between the edge of the guide skirt and the surface of the conveyor belt during transfer operations. This space is structurally designed to accommodate belt operation, but it may also become a channel for dust to leak outwards. This gap area is referred to as the slit area to characterize the path of dust migration from the inner cavity space to the outer space.

[0028] It should be noted that the gap area between the guide skirt and the conveyor belt is an objectively existing narrow space during the transfer operation. This space is used to ensure the normal operation of the conveyor belt and the structural installation of the guide skirt. However, during the material dropping and conveying process, dust generated inside the chute can easily escape to the external space through this gap area under the action of airflow and material movement. The gap area between the guide skirt and the conveyor belt is regarded as the gap area in order to clearly delineate the main channel for dust leakage from the inner cavity of the chute to the external aisle space. This allows for the identification of dust leakage paths and the differentiation between dust leakage caused by structural gaps and dust distribution generated by the production process itself in subsequent analysis.

[0029] Based on the three-dimensional spatial location data of the chute and the enclosure, a second spatial region located outside the chute and connected to the mine roadway space is determined. The second space region is designated as the external dust region.

[0030] The second space area refers to the air space located outside the chute, which is not completely isolated by the enclosure and is connected to the underground mine roadway space. Under the action of mine ventilation, this space is connected to the air inside the roadway. The second space area is used as the external dust area to characterize the diffusion and distribution of dust in the external roadway space of the transfer station.

[0031] Specifically, in the digital twin system of the mine, the three-dimensional spatial location data of the chute and the enclosure are processed synchronously to accurately extract the coordinates of the outer wall spatial boundary of the chute, the overall contour range parameters of the enclosure, and the relative spatial relationship between the two. Based on this data, a joint three-dimensional spatial model of the chute and the enclosure is constructed. Then, using the system's built-in spatial region division algorithm, all spatial points outside the chute are selected using the outer wall boundary of the chute as the first defining condition. Next, using the contour range of the enclosure as the second defining condition, points completely enclosed by the enclosure and without a connecting path to the roadway are removed from the spatial points outside the chute, while points not enclosed are retained. The spatial points that are completely isolated by the enclosure are then verified by a spatial connectivity detection algorithm. The spatial links between the retained spatial points and the three-dimensional model of the underground mine roadway space are verified, and a set of continuous spatial points that can form a direct connection with the roadway space is selected. The spatial topology of this set of points is reconstructed and the boundary is optimized to form a complete closed spatial range. This closed spatial range is the second spatial area located outside the chute and connected to the mine roadway space. Throughout the process, multiple rounds of spatial boundary verification and connectivity verification are conducted to ensure that the determined second spatial area can accurately reflect the real air space range connected to the outside of the chute and the roadway space.

[0032] Obtain the installation locations of each dust sensor at the underground centralized transfer station; Dust sensors are monitoring devices installed at different locations in underground centralized transfer stations to detect the concentration of dust in the air. The installation location refers to the actual fixed position of the dust sensor in the underground space.

[0033] The installation positions of each dust sensor are matched with the spatial positions of the inner dust area, the gap area, and the outer dust area to obtain the matching results.

[0034] Matching the installation location of dust sensors with the spatial locations of the internal dust area, gap area, and external dust area refers to determining which area of ​​the internal dust area, gap area, or external dust area each dust sensor is located in based on the three-dimensional spatial positional relationship, thereby establishing a correspondence between the dust sensor and the corresponding spatial area. The matching results are used to characterize the distribution of dust concentration in different spatial areas, providing basic data support for subsequent identification of the main area of ​​dust clusters and analysis of the path of dust migration from the internal cavity to the external space.

[0035] First, the precise spatial coordinates of each dust sensor, the three-dimensional spatial boundary range of the inner dust zone, the elongated spatial contour parameters of the gap zone, and the spatial distribution range of the external dust zone are uniformly converted and aligned to ensure that all data are calculated based on a unified spatial coordinate system in the mine. Then, the spatial coordinates of each dust sensor are processed individually. First, the sensor coordinates are compared point-by-point with the spatial boundary coordinates of the inner dust zone to determine if the coordinates are completely within the enclosed space defined by the inner dust zone. If they are, the sensor is marked and associated with the corresponding inner dust zone. If not, the sensor coordinates are further matched with the spatial contour parameters of the gap zone. By calculating the spatial distance between the sensor coordinates and the surfaces of the guide skirt and conveyor belt, it is determined whether the sensor is located within the elongated spatial range of the gap zone. If it is, it is marked. The sensor is associated with the corresponding gap area. If the association is still not established, the sensor coordinates are compared with the spatial distribution range of the external dust area to confirm whether the coordinates are located outside the chute and connected to the roadway space. If the conditions are met, the sensor is marked as associated with the corresponding external dust area. After the initial matching of all sensors is completed, the matching result verification process is initiated. Spatial uniqueness detection is used to check for anomalies such as a single sensor corresponding to multiple areas or no corresponding area. Abnormal data is re-compared and corrected. At the same time, the rationality of the spatial position relationship between the sensor and the area is verified to ensure that the matching result can truly reflect the actual monitoring area of ​​the sensor. Finally, a structured matching result containing the unique identifier of each sensor, the corresponding area identifier, and the area type is generated, providing an accurate data association basis for subsequent statistical analysis of dust data by area and analysis of dust migration paths.

[0036] The dust cluster identification module is used to compare the dust quality of all internal dust areas in the underground centralized transfer station based on the matching results, and to obtain the main area of ​​the dust cluster. In an embodiment of the present invention, the specific steps for obtaining the main region of the dust cluster are as follows: Based on the matching results, determine the total number of first sensors of the dust sensors corresponding to the dust area in the inner cavity; The matching result refers to the correspondence obtained by matching the installation position of the dust sensor with the spatial position of the inner cavity dust area. This correspondence is used to characterize which inner cavity dust area each dust sensor is located in. The first total number of sensors refers to the number of dust sensors that fall into the same inner cavity dust area according to the matching result. This number reflects the sensor coverage used to characterize the dust state of the inner cavity dust area.

[0037] Specifically, the generated structured matching results are first extracted, and all dust sensor information associated with the internal dust area is filtered out, including the unique identifier of each sensor and the corresponding internal dust area identifier. Then, the filtered sensor information is classified and collected according to the internal dust area identifier. All sensor information corresponding to the same internal dust area identifier is grouped together. The unique identifiers of the sensors in each group are counted one by one to ensure that each sensor is only counted in its corresponding associated internal dust area group and is not counted repeatedly. At the same time, sensor information without a corresponding internal dust area identifier or with an abnormal identifier is checked and removed. Finally, the number of sensors in each group is the total number of first sensors in the corresponding internal dust area of ​​that group, thus completing the determination of the total number of first sensors corresponding to each internal dust area.

[0038] Based on the matching results, determine the first dust concentration of the dust sensor corresponding to the dust area in the inner cavity; The first dust concentration refers to the dust concentration data collected by each dust sensor corresponding to the inner cavity dust zone. This dust concentration data reflects the dust content level in the air within the inner cavity dust zone.

[0039] First, the matching results are extracted, and the unique identifiers of all dust sensors associated with the inner cavity dust area are filtered out. These sensors are then grouped and categorized according to the unique identifiers of the inner cavity dust areas to ensure that each sensor belongs to only one inner cavity dust area. Then, based on the unique identifiers of each group of sensors, the raw dust concentration data collected in real time by each sensor in the current monitoring period is retrieved. The retrieved raw data is verified one by one, and the valid dust concentration data that meets the monitoring data specifications is retained. These valid dust concentration data are then associated and bound with the corresponding inner cavity dust areas, and finally, all the valid dust concentration data corresponding to each inner cavity dust area are obtained. This data is the first dust concentration corresponding to that inner cavity dust area.

[0040] The average dust concentration in the inner cavity dust area is determined based on the total number of first sensors and the first dust concentration. The average dust concentration in the inner cavity dust area refers to the characterization value obtained by summarizing the dust concentration data belonging to the same inner cavity dust area based on the total number of first sensors and the first dust concentration. It is used to reflect the overall dust distribution status of the inner cavity dust area.

[0041] First, the total number of first sensors corresponding to each inner cavity dust zone and all valid first dust concentration data in that zone are extracted. Then, all first dust concentration data in the same inner cavity dust zone are summed to obtain the total dust concentration of that inner cavity dust zone. Next, the calculated total dust concentration is divided by the corresponding total number of first sensors. During the calculation process, it is ensured that all first dust concentration data involved in the calculation are real and valid monitoring data and that the total number of first sensors is the accurately counted number of valid sensors, so as to avoid invalid data or statistical errors affecting the results. Finally, the value obtained by this arithmetic average calculation is the average dust concentration of the inner cavity dust zone. This value can comprehensively reflect the overall dust content level of the corresponding inner cavity dust zone, providing accurate concentration parameter support for subsequent calculation of dust quality in the inner cavity dust zone.

[0042] Multiply the average dust concentration by the volume of the inner dust zone to obtain the dust mass of the inner dust zone. The volume of the inner dust zone refers to the size of the space occupied by the inner dust zone in the downhole space, which is defined by structures such as chutes; the dust mass of the inner dust zone refers to the result obtained based on the average dust concentration and the volume of the inner dust zone, and is used to characterize the total amount of dust in the inner dust zone.

[0043] The inner cavity dust area corresponding to the largest quantity of dust is taken as the main area of ​​the dust cluster.

[0044] The main dust cluster area refers to the region within the chute cavity of an underground centralized transfer station where dust exhibits a highly concentrated spatial distribution. The density of suspended dust in this area is significantly higher than in other locations within the chute cavity. Due to the falling, collision, and friction of coal during transfer, dust is not uniformly distributed under airflow disturbances and structural constraints. Instead, it tends to accumulate within a specific spatial range inside the chute, forming a spatially directional and concentrated dust accumulation area. This dust accumulation area is the main dust cluster area, reflecting the most significant spatial location of dust generation and accumulation during the transfer operation. It is the main concentrated area of ​​dust activity within the chute cavity.

[0045] By combining the average dust concentration in the inner cavity dust zone with its volume, the overall scale of dust within that zone can be obtained. This overall scale can simultaneously reflect the degree of dust concentration in the space and the spatial range it occupies. Since the distribution of dust in the inner cavity of the chute is usually non-uniform, although there may be differences in dust concentration in different inner cavity dust zones, the concentration alone cannot fully reflect the actual dust accumulation in the space. The dust mass obtained by introducing the volume factor can more realistically characterize the degree of dust accumulation and spatial concentration state in a certain inner cavity dust zone. The inner cavity dust zone with the largest dust mass value is identified as the main area of ​​dust clusters, which can effectively correspond to the area with the most significant dust accumulation and the largest total dust volume in the inner cavity of the chute, thus reflecting the main concentration location of dust clusters in space.

[0046] The gap screening module is used to screen the gap areas adjacent to the main area of ​​the dust cluster to obtain the main jet gap; In an embodiment of the present invention, the specific steps for obtaining the main injection slot are as follows: Based on the spatial location of the main region of the dust cluster, the gap regions adjacent to the main region of the dust cluster are determined and defined as candidate gap regions; The spatial location of the main dust cluster area refers to the specific distribution location of the main dust cluster area in the internal cavity space of the underground centralized transfer station. This spatial location is used to characterize the area where dust is most concentrated in the internal cavity space. The candidate gap area refers to the gap space that is directly adjacent to the main dust cluster area in terms of spatial location. This gap space is usually located between the guide skirt and the conveyor belt or between the chute and other structures, and is a potential channel for dust to migrate from the internal cavity space to the external space.

[0047] First, the spatial location data of the identified main area of ​​the dust cluster is retrieved, including the three-dimensional spatial boundary coordinates, contour range, and spatial distribution parameters of the area. At the same time, the three-dimensional spatial location information of all gap areas is extracted, covering the spatial boundary, extension trajectory, and location parameters of each gap area. The spatial boundary of the main area of ​​the dust cluster and the spatial boundary of each gap area are compared and analyzed one by one through the spatial adjacency detection algorithm to determine whether there is a direct spatial contact or continuous spatial connection between the two. All gap areas that are directly adjacent to the main area of ​​the dust cluster in spatial location are screened out. These screened gap areas are uniformly defined as candidate gap areas. At the same time, the unique identifier, spatial location, and adjacency boundary information of each candidate gap area are recorded to ensure that the determination of candidate gap areas accurately reflects the potential channels for dust to migrate outward from the main area of ​​the dust cluster.

[0048] Based on the spatial adjacency relationship in the digital twin system, the external dust region connected to the candidate gap region is determined and defined as the candidate external dust region; Candidate external dust area refers to the external dust area that is directly connected to the candidate gap area in terms of spatial adjacency. It is used to characterize the spatial area that dust enters after diffusing outward through the corresponding gap.

[0049] First, the three-dimensional spatial data of all candidate gap areas in the digital twin system are retrieved, including the spatial boundary coordinates, extension trajectory, port position, and spatial contour parameters of each candidate gap area. At the same time, the three-dimensional spatial information of all external dust areas is extracted, covering the spatial range, boundary contour, connection path with the roadway space, and connection relationship with the surrounding structure of each external dust area. The spatial data of the two types of areas are uniformly converted into a unified spatial coordinate system in the mine to ensure that the data benchmark is consistent and the dimensions are uniform. Then, through the spatial connectivity detection algorithm, the port spatial position of each candidate gap area is compared and analyzed with the boundary spatial position of each external dust area one by one to determine whether there is a direct spatial connection without structural isolation, a continuous spatial connection, or an unobstructed channel that can form dust migration between the two. All external dust areas that are directly connected to the candidate gap areas in space are screened out, and these screened external dust areas are uniformly defined as candidate external dust areas.

[0050] Multiply the average dust concentration of the candidate external dust area by the volume of the candidate external dust area to obtain the dust mass of the candidate external dust area. Divide the dust mass of the candidate external dust area by the dust mass of the main dust cluster area to obtain the jet correlation ratio; select the candidate gap area with the largest jet correlation ratio as the main jet gap.

[0051] The jet correlation ratio refers to the ratio between the dust mass of the candidate external dust area and the dust mass of the main dust cluster area. This ratio reflects the relative correlation of dust migration from the inner cavity space to the outer space through the corresponding gap. The main jet gap refers to the gap area in the underground centralized transfer station where dust migration from the inner cavity space to the outer space is most concentrated among multiple gap areas located between the inner cavity of the chute and the outer roadway space. Because the dust inside the chute has obvious spatial orientation under the action of airflow disturbance and material movement, the dust does not uniformly escape from all structural gaps, but is more likely to form a concentrated discharge channel along the gap with more favorable geometric position, spatial connectivity and airflow conditions. This concentrated discharge channel is the main jet gap.

[0052] During the transfer operation at the underground centralized transfer station, dust in the chute's inner cavity migrates to the outer space under the influence of gravity, material falling disturbance, and airflow. When dust diffuses outward through different gaps, the scale of dust formed in the corresponding outer space is directly related to the dust leakage capacity of that gap. By combining the average dust concentration and volume of candidate outer dust zones, the overall scale of dust in that outer space can be obtained. This overall scale reflects the amount of dust entering the outer space through the corresponding gap. Further, by calculating the ratio of this outer dust mass to the dust mass of the main dust cluster area, the influence of changes in the total amount of dust in the inner cavity on the results can be eliminated, thus highlighting the relative contribution of different gaps in the dust leakage process. Since the migration path of dust from the inner cavity to the outer space is usually concentrated, dust tends to form the main exhaust channel along the gaps with better spatial connectivity and less resistance. The candidate gap with the largest jet correlation ratio corresponds to the largest proportion of external dust, which can characterize the dominant role of the gap in the dust jetting process. Therefore, the candidate gap is identified as the main jetting gap.

[0053] During the transfer point operation, the high concentration of dust generated inside the chute does not leak evenly from all structural gaps. Instead, it mainly disperses outward along a certain gap, forming a concentrated dust discharge phenomenon. This gap acts as the main outlet for dust leakage. If this main outlet is not identified, and only a sudden increase in dust at a certain external location is observed, it is easy to mistakenly believe that there is a problem with the entire transfer process, leading to a reduction in coal feed or a slowdown in belt speed. However, the production process itself may be normal. By identifying the main injection gap, the external dust anomaly can be directly correlated to a specific structural location, clearly indicating that the dust leakage is caused by a poor seal at a certain gap. This distinguishes between structural and process problems, enabling the production monitoring system to make the correct judgment, avoiding unnecessary production reduction, and providing a clear target for subsequent inspection and maintenance.

[0054] The process dust module is used to obtain process dust indicators based on the main area of ​​dust clusters and the main injection gap. In an embodiment of the present invention, the specific steps for obtaining the process dust index are as follows: Based on the main dust cluster area and the external dust area connected to the main jet gap, the structural dust leakage area is determined; Structural dust leakage areas refer to the spatial regions in underground centralized transfer stations where dust can leak from the internal cavity to the external roadway space through specific structural locations due to gaps between structures such as chutes, guide skirts, and enclosures. This area reflects the location where dust escapes due to structural sealing conditions.

[0055] First, the three-dimensional spatial data of the identified dust cluster main region is retrieved, including the boundary coordinates, outline range, and spatial distribution parameters of the region. At the same time, the complete spatial information of the main injection slot is extracted, covering the boundary coordinates, extension trajectory, end positions, and connection relationship with the surrounding structure of the slot. The three-dimensional spatial data of the external dust area directly connected to the main injection slot is also retrieved, including the spatial range, boundary outline, and connection path of the external dust area to the main injection slot. The spatial data of the three types of regions are uniformly converted into a unified spatial coordinate system in the mine to ensure consistent data benchmarks and uniform dimensions. Then, through spatial correlation verification, it is confirmed that there is a direct spatial adjacency relationship between the dust cluster main region and the main injection slot, and a direct connection relationship without structural isolation between the main injection slot and the corresponding external dust area. The three together constitute a continuous and uninterrupted dust leakage path. Then, the dust cluster main region is regarded as the source region of dust leakage, the main injection slot as the key channel region of dust leakage, and the corresponding connected external dust area as the diffusion and receiving area after dust leakage. This is integrated to form a structured spatial set containing these three types of regions. This set is the structured dust leakage region.

[0056] Determine the process dust area based on the structural dust leakage area; In embodiments of the present invention, determining the process dust area based on the structural dust leakage area includes: Remove the internal dust areas from the structural dust leakage areas from all internal dust areas to obtain the process internal dust area set; Specifically, first, all relevant information about the internal dust areas of the underground centralized transfer station is retrieved, including the unique identifier, spatial location, and volume parameters of each internal dust area. At the same time, the unique identifiers of the internal dust areas contained in the identified structural dust leakage areas are extracted. The unique identifiers of all internal dust areas are compared one by one with the unique identifiers of internal dust areas in the structural dust leakage areas. All internal dust areas that do not appear in the internal dust area identifier list in the structural dust leakage areas are screened out. These screened internal dust areas are integrated and classified to ensure that each included internal dust area has no duplicate identifiers and has a complete spatial range, and finally a set of process internal dust areas is formed.

[0057] Remove the external dust areas from the structural dust leakage areas from all external dust areas to obtain the process external dust area set; First, collect all external dust area information of the underground centralized transfer station, including the unique identifier, spatial distribution range and volume data of each external dust area. Then, extract the unique identifiers of the external dust areas contained in the structural dust leakage area. By comparing them one by one, match the unique identifiers of all external dust areas with the unique identifiers of external dust areas in the structural dust leakage area, remove the external dust areas with the same identifier, and retain the external dust areas not included in the structural dust leakage area. Collect and organize the remaining external dust areas in a unified manner, and check the spatial data integrity and identifier uniqueness of each external dust area to form a set of external dust areas in the process.

[0058] The dust areas in the process are determined based on the set of dust areas inside the process cavity and the set of dust areas outside the process.

[0059] The process dust area refers to the dust distribution space directly related to the coal transfer and conveying operations themselves, after excluding the impact of structural dust leakage. This area is used to characterize the dust generated and diffused during the normal operation of the production process.

[0060] The set of external dust areas refers to the spatial set formed after removing the external dust areas corresponding to structural dust leakage areas from all external dust areas; the set of internal dust areas and the set of external dust areas are spatially integrated in the digital twin system so that the two spatial sets together constitute a continuous dust distribution space; the integrated spatial set is determined as the process dust area, which is used to characterize the dust existence and distribution space corresponding to the normal production process of the underground centralized transfer station under the condition of not being affected by structural dust leakage, thereby completing the determination of the process dust area.

[0061] Based on the matching results, determine the dust quality in the process dust area; The dust quality of the process dust area refers to the overall scale of suspended dust in the air within the process dust area, which reflects the degree of dust accumulation in the space under normal production process conditions.

[0062] In the digital twin system, the spatial range of the process dust area and the installation position of each dust sensor are obtained. Based on the matching results, the process dust area corresponding to each dust sensor is determined. On this basis, the dust concentration data collected by the dust sensors mapped to each process dust area are obtained, and the dust concentration data belonging to the same process dust area are summarized and processed to obtain the average dust concentration of the process dust area.

[0063] Next, a three-dimensional spatial model of the underground centralized transfer station is loaded into the digital twin system. This three-dimensional spatial model includes complete spatial boundary information of chutes, guide skirts, conveyor belts, enclosures, and roadway spaces. The spatial division results of the process dust areas are read, which are used to determine the location range of each process dust area in the three-dimensional spatial model. For each process dust area, its corresponding spatial boundary surface in the three-dimensional spatial model is extracted, and a closed spatial unit is formed based on the spatial boundary surface. The closed spatial unit is spatially analyzed to identify the actual occupied range of the spatial unit in the underground coordinate system. After completing the spatial analysis, the volume of the spatial unit is calculated to obtain the volume information corresponding to each process dust area in the underground space. The volume information is used to characterize the size of different process dust areas in terms of spatial scale.

[0064] Finally, the average dust concentration in the process dust area is combined with the corresponding volume information to obtain the overall scale of dust in each process dust area, thereby determining the dust quality of the process dust area and realizing the determination of the dust quality of the process dust area based on the matching results.

[0065] The total dust mass is obtained by summing the dust masses in all process dust areas. Total dust mass refers to the result obtained by summing up the dust mass in all process dust areas, and is used to characterize the total amount of dust generated and distributed during the operation of the entire underground centralized transfer station during the production process.

[0066] Obtain the coal transport volume of the underground centralized transfer station; Coal transport volume refers to the amount of coal that is transferred through underground centralized transfer stations and enters the downstream transport system within the corresponding monitoring period. This quantity reflects the actual operating scale of the production process.

[0067] The operation data of the coal conveying equipment connected to the underground centralized transfer station is obtained. The operation data includes data that characterizes the actual conveying of coal through the transfer station and into the downstream conveying system. Based on the operation data, the amount of coal that is transferred through the underground centralized transfer station and enters the downstream conveying line within the corresponding monitoring period is statistically analyzed to obtain the coal conveying volume of the underground centralized transfer station within the monitoring period.

[0068] Divide the dust mass by the coal transport volume to obtain the process dust index.

[0069] The process dust index is a comprehensive indicator used to characterize the dust generation level during the normal production process of underground centralized transfer stations. This index reflects the overall dust level corresponding to the production process under a certain coal transportation scale. By establishing a correlation between the total amount of dust in the process dust area and the corresponding coal transportation volume, the process dust index makes the dust situation correspond to the production scale, thereby eliminating the impact of changes in transportation volume. It can reflect the dust generation and diffusion status in the transfer, transportation and other operation links of the production process itself, and is used to evaluate whether the production process operation is stable and the changes in dust control effectiveness.

[0070] In the production process of underground centralized transfer stations, dust generation is directly related to coal transfer and transportation operations. The larger the amount of coal passing through the transfer station, the greater the overall dust volume generated under the same operating conditions. By summarizing the dust quality in all process dust areas, the total amount of dust generated and distributed in the production process within the corresponding monitoring period can be obtained. This total amount reflects the overall dust level in the entire transfer station space. Furthermore, by calculating the ratio of this total dust volume to the coal transportation volume within the same monitoring period, the dust generation can be correlated with the production scale, thereby eliminating the impact of changes in coal transportation volume. This reflects the dust generation level corresponding to a unit of coal transportation process, making the dust situation comparable under different time periods or operating conditions, and thus characterizing the operating status of the production process in terms of dust control.

[0071] During transfer point operations, the high concentration of dust generated inside the chute does not leak evenly from all structural gaps, but mainly disperses outwards along a certain gap, forming a concentrated dust discharge phenomenon. In this case, the dust reading in a local area of ​​the external roadway will increase significantly due to the concentrated discharge from a single gap, but this increase does not indicate that the coal transfer and transportation process itself is abnormal. If monitoring is based solely on local dust concentration or total dust volume, it is easy to misjudge the local anomaly caused by the concentrated dust discharge phenomenon as an overall production process anomaly, thus incorrectly reducing the coal feed rate or adjusting the transportation parameters. By introducing process dust indicators and establishing a correlation between the total dust volume corresponding to the production process and the coal transportation volume, the dust generation level of the production process itself under the unit production scale can be reflected, excluding the interference of concentrated dust discharge. This allows the monitoring results to truly reflect the operating status of the production process, thereby avoiding the misleading effect of concentrated dust discharge phenomenon on the monitoring and management of the mine production process.

[0072] The process monitoring module is used to obtain production process monitoring results based on process dust indicators.

[0073] In an embodiment of the present invention, the specific steps for obtaining production process monitoring results are as follows: Set threshold ranges for indicators based on historical production data from the mine; Historical production data refers to the data set related to the operation status of the underground centralized transfer station formed during the mine's past production process. This data set reflects the scale of coal transportation, dust generation, and process operation characteristics under different production conditions. The index threshold range refers to the range of changes in process dust indexes formed based on the historical production data. This range is used to characterize the reasonable range of process dust indexes under normal operating conditions.

[0074] First, a comprehensive collection of historical production data related to the operation status of the underground centralized transfer station was generated during the mine's previous production processes. This included data on coal conveying volume, conveying speed, transfer frequency, and other conveying scale data for different production periods; process dust index data such as dust concentration and dust quality for each monitoring period; environmental parameters such as underground temperature, humidity, and air pressure under corresponding production conditions; and equipment operating parameters such as rotational speed, load, and running time of the transfer equipment. A small number of key missing data were supplemented using linear interpolation to ensure that all retained data are valid data reflecting normal production status.

[0075] Subsequently, statistical analysis was performed on the process dust index data in the valid historical data. Box plot analysis was used to identify and eliminate potential outliers in the data. Statistical parameters such as the mean, median, standard deviation, maximum, and minimum values ​​of the process dust index were calculated. At the same time, multiple production load intervals were divided based on coal transportation volume, and the distribution characteristics and variation patterns of the process dust index in each interval were statistically analyzed. Combining mine safety production regulations, environmental emission standards, and equipment operation safety requirements, and referring to industry benchmark data of similar mines, the statistical parameters of the process dust index in each production load interval were weighted and corrected to determine the reasonable variation range of the process dust index corresponding to each production load interval. The reasonable ranges of all intervals were integrated to form a complete index threshold range covering the entire production load scenario.

[0076] Next, simulation tests were conducted on the initially set threshold range using historical data backtesting to verify its ability to distinguish between normal and abnormal states under different production conditions. The threshold boundaries were adjusted and optimized based on the test results, and finally, a threshold range with high adaptability and reliability was determined. At the same time, the historical data statistical basis, applicable production load range, and data confidence level corresponding to the threshold range were recorded to ensure that the threshold range can accurately characterize the range of process dust indicators under normal production process conditions, providing a scientific and reliable reference standard for subsequent judgment of the production process operation status.

[0077] Define threshold comparison rules; Threshold comparison rule refers to the judgment rule used to determine whether the dust index of the process is within the threshold range. This rule is used to distinguish whether the production process is in a normal state or deviates from the normal state.

[0078] The core purpose of defining threshold comparison rules is to accurately distinguish the state of the production process by associating the values ​​of process dust indicators with the corresponding threshold ranges. First, extract the pre-defined threshold ranges covering different production load intervals, and clarify the lower and upper limits of the thresholds for each interval. At the same time, determine the specific values ​​of the process dust indicators calculated within the current monitoring period and the corresponding production load intervals. Ensure that the process dust indicators are valid data calculated based on the total mass of process dust and coal transportation volume after removing the influence of structural dust leakage, and that the production load intervals corresponding to the indicators completely match the production load intervals of the threshold ranges, avoiding judgment bias caused by cross-interval comparisons.

[0079] Subsequently, the process dust index value is compared with the threshold range of the corresponding production load interval. If the process dust index value is greater than or equal to the lower threshold and less than or equal to the upper threshold, the production process is determined to be in normal operation. If the process dust index value is less than the lower threshold, the production process is determined to be in a low dust abnormal state. If the process dust index value is greater than the upper threshold, the production process is determined to be in a high dust abnormal state. At the same time, a comparison result review mechanism is set up to re-verify the accuracy of the process dust index calculation process, the rationality of the production load interval matching, and the applicability of the threshold range for results determined to be abnormal. Complete information of each comparison is recorded, including process dust index value, corresponding threshold range, production load interval, comparison result, and review conclusion, to ensure that the threshold comparison rule is strictly and traceably executed, providing a clear judgment basis for subsequent production process adjustments and anomaly troubleshooting.

[0080] Input the process dust index into the process monitoring unit of the digital twin system; The process monitoring unit performs threshold comparison on the process dust index according to the threshold comparison rules to obtain the production process monitoring results.

[0081] The process monitoring unit is a functional unit set up in the digital twin system. It is used to receive process dust indicators and judge the process dust indicators according to the threshold comparison rules. The production process monitoring result refers to the judgment result obtained by the process monitoring unit after completing the comparison of process dust indicators with the threshold range. This result is used to reflect the operating status of the production process of the underground centralized transfer station under the current production conditions.

[0082] The process monitoring unit receives the input process dust index, and simultaneously retrieves the pre-stored threshold comparison rules and index threshold ranges covering different production load intervals. First, it verifies the validity of the process dust index, confirming that it is valid data calculated based on the total mass of process dust and coal transportation volume after removing the influence of structural dust leakage, and that the index is accompanied by clear information on the current production load interval. Then, it accurately matches the corresponding index threshold range according to the production load interval, clarifies the lower limit and upper limit of the range, and performs a precise numerical comparison between the process dust index value and the matched threshold range according to the threshold comparison rules.

[0083] If the indicator value is greater than or equal to the lower threshold and less than or equal to the upper threshold, the production process is determined to be in normal operation. If the indicator value is less than the lower threshold, it is determined to be a low dust abnormality. If the indicator value is greater than the upper threshold, it is determined to be a high dust abnormality. For the results determined to be abnormal, a secondary review process is initiated to re-verify the accuracy of the calculation logic of the process dust indicator, the rationality of the matching of the production load range, and the applicability of the threshold range. Misjudgments caused by data errors or matching deviations are eliminated. Finally, a production process monitoring result containing the process dust indicator value, the corresponding production load range, the matched threshold range, the comparison process, and the final judgment conclusion is generated. This result can clearly reflect the operating status of the production process under the current production conditions of the underground centralized transfer station, providing a reliable basis for subsequent production adjustments or abnormal handling.

[0084] To address the aforementioned problems, this invention also provides a mining production process monitoring and management method based on digital twins, see [link to relevant documentation]. Figure 1 Specifically, including: The matching results are obtained based on the geometric information of the underground centralized transfer station; Based on the matching results, the dust quality of all internal dust zones in the underground centralized transfer station is compared to obtain the main area of ​​dust clusters. The gap regions adjacent to the main area of ​​the dust cluster are screened to obtain the main jet gaps; Process dust indicators are obtained based on the main area of ​​dust clusters and the main jet gaps. Production process monitoring results are obtained based on process dust indicators.

[0085] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A mine production process monitoring and management system based on digital twins, characterized in that, include: The geometric matching module is used to obtain matching results based on the geometric information of the underground centralized transfer station; The dust cluster identification module is used to compare the dust quality of all internal dust areas in the underground centralized transfer station based on the matching results, and to obtain the main area of ​​the dust cluster. The gap screening module is used to screen the gap areas adjacent to the main area of ​​the dust cluster to obtain the main jet gap; The process dust module is used to obtain process dust indicators based on the main area of ​​dust clusters and the main injection gap. The process monitoring module is used to obtain production process monitoring results based on process dust indicators.

2. The mine production process monitoring and management system based on digital twins according to claim 1, characterized in that, The specific steps to obtain the matching results are as follows: In the digital twin system of the mine, the geometric information of the underground centralized transfer station is acquired; the geometric information includes the three-dimensional spatial position data of the chute, guide skirt, conveyor belt and enclosure. Based on geometric information, the underground centralized transfer station is divided into an inner dust zone, a crevice zone, and an outer dust zone; Obtain the installation locations of each dust sensor at the underground centralized transfer station; The installation positions of each dust sensor are matched with the spatial positions of the inner dust area, the gap area, and the outer dust area to obtain the matching results.

3. The mine production process monitoring and management system based on digital twins according to claim 2, characterized in that, The specific steps for dividing the internal dust area, the gap area, and the external dust area are as follows: Based on the three-dimensional spatial location data of the chute, the first spatial region located inside the chute is determined; The first spatial region is designated as the inner cavity dust zone; The gap area between the guide skirt and the conveyor belt is defined as the gap area. Based on the three-dimensional spatial location data of the chute and the enclosure, a second spatial region located outside the chute and connected to the mine roadway space is determined. The second space region is designated as the external dust region.

4. The mine production process monitoring and management system based on digital twins according to claim 1, characterized in that, The specific steps to obtain the main region of the dust cluster are as follows: Based on the matching results, determine the total number of first sensors of the dust sensors corresponding to the dust area in the inner cavity; Based on the matching results, determine the first dust concentration of the dust sensor corresponding to the dust area in the inner cavity; The average dust concentration in the inner cavity dust area is determined based on the total number of first sensors and the first dust concentration. Multiply the average dust concentration by the volume of the inner dust zone to obtain the dust mass of the inner dust zone. The inner cavity dust area corresponding to the largest quantity of dust is taken as the main area of ​​the dust cluster.

5. The mine production process monitoring and management system based on digital twins according to claim 1, characterized in that, The specific steps to obtain the main injection slot are as follows: Based on the spatial location of the main region of the dust cluster, the gap regions adjacent to the main region of the dust cluster are determined and defined as candidate gap regions; Based on the spatial adjacency relationship in the digital twin system, the external dust region connected to the candidate gap region is determined and defined as the candidate external dust region; Multiply the average dust concentration of the candidate external dust area by the volume of the candidate external dust area to obtain the dust mass of the candidate external dust area. Divide the dust mass of the candidate external dust area by the dust mass of the main dust cluster area to obtain the jet correlation ratio; The candidate gap region corresponding to the largest injection correlation ratio is selected as the main injection gap.

6. The mine production process monitoring and management system based on digital twins according to claim 1, characterized in that, The specific steps to obtain the process dust index are as follows: Based on the main dust cluster area and the external dust area connected to the main jet gap, the structural dust leakage area is determined; the process dust area is determined based on the structural dust leakage area. Based on the matching results, determine the dust quality in the process dust area; The total dust mass is obtained by summing the dust masses in all process dust areas. Obtain the coal transport volume of the underground centralized transfer station; Divide the dust mass by the coal transport volume to obtain the process dust index.

7. The mine production process monitoring and management system based on digital twins according to claim 6, characterized in that, The process dust areas are determined based on structural dust leakage areas, including: Remove the internal dust areas from the structural dust leakage areas from all internal dust areas to obtain the process internal dust area set; Remove the external dust areas from the structural dust leakage areas from all external dust areas to obtain the process external dust area set; The dust areas in the process are determined based on the set of dust areas inside the process cavity and the set of dust areas outside the process.

8. The mine production process monitoring and management system based on digital twins according to claim 1, characterized in that, The specific steps to obtain production process monitoring results are as follows: Set threshold ranges for indicators based on historical production data from the mine; Define threshold comparison rules; Input the process dust index into the process monitoring unit of the digital twin system; The process monitoring unit performs threshold comparison on the process dust index according to the threshold comparison rules to obtain the production process monitoring results.

9. A method for monitoring and managing mine production processes based on digital twins, characterized in that, The method includes: The matching results are obtained based on the geometric information of the underground centralized transfer station; Based on the matching results, the dust quality of all internal dust zones in the underground centralized transfer station is compared to obtain the main area of ​​dust clusters. The gap regions adjacent to the main area of ​​the dust cluster are screened to obtain the main jet gaps; Process dust indicators are obtained based on the main area of ​​dust clusters and the main jet gaps. Production process monitoring results are obtained based on process dust indicators.

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