Remote visualized coal mining monitoring analysis and control system

Abstract

The present application belongs to the technical field of coal mining monitoring analysis and control, and specifically discloses a remote visual coal mining monitoring analysis and control system, which comprises a cutting area monitoring module, a cutting track generating module, an obstacle avoidance track generating module, a database and a cutting correction executing module. The present application constructs a three-dimensional geological model by fusing multi-source geological data such as methane concentration distribution, fissure density and rock hardness, realizes accurate identification of methane accumulation area, fissure expansion risk and hard rock mutation, predicts methane diffusion path in combination with wind speed and direction data, significantly reduces the incidence of methane combustion and explosion accidents, reduces the safety warning response time, simultaneously corrects the obstacle avoidance of the spatial boundary of the methane accumulation area by monitoring the methane concentration distribution data of the cutting track prediction path of the roadheader during operation in real time, and generates an obstacle avoidance cutting track, accurately defines the three-dimensional spatial range of the methane accumulation area, and avoids the risk of the cutting head of the roadheader entering the risk area.

Description

Technical Field

[0001] This invention belongs to the field of coal mine mining monitoring, analysis and control technology, and relates to a remote visual coal mine mining monitoring, analysis and control system. Background Technology

[0002] As a crucial link in energy production, coal mining safety and efficiency have always been core concerns for the industry. During tunneling machine cutting operations, complex geological conditions such as uneven rock hardness, varying fracture distribution, and the risk of methane accumulation pose severe challenges to equipment operational stability and safety.

[0003] For example, Chinese invention patent CN117348500A discloses an automated control method and system for fully mechanized coal mining faces, relating to the field of coal mine data acquisition and control technology. The method includes the following steps: establishing a coal mine face mining analysis and decision-making platform; collecting various data from the coal mine face to establish a three-dimensional dynamic coal seam model, and simulating the optimal path of the coal mining machine during operation based on the three-dimensional dynamic coal seam model; establishing an evaluation model based on the optimal path results to predict changes in the working face morphology, and judging the probability of collapse risk based on the changes; converting the optimal path results into coordinate information, feeding it back to the analysis and decision-making platform for calculation and analysis, and then outputting instructions to adjust the status of the hydraulic pump station, conveyor, and hydraulic supports; and using the simulation results to perform coordinated control of the coal mine face mining. This invention enables automated control equipment to mine according to plan, reduces human error, and achieves automated mining of the working face through coordinated control of various equipment.

[0004] The existing technologies mentioned above have the following shortcomings: 1. Existing technologies only construct three-dimensional models based on coal seam morphology, without integrating key safety parameters such as methane concentration distribution, fracture density, and rock layer hardness for comprehensive analysis. This results in significant blind spots in safety risk prevention and control, a lack of geological adaptability in the adjustment of cutting parameters, and the absence of a multi-dimensional risk assessment system. Furthermore, the spatial resolution and data-driven capabilities of the three-dimensional models are insufficient, making it difficult to support the safety and efficiency of cutting operations under complex geological conditions.

[0005] 2. Existing technologies only adjust the status of equipment such as pump stations and conveyors based on the optimal path coordinate information, but do not involve the adaptive adjustment of the core parameters of the cutting head. This results in a significant decrease in cutting efficiency due to the mismatch between parameters and geological conditions. The equipment faces risks such as overload burnout and cutting tooth breakage due to the lack of load and vibration protection mechanisms. Furthermore, it is impossible to adjust parameters synchronously to reduce risks in response to safety hazards such as methane accumulation areas. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background technology, a remote visual coal mine mining monitoring, analysis and control system is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: This invention provides a remote visual coal mine mining monitoring, analysis and control system, including: a cutting area monitoring module, which monitors the methane concentration distribution data, geological data, equipment position data and wind speed and direction data of the cutting area before the tunneling machine operates.

[0008] The cutting trajectory generation module constructs a three-dimensional geological model based on methane concentration distribution data, geological data, and wind speed and direction data, and marks the rock layer hardness, fracture density, and spatial boundaries of the methane accumulation area. Then, it combines the equipment pose data and the final mining location to generate a dynamic cutting trajectory prediction path.

[0009] The obstacle avoidance trajectory generation module monitors the methane concentration distribution data of the predicted cutting trajectory path during tunneling machine operation and the real-time position of the tunneling machine. If the methane concentration is higher than the preset methane concentration threshold, the spatial boundary of the methane accumulation area is dynamically corrected, and an obstacle avoidance cutting trajectory is generated.

[0010] The database stores a mapping table between rock layer hardness and cutting speed.

[0011] The cutting and correction execution module monitors the geological data, equipment position data, and operating status parameters of the obstacle avoidance and cutting trajectory of the tunneling machine in real time. It calculates the adjustment speed, feed speed, and cutting angle of the tunneling machine's cutting head, and generates a cutting control command set, which is then transmitted to the tunneling machine for execution.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention constructs a three-dimensional geological model by integrating multi-source geological data such as methane concentration distribution, fissure density and rock layer hardness, so as to accurately identify methane accumulation areas, fissure expansion risks and hard rock mutations, and predicts methane diffusion paths by combining wind speed and wind direction data, which significantly reduces the incidence of methane combustion and explosion accidents and reduces the safety early warning response time.

[0013] (2) This invention corrects the spatial boundary of the methane accumulation area by real-time monitoring of the methane concentration distribution data of the predicted path of the cutting trajectory during tunneling machine operation, and generates an obstacle avoidance cutting trajectory, accurately delineating the three-dimensional spatial range of the methane accumulation area, thus avoiding the tunneling machine cutting head from accidentally entering the methane risk area.

[0014] (3) By using geological data and equipment position data of the obstacle avoidance and cutting trajectory during tunneling machine operation, the present invention dynamically adjusts the rotation speed, feed speed and cutting angle of the tunneling machine cutting head, realizes the depth adaptation of cutting parameters with rock hardness, fracture density and fracture direction, and significantly improves the cutting speed. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention.

[0017] Figure 2 This is a schematic diagram showing the connection steps of the three-dimensional geological model construction process of the present invention.

[0018] Figure 3 This is a schematic diagram showing the connection steps of the truncation control instruction set generation process of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 As shown, the present invention provides a remote visual coal mining monitoring, analysis and control system, which includes: a cutting area monitoring module, a cutting trajectory generation module, an obstacle avoidance trajectory generation module, a database and a cutting correction execution module.

[0021] In the above, the cutting trajectory generation module is connected to the cutting area monitoring module and the obstacle avoidance trajectory generation module, respectively. The obstacle avoidance trajectory generation module is also connected to the database and the cutting correction execution module, respectively.

[0022] The cutting area monitoring module monitors the methane concentration distribution data, geological data, equipment position data, and wind speed and direction data of the cutting area before the tunneling machine operates.

[0023] It should be added that the methane concentration distribution data is obtained by monitoring a methane sensor installed at the front end of the tunnel boring machine's cutting head. The geological data includes geological interfaces, rock layer hardness, fracture density, and fracture direction. The geological interfaces are obtained by monitoring a ground-penetrating radar installed at the front end of the tunnel boring machine's cutting head and a laser scanner at the front end of the machine body. The rock layer hardness is obtained by monitoring a pressure penetrometer installed on the side of the tunnel boring machine's cutting head. The fracture density and fracture direction are obtained by monitoring an ultrasonic fracture detector installed on the tunnel boring machine's cutting head. The equipment attitude data is obtained by using a laser positioning device installed on the top of the tunnel boring machine to obtain the attitude angle of the tunnel boring machine, and the real-time position of the tunnel boring machine is located in real time through an inertial navigation system. The attitude angle and real-time position of the tunnel boring machine's cutting head are used as the attitude data.

[0024] The cutting trajectory generation module constructs a three-dimensional geological model based on methane concentration distribution data, geological data, and wind speed and direction data, and marks the rock layer hardness, fracture density, and spatial boundary of the methane accumulation area. Then, it combines the equipment pose data and the final mining location to generate a dynamic cutting trajectory prediction path.

[0025] Please see Figure 2 As shown, exemplarily, the construction of the three-dimensional geological model includes: Q1, dividing the cut-off region into sub-regions based on the geological interfaces in the geological data.

[0026] It should be added that the geological interface refers to the boundary between geological bodies with different lithologies, structures, or physical and mechanical properties within the cut area during the excavation of coal mine roadways. Specifically, it includes strata boundaries, tectonic boundaries, and weathering boundaries. The spatial morphology of these interfaces directly determines the geological heterogeneity of the cut area and is the core basis for dividing differentiated cut sub-regions.

[0027] When dividing the geological interface into sub-regions, the key features such as spatial coordinates, dip angle, and dip direction of the geological interface are first obtained using a ground-penetrating radar at the front of the cutting head and a laser scanner at the front of the machine body. Then, based on the dip angle and spatial distribution of the interface, it is divided along the tunneling direction and cross-section: Longitudinal division: For inclined interfaces with a dip angle >15°, the projection line of the interface in the tunneling direction is used as the boundary, dividing the cutting area into longitudinal sub-regions with different geological characteristics, with transition zones reserved between adjacent sub-regions. Lateral division: For horizontal or gently dipping interfaces, the tunnel cross-section is divided into top, middle, and bottom lateral sub-regions according to the interface elevation, thereby ensuring relatively uniform geological parameters within each sub-region.

[0028] Q2. Select the maximum rock layer hardness of each sub-region at each spatial point from the geological data as the rock layer hardness of each sub-region.

[0029] Q3. Extract the fracture density and fracture direction of each sub-region at each spatial point from the geological data to perform fracture characteristic analysis and obtain the fracture density of each sub-region.

[0030] Furthermore, the analysis of the fracture density in each sub-region includes: Q3-1, identifying the dominant direction based on the fracture direction of each sub-region, and generating a group of dominant directions.

[0031] Q3-2. For cracks within each dominant direction group, calculate the average crack density within each dominant direction group, and select the highest average crack density as the crack density of each sub-region.

[0032] In one specific embodiment, taking sub-region A within the cut-off area of ​​a coal mine roadway as an example, crack data of 100 spatial points in the area are obtained by an ultrasonic crack detector and a high-definition explosion-proof camera. The crack direction and crack density are extracted. Cracks with a dip angle difference of ≤15° are considered to be in the same direction, and at least 3 cracks in the same direction are defined as a dominant direction group.

[0033] Q4. Compare the methane concentration at each spatial point in each sub-region of the methane concentration distribution data with the preset methane concentration threshold, and select the spatial points in each sub-region where the concentration exceeds the standard as the excess points.

[0034] Q5. Count the number of points exceeding the standard and construct the spatial boundary of the methane accumulation area based on the preset safety radius.

[0035] Furthermore, the spatial boundary for constructing the methane accumulation zone includes: Q5-1, if there is only a single point exceeding the standard, then a three-dimensional spatial sphere is constructed with the point exceeding the standard as the center and a preset safety radius, which serves as the boundary of the methane accumulation zone.

[0036] Q5-2. If there are multiple points exceeding the standard, merge the adjacent three-dimensional spatial spheres through spatial clustering analysis to form the boundary of the methane accumulation area.

[0037] It should be added that the process of forming the boundary of the methane accumulation zone is as follows: The three-dimensional coordinates of multiple methane exceedance points are obtained. Using a spatial clustering algorithm with a preset distance threshold, spatially adjacent exceedance points are grouped into the same cluster, ensuring that the distance between any two points within a cluster does not exceed the clustering threshold. For each cluster, the smallest enclosing region of all exceedance points in that cluster is used as the initial boundary of the methane accumulation zone, replacing the simple superposition of independent safety spheres, thus forming a continuous and complete risk area.

[0038] To avoid boundary redundancy or breakage caused by independently handling out-of-range points, this method truly reflects the spatial continuity of methane accumulation, reduces the computational load of subsequent airflow data fitting, improves the efficiency of dynamic boundary expansion, and ensures the fusion of boundaries of adjacent risk points through clustering, preventing the truncation trajectory from mistakenly entering the risk gap due to "missed neighboring areas".

[0039] Q6. Construct a three-dimensional geological model based on the rock layer hardness, fracture density, and spatial boundary of the methane accumulation zone in each sub-region.

[0040] This invention constructs a three-dimensional geological model by integrating multi-source geological data such as methane concentration distribution, fracture density, and rock layer hardness. This model enables accurate identification of methane accumulation zones, fracture propagation risks, and sudden changes in hard rock. Combined with wind speed and direction data, it predicts methane diffusion paths, significantly reducing the incidence of methane combustion and explosion accidents and shortening the safety warning response time.

[0041] For example, the generation of the dynamic truncation trajectory prediction path includes: extracting the maximum methane concentration from the methane concentration of each spatial point in each sub-region, comparing it with a preset methane concentration threshold, and if the maximum methane concentration of the sub-region is greater than or equal to the preset methane concentration threshold, then the sub-region is marked as a warning region and removed; otherwise, the maximum methane concentration of the sub-region is matched with the methane concentration interval corresponding to each methane risk score to obtain the methane risk score of the sub-region.

[0042] Similarly, the rock hardness score and fracture density score of the sub-region were obtained by analyzing the methane risk score.

[0043] The safety risk score of the sub-region is obtained by weighted fusion of the methane risk score, rock hardness score and fracture density score.

[0044] It should be added that the core logic followed by the weighted fusion is that the weight of methane risk is greater than that of rock hardness, which is greater than that of fracture density. This is because methane is a flammable and explosive gas; when its concentration exceeds the standard, it can explode upon contact with a spark, leading to significant casualties and equipment damage. It is the most urgent and serious risk in coal mining, hence its highest weight. Rock hardness directly determines the load on the cutting head, equipment wear, and energy consumption. Long-term overload may cause equipment failure or shutdown, but the risk consequences are gradual safety hazards rather than immediate fatal threats, hence its second highest weight. Fracture density reflects the integrity of the rock strata. High fracture density may lead to surrounding rock instability, spalling, or collapse, but such risks usually develop slowly and can be reinforced in advance through support measures. Furthermore, the impact is mostly limited to localized areas and will not immediately cause catastrophic consequences, hence its lowest weight. For ease of analysis, the weights for methane risk, rock hardness, and fracture density are set to 0.5, 0.3, and 0.2, respectively.

[0045] The safety risk score of the sub-region is compared with the preset safety risk score threshold, and the sub-regions with a score lower than the preset safety risk score threshold are selected to form a set of candidate regions for the cutting trajectory.

[0046] Based on the equipment pose data of the tunneling machine and the final mining location, a dynamic cutting trajectory prediction path is generated in the candidate area set using a path planning algorithm.

[0047] It should be added that the generation process of the dynamic cutting trajectory prediction path is as follows: the real-time position of the tunneling machine in the tunneling machine pose data is used as the starting point of the path, the final mining position is used as the ending point of the path, and the current direction of travel determined by the attitude angle of the tunneling machine in the tunneling machine pose data is used as the starting direction. Multiple feasible prediction paths are generated in the candidate area set through the path planning algorithm, and then the shortest feasible prediction path is selected as the dynamic cutting trajectory prediction path.

[0048] It's worth noting that the reason for first removing methane-concentrated areas before performing multi-factor safety analysis during dynamic cutting trajectory prediction path generation is that these areas directly pose a gas explosion risk and are considered "prohibited work zones." This pre-emptive removal mechanism excludes such areas from trajectory planning, preventing the cutting head from accidentally entering high-risk zones. If included in subsequent assessments, the high methane risk might be diluted by lower geological risks. Pre-emptive removal ensures that the "safety red line" cannot be crossed, eliminating major accident hazards. After removing the areas exceeding the limit, the methane concentration in the remaining sub-regions is compliant. At this point, only geological risks such as rock hardness and fracture density need to be assessed to avoid interference from methane risks on the model. Areas exceeding the methane limit are inherently impassable; including them in the planning would increase unnecessary computational effort. Removing them reduces algorithm complexity and improves trajectory generation speed.

[0049] The obstacle avoidance trajectory generation module monitors the methane concentration distribution data of the predicted cutting trajectory path during tunneling machine operation and the real-time position of the tunneling machine. If the methane concentration is higher than the preset methane concentration threshold, the spatial boundary of the methane accumulation area is dynamically corrected, and an obstacle avoidance cutting trajectory is generated.

[0050] For example, the dynamic correction of the spatial boundary of the methane accumulation area includes marking points in the truncation trajectory prediction path where the methane concentration is higher than a preset methane concentration threshold as risk points.

[0051] A three-dimensional sphere is constructed with the risk point as the center and a preset safety radius as the spatial boundary of the initial methane accumulation area.

[0052] The product of the real-time wind speed at the risk point and the preset diffusion time in the wind speed and direction data is used as the expansion radius of the risk point.

[0053] It should be added that the preset diffusion time was obtained through gradient descent optimization experiments using historical coal mining datasets.

[0054] Using the real-time wind direction of the risk point in the wind speed and direction data as the wind speed expansion direction, and combining it with the expansion radius, the spatial boundary of the initial methane accumulation area is dynamically expanded to obtain the spatial boundary of the methane accumulation area.

[0055] For example, generating the obstacle avoidance cutting trajectory includes: removing the spatial boundary of the methane accumulation area from the set of candidate cutting trajectory areas based on the spatial boundary of the methane accumulation area, to obtain the set of remaining candidate cutting trajectory areas.

[0056] Using the real-time position of the tunneling machine as the starting point and the final mining position as the ending point, a path planning algorithm is used to plan each feasible obstacle avoidance path in the set of candidate areas for the remaining cutting trajectory, and the shortest obstacle avoidance path is selected as the obstacle avoidance cutting trajectory.

[0057] This invention corrects the spatial boundary of the methane accumulation area by real-time monitoring of the methane concentration distribution data of the predicted cutting trajectory during tunneling machine operation, and generates an obstacle-avoidance cutting trajectory, accurately delineating the three-dimensional spatial range of the methane accumulation area, thus preventing the tunneling machine cutting head from accidentally entering the methane risk area.

[0058] The database stores a mapping table between rock layer hardness and cutting speed, and a mapping table between fracture density and feed rate.

[0059] It should be added that the mapping relationship between rock hardness and cutting speed is shown in Table 1, and the mapping relationship between fracture density and feed rate is shown in Table 2.

[0060] Table 1: Mapping Relationship between Rock Strata Hardness and Cutting Rotation Speed

[0061]

[0062] The higher the hardness of the rock strata, the greater the compressive strength of the rock. It is necessary to increase the cutting speed to increase the impact frequency of the cutting teeth on the rock strata, reduce the single cutting load, and avoid the cutting head from stopping or being damaged due to excessive resistance.

[0063] Table 2: Mapping Relationship between Fracture Density and Feed Rate

[0064]

[0065] The higher the fracture density, the greater the degree of rock fragmentation, and the more likely vibration, cutting tooth jamming, or rock splashing will occur during cutting. Therefore, it is necessary to reduce the single cutting load by reducing the feed speed, protect the equipment, and improve the cutting surface accuracy.

[0066] The cutting correction execution module monitors in real time the geological data, equipment position data, and operating status parameters of the obstacle avoidance cutting trajectory of the tunneling machine during operation, calculates the adjustment speed, adjustment feed speed, and adjustment cutting angle of the tunneling machine's cutting head, and generates a cutting control command set and transmits it to the tunneling machine for execution.

[0067] It should be added that the geological data includes rock hardness and fracture density, which are obtained in the same way as the geological data mentioned above, and will not be repeated here. The equipment position data includes the cutting speed, feed speed and cutting angle of the tunneling machine cutting head. The cutting speed is obtained by monitoring the speed sensor of the cutting motor. The feed speed is calculated by the displacement sensor of the tunneling machine's feed mechanism, reflecting the advancing speed of the cutting head along the tunneling direction. Specifically, a magnetostrictive displacement sensor is installed on the tunneling machine's feed cylinder or lead screw to monitor the displacement change of the feed mechanism in real time. The feed speed is calculated by differentiation: speed = displacement change / time interval. The cutting angle is obtained by monitoring the tilt sensor installed on the cutting head.

[0068] It should be added that the operating status parameters include the real-time current and vibration intensity of the tunneling machine. The real-time current is obtained through a current sensor, and the vibration intensity is obtained through an acceleration sensor.

[0069] Please see Figure 3 As shown, exemplarily, the generation of the cutting control instruction set includes: G1, calculating the load rate of the tunneling machine based on the real-time current of the tunneling machine in the operating status parameters, and comparing it with a preset load rate threshold to obtain a comparison result.

[0070] It should be added that the load rate is calculated by extracting the rated current of the tunneling machine from its technical manual and using the ratio of the real-time current to the rated current as the load rate of the tunneling machine.

[0071] G2. Based on the comparison results and the rock hardness of the current trajectory point in the geological data of the obstacle avoidance and cutting trajectory during tunneling machine operation, determine the adjustment speed of the tunneling machine cutting head.

[0072] Furthermore, the determination of the adjustment speed of the tunneling machine cutting head includes: G2-1, if the load rate of the tunneling machine is greater than the preset load rate threshold, triggering overload protection, and using the preset safe speed as the adjustment speed.

[0073] G2-2. If the load rate of the tunneling machine is less than or equal to the preset load rate threshold, extract the mapping relationship table between rock hardness and cutting speed from the database.

[0074] G2-3. Import the rock layer hardness of the current trajectory point into the mapping table to obtain the appropriate cutting speed for the rock layer hardness of the current trajectory.

[0075] G2-4. The difference between the real-time speed and the adapted cutting speed is taken as the speed difference. The speed difference is compared with the preset speed deviation threshold. If the speed difference is less than the preset speed deviation threshold, the real-time speed is taken as the adjustment speed; otherwise, the adapted cutting speed is taken as the adjustment speed.

[0076] It should be added that the preset speed deviation threshold is dynamically adjusted based on the tunneling machine's historical operating data.

[0077] G3. Similarly, the adjustment feed speed of the tunneling machine cutting head is determined by the same method as the determination of the adjustment speed of the tunneling machine cutting head.

[0078] It should be added that the analysis process for adjusting the feed speed of the tunneling machine cutting head is as follows: the vibration intensity is calculated based on the real-time vibration signal of the tunneling machine in the operating status parameters.

[0079] It should be added that the vibration intensity calculation process is as follows: Vibration acceleration signals in the forward direction are monitored by acceleration sensors installed on the tunneling machine. , Number the vibration acceleration signal. Then the effective value of vibration The calculation process is as follows: ,in It represents the number of vibration acceleration signals, and uses the effective value of vibration as the vibration intensity, reflecting the severity of vibration in the forward direction during the cutting process.

[0080] If the vibration intensity of the tunneling machine exceeds the preset vibration intensity threshold, vibration protection is triggered, and the preset safe feed speed is used as the adjustment feed speed.

[0081] If the vibration intensity of the tunneling machine is less than or equal to the preset vibration intensity threshold, the mapping relationship table between fracture density and feed speed is extracted from the database. The fracture density of the current trajectory point in the geological data of the obstacle avoidance and cutting trajectory is imported into the mapping relationship table to obtain the adapted feed speed of the tunneling machine.

[0082] The difference between the real-time feed rate and the adapted feed rate is taken as the feed rate difference. The feed rate difference is compared with the preset feed rate difference. If the feed rate difference is less than the preset feed rate difference, the real-time feed rate is taken as the adjusted feed rate; otherwise, the adapted feed rate is taken as the adjusted feed rate.

[0083] G4. Extract the theoretical cutting angle of the tunneling machine cutting head from the obstacle avoidance cutting trajectory. Analyze the deviation between the actual cutting angle and the theoretical cutting angle of the tunneling machine in the equipment pose data to obtain the adjusted cutting angle of the tunneling machine cutting head.

[0084] Furthermore, the analysis of adjusting the cutting angle includes: G4-1, subtracting the theoretical cutting angle of the tunneling machine cutting head from the actual cutting angle to obtain the angle difference of the tunneling machine cutting head.

[0085] G4-2. Compare the angle difference of the tunneling machine cutting head with the set reference angle difference threshold. If the angle difference is greater than the set reference angle difference threshold, the theoretical cutting angle is used as the adjusted cutting angle; otherwise, the actual cutting angle is used as the adjusted cutting angle.

[0086] G5. Based on the adjustment of the cutting speed, feed speed and cutting angle of the tunneling machine cutting head, generate a cutting control command set.

[0087] This invention utilizes geological data and equipment position data from the obstacle avoidance and cutting trajectory of the tunneling machine during operation to dynamically adjust the rotational speed, feed speed, and cutting angle of the tunneling machine's cutting head. This achieves depth adaptation of cutting parameters to rock hardness, fracture density, and fracture direction, significantly improving the cutting speed.

[0088] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications or additions should fall within the protection scope of the present invention.

Claims

1. A remote visualized coal mining monitoring analysis control system, characterized in that: The system comprises: A cutting area monitoring module for monitoring methane concentration distribution data, geological data, equipment pose data and wind speed and direction data of the cutting area before the operation of the tunneling machine; A cutting trajectory generation module for constructing a three-dimensional geological model based on the methane concentration distribution data, the geological data and the wind speed and direction data, labeling the rock hardness, the fracture density and the spatial boundary of the methane accumulation area, and then generating a dynamic cutting trajectory prediction path in combination with the equipment pose data and the final mining location; The generation of the dynamic cutting trajectory prediction path comprises: Extracting the maximum methane concentration from the methane concentration of each spatial point in each sub-region, comparing it with the preset methane concentration threshold value, and if the maximum methane concentration of the sub-region is greater than or equal to the preset methane concentration threshold value, marking the sub-region as a warning area and eliminating it, otherwise, matching and analyzing the maximum methane concentration of the sub-region with the methane concentration interval corresponding to each methane risk score to obtain the methane risk score of the sub-region; The rock hardness score and the fracture density score of the sub-region are analyzed in the same way as the analysis method of the methane risk score; The methane risk score, the rock hardness score and the fracture density score of the sub-region are weighted and fused to obtain the safety risk score of the sub-region; Comparing the safety risk score of the sub-region with the preset safety risk score threshold value, and screening the sub-regions less than the preset safety risk score threshold value to form a cutting trajectory candidate region set; Based on the equipment pose data of the tunneling machine and the final mining location, a dynamic cutting trajectory prediction path is generated in the candidate region set through a path planning algorithm; An obstacle avoidance trajectory generation module for real-time monitoring of the methane concentration distribution data of the cutting trajectory prediction path during the operation of the tunneling machine and the real-time position of the tunneling machine, and if the methane concentration is higher than the preset methane concentration threshold value, dynamically correcting the spatial boundary of the methane accumulation area and generating an obstacle avoidance cutting trajectory; The generation of the obstacle avoidance cutting trajectory comprises: According to the spatial boundary of the methane accumulation area, eliminating the methane accumulation area spatial boundary in the cutting trajectory candidate region set to obtain a remaining cutting trajectory candidate region set; Taking the real-time position of the tunneling machine as the starting point and the final mining location as the terminal point, planning each obstacle avoidance feasible path in the remaining cutting trajectory candidate region set through a path planning algorithm, and selecting the shortest obstacle avoidance path as the obstacle avoidance cutting trajectory; A database for storing a mapping relationship table of rock hardness and cutting rotational speed; A cutting correction execution module for real-time monitoring of the geological data, equipment pose data and running state parameters of the obstacle avoidance cutting trajectory during the operation of the tunneling machine, calculating the adjustment rotational speed, adjustment feed speed and adjustment cutting angle of the cutting head of the tunneling machine, generating a cutting control instruction set and transmitting it to the tunneling machine for execution.

2. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 1, characterized in that: The construction of the three-dimensional geological model comprises: Q1, dividing the cutting area into sub-regions based on the geological interface in the geological data; Q2, selecting the maximum value of the rock hardness of each spatial point in each sub-region from the geological data as the rock hardness of each sub-region; Q3, extracting the fracture density and fracture direction of each spatial point in each sub-region from the geological data for fracture feature analysis to obtain the fracture density of each sub-region; Q4, compare the methane concentration of each sub-region at each spatial point in the methane concentration distribution data with the preset methane concentration threshold value, and screen the spatial points with concentration exceeding the standard in each sub-region as the exceeding points; Q5, count the number of exceeding points, and construct the spatial boundary of the methane accumulation zone combined with the preset safety radius; Q6, construct a three-dimensional geological model based on the rock hardness, fracture density of each sub-region and the spatial boundary of the methane accumulation zone.

3. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 2, characterized in that: The analysis of the fracture density of each sub-region includes: identifying the dominant direction based on the fracture direction of each sub-region, generating each dominant direction group; for the fractures in each dominant direction group, calculate the average fracture density in each dominant direction group, and select the highest average fracture density as the fracture density of each sub-region.

4. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 2, characterized in that: The construction of the spatial boundary of the methane accumulation zone includes: if there is only a single exceeding point, a three-dimensional space sphere is constructed with the exceeding point as the center and the preset safety radius, and is taken as the boundary of the methane accumulation zone; if there are multiple exceeding points, adjacent three-dimensional space spheres are combined through spatial clustering analysis to form the boundary of the methane accumulation zone.

5. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 1, characterized in that: The dynamic correction of the spatial boundary of the methane accumulation zone includes: marking the points with methane concentration higher than the preset methane concentration threshold value in the cutting trajectory prediction path as risk points; constructing a three-dimensional space sphere with the risk points as the center and the preset safety radius as the initial methane accumulation zone spatial boundary; calculating the product of the real-time wind speed of the risk point in the wind speed and direction data and the preset diffusion time as the expansion radius of the risk point; taking the real-time wind direction of the risk point in the wind speed and direction data as the wind speed expansion direction, and dynamically expanding the initial methane accumulation zone spatial boundary combined with the expansion radius to obtain the methane accumulation zone spatial boundary.

6. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 1, characterized in that: The generation of the cutting control instruction set includes: G1, calculating the load rate of the heading machine based on the real-time current of the heading machine in the running state parameter, and comparing it with the preset load rate threshold to obtain the comparison result; G2, determining the adjustment speed of the heading machine cutting head according to the comparison result combined with the rock hardness of the current trajectory point in the obstacle avoidance cutting trajectory geological data when the heading machine is working; G3, determining the adjustment speed of the heading machine cutting head according to the adjustment speed of the heading machine cutting head; G4, extracting the theoretical cutting angle of the heading machine cutting head from the obstacle avoidance cutting trajectory, and performing deviation analysis on the actual cutting angle of the heading machine in the device pose data and the theoretical cutting angle to obtain the adjustment cutting angle of the heading machine cutting head; G5, generating the cutting control instruction set based on the adjustment speed, adjustment speed and adjustment cutting angle of the heading machine cutting head.

7. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 6, characterized in that: The determination of the adjustment speed of the heading machine cutting head includes: if the load rate of the heading machine is greater than the preset load rate threshold, triggering overload protection, and taking the preset safety speed as the adjustment speed; if the load rate of the heading machine is less than or equal to the preset load rate threshold, extracting the mapping relationship table of rock hardness and cutting speed from the database; importing the rock hardness of the current trajectory point into the mapping relationship table to obtain the adaptive cutting speed of the current trajectory rock hardness; The difference between the real-time rotating speed and the adaptive cutting rotating speed is taken as a rotating speed difference, and the rotating speed difference is compared with a preset rotating speed deviation threshold value; if the rotating speed difference is less than the preset rotating speed deviation threshold value, the real-time rotating speed is taken as the adjusting rotating speed; otherwise, the adaptive cutting rotating speed is taken as the adjusting rotating speed.

8. A remote visualized coal mining monitoring, analyzing and controlling system according to claim 6, characterized in that: The analysis of the adjusting cutting angle comprises: The theoretical cutting angle of the heading machine cutting head is subtracted from the actual cutting angle to obtain an angle difference of the heading machine cutting head; The angle difference of the heading machine cutting head is compared with a set reference angle difference threshold value; if the angle difference is greater than the set reference angle difference threshold value, the theoretical cutting angle is taken as the adjusting cutting angle; otherwise, the actual cutting angle is taken as the adjusting cutting angle.

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