A kind of fine geological model updating method based on fully mechanized mining equipment monitoring data

Abstract

This invention discloses a method for updating a fine geological model for longwall mining based on monitoring data from fully mechanized mining equipment. Belonging to the field of fully mechanized coal mining faces, this method updates the parameters of the fine geological model based on hydraulic supports. These parameters include: the coal wall thickness at the current position of the hydraulic support, the spatial coordinates of the bottom and top plates of the hydraulic support, and the data point type. The method calculates the coal wall thickness at the current position of each hydraulic support; calculates the corresponding spatial coordinates of the bottom plate for each hydraulic support; calculates only the neighborhood of newly added top and bottom plate data points, reusing historical stable clusters, reducing computational load by more than 60%; the neighborhood radius and minimum number of points (MinPts) are dynamically adjusted with the advance speed and the number of supports, conforming to the spatial correlation of geology and avoiding clustering bias caused by fixed parameters, significantly improving update efficiency and adapting to the dynamics of longwall mining; it abandons traditional full-scale clustering, solving the technical problem of long update times in existing model update methods.

Description

Technical Field

[0001] This invention belongs to the field of fully mechanized coal mining faces and relates to a data update method, specifically a method for updating a fine geological model of coal mining based on monitoring data of fully mechanized mining equipment. Background Technology

[0002] The fully mechanized mining face employs techniques such as channel wave exploration, precise roadway measurement, geological mapping of the face roadway, and gas borehole measurement to investigate the coal seam information and geological structure. By integrating this data, a three-dimensional geological model of the mining face is constructed. Based on this model, cutting curves are provided to the coal mining machine, providing geological support for precise mining in intelligent fully mechanized mining faces.

[0003] Currently, model updates rely on manual intervention, which is labor-intensive and inefficient. Existing technologies primarily rely on manual field measurements (such as manual drilling and leveling to obtain coal thickness and floor elevation data), followed by manual data entry and calibration. However, fully mechanized mining faces are typically 100-300m long, with rapid advances (5-10m per day). Manual measurements require frequent entry into hazardous areas of the working face, resulting in extremely high labor intensity and long data collection cycles. This causes model updates to lag behind the pace of mining and fail to reflect the dynamic changes in geological conditions at the working face in a timely manner.

[0004] Furthermore, existing models suffer from poor adaptability and struggle to handle the dynamic characteristics of mining data: during mining, geological parameters such as coal thickness and floor elevation change continuously as the mining progresses, and the data exhibits "incremental, fluctuating, and correlated" characteristics. For example, coal thickness data from adjacent supports show spatial correlation, while data from different periods of the same support show temporal correlation. When using the existing DBSCAN clustering algorithm for model updates, it adopts a "full clustering" mode, meaning that after each acquisition of new data, a full clustering calculation must be performed on all historical data and the newly added data. This not only consumes a large amount of computing resources but also consumes a lot of time for updates, failing to meet the needs of incremental updates of mining site data. Consequently, the model update efficiency is low, making it difficult to achieve "real-time updates and dynamic adaptation." Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a method for updating a refined geological model of mining operations based on monitoring data from fully mechanized mining equipment, thereby solving the technical problems of high labor intensity and time-consuming update processes in existing model update methods.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A method for updating a fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment. This method updates the parameters of the fine geological model based on hydraulic supports, including the coal wall thickness at the current position of the hydraulic supports. The spatial coordinates of the base plate and the spatial coordinates of the top plate of the hydraulic support, as well as the data point types, including core points, boundary points, and noise; The hydraulic support is located between the top and bottom plates of the coal seam, and includes a base mounted on the bottom plate. A set of long hydraulic rods is hinged to the base, and a top beam is hinged to the top of the long hydraulic rods. A side guard plate is provided at the front end of the top beam, and a tail beam is provided at the rear end of the top beam. A height sensor and an tilt sensor are provided on the top beam. A support seat is also provided on the base, and a set of short hydraulic rods is provided on the support seat. The top of the short hydraulic rods is hinged to the tail beam. The method specifically includes the following steps: Step 1: Calculate the coal wall thickness at the current position of each hydraulic support. ; +c in: 'a' represents the length of the top beam, in meters (m). b is the distance between the intersection of the top beam and the tail beam and the height sensor, in meters; c represents the height of the base, in meters (m). The value measured by the altitude sensor, in meters (m). The roll angle of the i-th hydraulic support detected by the tilt sensor, in degrees. Step 2: Calculate the base plate spatial coordinates corresponding to each hydraulic support. ; Step 3: Based on the coal at each hydraulic support obtained in Step 1... The base plate spatial coordinates of each hydraulic support obtained in step two The calculated top plate spatial coordinates for each hydraulic support are as follows: This yields the newly added top and bottom plate data points for each hydraulic support, thus creating the updated top and bottom plate dataset. ; The newly added top and bottom plate data points include the number, plane coordinates, bottom plate elevation, and coal wall thickness of each hydraulic support; Step 4: Calculate the updated top and bottom plate datasets obtained in Step 3. The ε-neighborhood of each newly added top and bottom plate data point is calculated, and the data points within the ε-neighborhood of each newly added top and bottom plate data point are counted to obtain the dataset corresponding to each newly added top and bottom plate data point. ; Step 5: Determine the data point type of the newly added top and bottom plate data points. If it is a core point, proceed to step 6; if it is a boundary point, proceed to step 7; if it is a noise point, temporarily mark the noise point as noise. Step 6: Check the dataset corresponding to the newly added top and bottom plate data points. If the data point includes other core points, then merge the newly added top and bottom plate data point with the cluster to which the other core points belong, and update the core parameters of the merged cluster; if not, then create a new cluster with the newly added top and bottom plate data point as the center, include the boundary points in its ε-neighborhood into the new cluster, and proceed to step seven. The core parameters of the cluster include the cluster's center coordinates and parameter fluctuation range; Other key points include key points in the historical cluster and newly added key points; Step 7: Calculate the spatial distance between the newly added roof and floor data point and all core points, select the core point with the smallest spatial distance, and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements. If so, assign it to the cluster to which the core point belongs; otherwise, re-select the next nearest core point and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements, until the cluster allocation of the newly added roof and floor data point is completed, thus obtaining the updated refined geological model for mining. The parameter fluctuation requirements include coal thickness fluctuation and elevation fluctuation.

[0008] This invention also includes the following technical features: Between steps four and five, the following step is also included: verifying the marked noise. If the verification passes, the point is converted to a boundary point; otherwise, the noise point is maintained.

[0009] Step two specifically includes the following steps: Step 2.1, calculate the working face correction factor T;

[0010] in: i is the hydraulic support number, 1≤i≤N, and N is the total number of hydraulic supports on the working face. Let be the roll angle of the i-th hydraulic support, in degrees. L represents the width of the hydraulic support, in meters (m). The floor value of the left-side roadway when located at the working face cut-off point and facing the coal seam, in meters; The floor value of the right-side roadway when located at the working face cut-off point and facing the coal seam, in meters; Step 2.2, calculate the base plate elevation of each hydraulic support. ;

[0011] Step 2.3: Establish a coordinate system with the starting point of the intake roadway as the origin, the advancing direction as the x-axis, and the working face width direction as the y-axis; calculate the planar coordinates of each hydraulic support based on the arrangement sequence and advancing distance. That is, the base plate spatial coordinates corresponding to each hydraulic support are obtained as follows: .

[0012] The specific steps for step four are as follows: 4.1 Calculate the updated dataset for the top and bottom plates. any point in Calculation points With point Euclidean distance between ;

[0013] 4.2, European distance Does the following formula apply, and is q a newly added point or a historical valid point? If so, then include the point. The neighborhood;

[0014] 4.3 The neighborhood of adjacent hydraulic supports is weighted with a weight of 1.2 to 1.5, and the neighborhood of non-hydraulic supports is weighted with a weight of 1.0 to obtain the points. The set of data points in the ε-neighborhood Thus, the dataset is obtained.

[0015] Step five specifically includes the following steps: 5.1 Determine whether the newly added top and bottom plate data points obtained in step three satisfy the following formula. If they satisfy the formula, the newly added top and bottom plate data points are core points, and proceed to step six. If they do not satisfy the formula, the newly added top and bottom plate data points are boundary points or noise points, and proceed to step 5.2.

[0016] in: To add new top and bottom plate data points The number of data points within a neighborhood of radius ε centered at the origin; This is the minimum number of points after dynamic adjustment; Step 5.2: Determine whether there are core points within the domain of the newly added top and bottom plate data points. If there are, the newly added top and bottom plate data points are boundary points, and proceed to step seven; if not, the newly added top and bottom plate data points are noise points, and proceed to step 5.3. Step 5.3: Determine whether the newly added top and bottom plate data points corresponding to the three hydraulic supports adjacent to the noise point are all core points or boundary points, and whether the parameter deviation between the noise point and the three adjacent data points meets the allowable range of parameter deviation. If yes, then the noise point is identified as a boundary point and proceed to step seven; otherwise, the noise point is temporarily marked as noise. The allowable range of parameter deviations includes coal thickness deviation and elevation deviation, wherein the coal thickness deviation is ≤0.3m and the elevation deviation is ≤0.2m.

[0017] In step six, merging the newly added top and bottom plate data points with the clusters to which the other core points belong also requires meeting one of the following two conditions: First, the hydraulic supports corresponding to the two clusters are adjacent supports, and the parameter fluctuations of the core points within the clusters are consistent. Second, the two clusters are located in the same mining advance section, and the spatial distribution of the clusters is consistent with the undulation trend of the roadway floor.

[0018] Compared with the prior art, the beneficial technical effects of this invention are: (I) In this invention, only the neighborhood of newly added top and bottom plate data points is calculated, and historical stable clusters are reused, reducing the computational load by more than 60%; neighborhood radius The minimum number of points (MinPts) is dynamically adjusted according to the advance speed and the number of supports, which conforms to the geological spatial correlation and avoids the clustering bias caused by fixed parameters. This greatly improves the update efficiency and adapts to the dynamic nature of mining. It abandons the traditional full-scale clustering and solves the technical problem of the long update time in the model update method in the existing technology.

[0019] (II) In this invention, hydraulic support height and tilt sensors are used to automatically collect data, eliminating the need for manual drilling and leveling, and avoiding personnel entering dangerous areas; it achieves real-time updates at the support level and on a per-tool basis, with efficiency far exceeding that of traditional manual updates, thus solving the technical problem of high labor intensity for personnel in existing model update methods.

[0020] (III) In this invention, noise points are added for secondary verification to reduce sensor misjudgment due to instantaneous interference; cluster merging / splitting rules are formulated in combination with the adjacency of the support and the consistency of the advancement section to ensure the continuity of geological units and accurate reflection of local changes, thereby improving the robustness of the model and geological consistency. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2This is a flowchart illustrating step five in this invention; Figure 3 This is a schematic diagram of a hydraulic support. Figure 4 This is a schematic diagram of a coal mining face.

[0022] The meanings of the labels in the diagram are as follows: 1. Base; 2. Hydraulic support; 3. Top beam; 4. Side guard plate; 5. Tail beam; 6. Height sensor; 7. Tilt sensor; 8. Support seat; 9. Short hydraulic rod.

[0023] The specific content of the present invention will be further explained in detail below with reference to the embodiments. Detailed Implementation

[0024] It should be noted that, unless otherwise specified, all components in this invention are components known in the art.

[0025] The following are specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments. All equivalent modifications made based on the technical solutions of this application fall within the protection scope of the present invention.

[0026] This invention provides a method for updating a fine geological model of longwall mining based on monitoring data from fully mechanized mining equipment. The method updates the parameters of the fine geological model based on hydraulic supports, including the coal wall thickness at the current position of the hydraulic support. The spatial coordinates of the base plate and top plate of the hydraulic support, as well as the data point types, including core points, boundary points, and noise; The hydraulic support is located between the top and bottom plates of the coal seam and includes a base 1 set on the bottom plate. A set of long hydraulic rods 2 are hinged to the base 1. The top of the long hydraulic rods 2 are hinged to a top beam 3. A side guard plate 4 is set at the front end of the top beam 3 and a tail beam 5 is set at the rear end of the top beam 3. A height sensor 6 and an tilt sensor 7 are set on the top beam 3. A support seat 8 is also set on the base 1. A set of short hydraulic rods 9 are set on the support seat 8. The top of the short hydraulic rods 9 is hinged to the tail beam 5. The method specifically includes the following steps: Step 1: Calculate the coal wall thickness at the current position of each hydraulic support. ; +c in: 'a' represents the length of the top beam 3, in meters. b is the distance between the intersection of the top beam 3 and the tail beam 5 and the height sensor 6, in meters; c represents the height of base 1, in meters. The value detected by height sensor 6, in meters (m). The roll angle of the i-th hydraulic support detected by tilt sensor 7, in degrees. Step 2: Calculate the base plate spatial coordinates corresponding to each hydraulic support. ; Step 3: Based on the coal at each hydraulic support obtained in Step 1... The base plate spatial coordinates of each hydraulic support obtained in step two The calculated top plate spatial coordinates for each hydraulic support are as follows: This yields the newly added top and bottom plate data points for each hydraulic support, thus creating the updated top and bottom plate dataset. ; The newly added data points for the roof and floor include the number, plane coordinates, floor elevation, and coal wall thickness of each hydraulic support; Step 4: Calculate the updated top and bottom plate datasets obtained in Step 3. The ε-neighborhood of each newly added top and bottom plate data point is calculated, and the data points within the ε-neighborhood of each newly added top and bottom plate data point are counted to obtain the dataset corresponding to each newly added top and bottom plate data point. ; Step 5: Determine the data point type of the newly added top and bottom plate data points. If it is a core point, proceed to step 6; if it is a boundary point, proceed to step 7; if it is a noise point, temporarily mark the noise point as noise. Step 6: Check the dataset corresponding to the newly added top and bottom plate data points. If the data point includes other core points, then merge the newly added top and bottom plate data point with the cluster to which the other core points belong, and update the core parameters of the merged cluster; if not, then create a new cluster with the newly added top and bottom plate data point as the center, include the boundary points in its ε-neighborhood into the new cluster, and proceed to step seven. The core parameters of a cluster include the cluster's center coordinates and the range of parameter fluctuations; Other key points include key points in the historical cluster and newly added key points; Step 7: Calculate the spatial distance between the newly added roof and floor data point and all core points, select the core point with the smallest spatial distance, and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements. If so, assign it to the cluster to which the core point belongs; otherwise, re-select the next nearest core point and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements, until the cluster allocation of the newly added roof and floor data point is completed, thus obtaining the updated refined geological model for mining. The parameter fluctuation requirements include coal thickness fluctuation and elevation fluctuation.

[0027] In step one, the length 'a' of the top beam is a fixed value, determined by the hydraulic support model; the distance 'b' from the intersection of the top beam and the tail beam to the height sensor's installation position on the top beam is determined by the sensor's installation position; the height 'c' of the hydraulic support base is a fixed value, determined by the hydraulic support model; and the roll angle of the i-th support detected by the top beam tilt sensor... Angles of elevation are positive, angles of depression are negative; In step six, the core parameters of the merged clusters are updated to ensure cluster continuity. The traditional full-scale clustering approach is abandoned, and incremental updates and historical cluster reuse are adopted. Clustering calculations are performed only on newly added top and bottom plate data points, reusing stable clusters from historical models, significantly improving update efficiency. This is handled in three specific cases: In step six, the historical clusters are the geological clusters that have been stably stored after the previous model update.

[0028] Preferably, ε is set to 20 meters.

[0029] In step seven, the coal thickness fluctuation is ≤0.5m and the elevation fluctuation is ≤0.3m.

[0030] This invention also includes the following technical features: Between steps four and five, the following step is also included: verifying the marked noise. If the verification passes, the point is converted to a boundary point; otherwise, the noise point is maintained.

[0031] In the above technical solution, a secondary verification of noise points is added to reduce sensor misjudgment due to instantaneous interference; cluster merging / splitting rules are formulated in combination with the adjacency of the support and the consistency of the advancement section to ensure the continuity of geological units and accurate reflection of local changes, thereby improving the robustness of the model and geological consistency.

[0032] Step two specifically includes the following steps: Step 2.1, calculate the working face correction factor T;

[0033] in: i is the hydraulic support number, 1≤i≤N, and N is the total number of hydraulic supports on the working face. Let be the roll angle of the i-th hydraulic support, in degrees. L represents the width of the hydraulic support, in meters (m). The floor value of the left-side roadway when located at the working face cut-off point and facing the coal seam, in meters; The floor value of the right-side roadway when located at the working face cut-off point and facing the coal seam, in meters; Step 2.2, calculate the base plate elevation of each hydraulic support. ;

[0034] Step 2.3: Establish a coordinate system with the starting point of the intake roadway as the origin, the advancing direction as the x-axis, and the working face width direction as the y-axis; calculate the planar coordinates of each hydraulic support based on the arrangement sequence and advancing distance. That is, the base plate spatial coordinates corresponding to each hydraulic support are obtained as follows: .

[0035] In the above technical solution, the width L of the hydraulic support is a fixed value, determined by the hydraulic support model; the width L of the left-side roadway floor when facing the coal face... The baseline value was calibrated through prior leveling measurements; the floor value of the right-side roadway when facing the coal face. The benchmark value is calibrated through prior leveling measurements; the working face correction factor P is used to offset the effects of sensor measurement deviations and minor undulations in the roadway floor. The specific steps for step four are as follows: 4.1 Calculate the updated dataset for the top and bottom plates. any point in Calculation points With point Euclidean distance between ;

[0036] 4.2, European distance Does the following formula apply, and is q a newly added point or a historical valid point? If so, then include the point. The neighborhood;

[0037] 4.3 The neighborhood of adjacent hydraulic supports is weighted with a weight of 1.2 to 1.5, and the neighborhood of non-hydraulic supports is weighted with a weight of 1.0 to obtain the points. The set of data points in the ε-neighborhood Thus, the dataset is obtained.

[0038] In the above technical solution, the neighborhood is dynamically adjusted according to the current mining advance speed; the faster the advance speed, the smaller the value of ε, ranging from 0.5 to 1.5m; the slower the advance speed, the larger the value of ε, ranging from 1.5 to 2.5m. examine The neighborhood of each newly added top and bottom plate data point is calculated only for the newly added top and bottom plate data points, without repeating the calculation for historical data. In the neighborhood calculation process, spatial correlation weights are introduced, assigning higher weights (weight coefficients of 1.2-1.5) to data points of adjacent supports and normal weights (weight coefficients of 1.0) to data points of non-adjacent supports. This ensures that the neighborhood detection can fit the spatial continuity of the geological parameters of the mining face and improve the rationality of clustering.

[0039] Step five specifically includes the following steps: 5.1 Determine whether the newly added top and bottom plate data points obtained in step three satisfy the following formula. If they satisfy the formula, the newly added top and bottom plate data points are core points, and proceed to step six. If they do not satisfy the formula, the newly added top and bottom plate data points are boundary points or noise points, and proceed to step 5.2.

[0040] in: To add new top and bottom plate data points The number of data points within a neighborhood of radius ε centered at the origin; This is the minimum number of points after dynamic adjustment; Step 5.2: Determine whether there are core points within the domain of the newly added top and bottom plate data points. If there are, the newly added top and bottom plate data points are boundary points, and proceed to step seven; if not, the newly added top and bottom plate data points are noise points, and proceed to step 5.3. Step 5.3: Determine whether the newly added top and bottom plate data points corresponding to the three hydraulic supports adjacent to the noise point are all core points or boundary points, and whether the parameter deviation between the noise point and the three adjacent data points meets the allowable range of parameter deviation. If yes, then the noise point is identified as a boundary point and proceed to step seven; otherwise, the noise point is temporarily marked as noise. The allowable range of parameter deviations includes coal thickness deviation and elevation deviation, wherein the coal thickness deviation is ≤0.3m and the elevation deviation is ≤0.2m.

[0041] In the above scheme, the data will be reclassified based on the next batch of new data (to avoid misjudgment caused by interference from a single sensor).

[0042] Based on the traditional DBSCAN algorithm's rules for identifying core points, boundary points, and noise points, and considering the characteristics of noise data under longwall mining conditions (instantaneous and localized), a secondary rule for identifying noise points (an innovation) is added to avoid misjudgments. Core points correspond to areas with stable geological conditions at the working face and are the core foundation for constructing geological model clusters. Boundary points belong to the ε-neighborhood of a core point and correspond to areas with slight fluctuations in geological parameters (such as minor changes in coal thickness and slight undulations in the floor), and must be attached to the cluster to which the core point belongs.

[0043] In section 5.2, the minimum number of points, MinPts, is dynamically adjusted based on the spatial correlation between the number of supports and the geological parameters of the longwall mining face (the value is 5%-8% of the total number of supports in the working face to avoid clustering bias caused by fluctuations in data volume). The preferred value is MinPts=8.

[0044] In step six, merging the newly added top and bottom plate data points with the clusters to which the other core points belong also requires meeting one of the following two conditions: First, the hydraulic supports corresponding to the two clusters are adjacent supports, and the parameter fluctuations of the core points within the clusters are consistent. Second, the two clusters are located in the same mining advance section, and the spatial distribution of the clusters is consistent with the undulation trend of the roadway floor; Preferably, the parameter fluctuation value is ≤0.4m; the difference in advance distance is ≤5m when they are in the same mining advance section.

[0045] If a cluster becomes disconnected due to the removal of noise points (or the removal of abnormal data points after reviewing historical data), resulting in some core points within the cluster no longer being density-reachable, and the resulting sub-clusters all satisfy the condition of "number of core points ≥ M{MinPts} / 2", then the cluster is split. After splitting, the core parameters of each sub-cluster are initialized, and the spatial distribution of the sub-clusters is matched with the local changes in the geological conditions of the working face (such as cluster splitting caused by sudden changes in local coal thickness) in combination with the support arrangement order and spatial coordinates.

Claims

1. A method for updating a fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment, wherein the parameters of the fine geological model of longwall mining are updated based on hydraulic supports, and the parameters include: Coal wall thickness at the current position of the hydraulic support The spatial coordinates of the base plate and top plate of the hydraulic support, as well as the data point types, including core points, boundary points, and noise; The hydraulic support is located between the top and bottom plates of the coal seam and includes a base (1) set on the bottom plate. A set of long hydraulic rods (2) are hinged on the base (1). The top of the long hydraulic rods (2) is hinged to a top beam (3). A side guard plate (4) is provided at the front end of the top beam (3). A tail beam (5) is provided at the rear end of the top beam (3). A height sensor (6) and an inclination sensor (7) are provided on the top beam (3). A support seat (8) is also provided on the base (1). A set of short hydraulic rods (9) is provided on the support seat (8). The top of the short hydraulic rods (9) is hinged to the tail beam (5). The method is characterized by the following steps: Step 1: Calculate the coal wall thickness at the current position of each hydraulic support. ; +c in: a is the length of the top beam (3), in meters; b is the distance between the intersection of the top beam (3) and the tail beam (5) and the height sensor (6), in meters; c is the height of the base (1), in meters; The value detected by the height sensor (6) is in meters (m). The roll angle of the i-th hydraulic support detected by the tilt sensor (7), in °; Step 2: Calculate the base plate spatial coordinates corresponding to each hydraulic support. ; Step 3: Based on the coal at each hydraulic support obtained in Step 1 The base plate spatial coordinates of each hydraulic support obtained in step two The calculated top plate spatial coordinates for each hydraulic support are as follows: This yields the newly added top and bottom plate data points for each hydraulic support, thus creating the updated top and bottom plate dataset. ; The newly added top and bottom plate data points include the number, plane coordinates, bottom plate elevation, and coal wall thickness of each hydraulic support; Step 4: Calculate the updated top and bottom plate datasets obtained in Step 3. The ε-neighborhood of each newly added top and bottom plate data point is calculated, and the data points within the ε-neighborhood of each newly added top and bottom plate data point are counted to obtain the dataset corresponding to each newly added top and bottom plate data point. ; Step 5: Determine the data point type of the newly added top and bottom plate data points. If it is a core point, proceed to step 6; if it is a boundary point, proceed to step 7; if it is a noise point, temporarily mark the noise point as noise. Step 6: Check the dataset corresponding to the newly added top and bottom plate data points. If the data point includes other core points, then merge the newly added top and bottom plate data point with the cluster to which the other core points belong, and update the core parameters of the merged cluster; if not, then create a new cluster with the newly added top and bottom plate data point as the center, include the boundary points in its ε-neighborhood into the new cluster, and proceed to step seven. The core parameters of the cluster include the cluster's center coordinates and parameter fluctuation range; Other key points include key points in the historical cluster and newly added key points; Step 7: Calculate the spatial distance between the newly added roof and floor data point and all core points, select the core point with the smallest spatial distance, and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements. If so, assign it to the cluster to which the core point belongs; otherwise, re-select the next nearest core point and determine whether the parameter fluctuation range of the newly added roof and floor data point and the cluster to which the core point belongs meets the parameter fluctuation requirements, until the cluster allocation of the newly added roof and floor data point is completed, thus obtaining the updated refined geological model for mining. The parameter fluctuation requirements include coal thickness fluctuation and elevation fluctuation.

2. The method for updating the fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment as described in claim 1, characterized in that, Between steps four and five, the following step is also included: verifying the marked noise. If the verification passes, the point is converted to a boundary point; otherwise, the noise point is maintained.

3. The method for updating the fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment as described in claim 1, characterized in that, Step two specifically includes the following steps: Step 2.1, calculate the working face correction factor T; in: i is the hydraulic support number, 1≤i≤N, and N is the total number of hydraulic supports on the working face. Let be the roll angle of the i-th hydraulic support, in degrees. L represents the width of the hydraulic support, in meters (m). The floor value of the left-side roadway when located at the working face cut-off point and facing the coal seam, in meters; The floor value of the right-side roadway when located at the working face cut-off point and facing the coal seam, in meters; Step 2.2, calculate the base plate elevation of each hydraulic support. ; Step 2.3: Establish a coordinate system with the starting point of the intake roadway as the origin, the advancing direction as the x-axis, and the working face width direction as the y-axis; calculate the planar coordinates of each hydraulic support based on the arrangement sequence and advancing distance. That is, the base plate spatial coordinates corresponding to each hydraulic support are obtained as follows: .

4. The method for updating the fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment as described in claim 1, characterized in that, The specific steps for step four are as follows: 4.1 Calculate the updated dataset for the top and bottom plates. any point in Calculation points With point Euclidean distance between ; 4.2, European distance Does the following formula apply, and is q a newly added point or a historical valid point? If so, then include the point. ; 4.3 The neighborhood of adjacent hydraulic supports is weighted with a weight of 1.2 to 1.5, and the neighborhood of non-hydraulic supports is weighted with a weight of 1.0 to obtain the points. The set of data points in the ε-neighborhood Thus, the dataset is obtained. .

5. The method for updating the fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment as described in claim 1, characterized in that, Step five specifically includes the following steps: 5.1 Determine whether the newly added top and bottom plate data points obtained in step three satisfy the following formula. If they satisfy the formula, the newly added top and bottom plate data points are core points, and proceed to step six. If they do not satisfy the formula, the newly added top and bottom plate data points are boundary points or noise points, and proceed to step 5.

2. in: To add new top and bottom plate data points The number of data points within a neighborhood of radius ε centered at the origin; This is the minimum number of points after dynamic adjustment; Step 5.2: Determine whether there are core points within the domain of the newly added top and bottom plate data points. If there are, the newly added top and bottom plate data points are boundary points, and proceed to step seven; if not, the newly added top and bottom plate data points are noise points, and proceed to step 5.

3. Step 5.3: Determine whether the newly added top and bottom plate data points corresponding to the three hydraulic supports adjacent to the noise point are all core points or boundary points, and whether the parameter deviation between the noise point and the three adjacent data points meets the allowable range of parameter deviation. If yes, then the noise point is identified as a boundary point and proceed to step seven; otherwise, the noise point is temporarily marked as noise. The allowable range of parameter deviations includes coal thickness deviation and elevation deviation, wherein the coal thickness deviation is ≤0.3m and the elevation deviation is ≤0.2m.

6. The method for updating the fine geological model of longwall mining based on monitoring data of fully mechanized mining equipment as described in claim 1, characterized in that, In step six, merging the newly added top and bottom plate data points with the clusters to which the other core points belong also requires meeting one of the following two conditions: First, the hydraulic supports corresponding to the two clusters are adjacent supports, and the parameter fluctuations of the core points within the clusters are consistent. Second, the two clusters are located in the same mining advance section, and the spatial distribution of the clusters is consistent with the undulation trend of the roadway floor.

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