A coal transportation control system for large-angle rotary mining in fully mechanized longwall faces

Abstract

This invention belongs to the field of coal transportation control technology, specifically disclosing a coal transportation control system for large-angle rotary mining in a fully mechanized longwall face. The system includes a primary overlap change judgment module, a secondary overlap change judgment module, an overlap change determination module, and an overlap change control terminal. By setting two overlap angle change judgments, when a change is deemed necessary, the invention determines the change direction and proportion based on relevant factors, generating the changed overlap angle. This effectively solves the problems in existing technologies, such as the inability to adapt to dynamic changes in overlap angles, lack of linkage between control and the mining environment, and failure to achieve coordinated control of coal flow and overlap angles. It achieves adaptation to dynamic changes in overlap angles during rotary mining, strengthens the linkage between transportation control and the mining environment, and realizes coordinated control of coal flow and equipment overlap angles, thereby improving the stability of the coal transportation process and the efficiency and safety of coal mining.

Description

Technical Field

[0001] This invention belongs to the field of coal transportation control technology, and more specifically, relates to a coal transportation control system for large-angle rotary mining in fully mechanized longwall faces. Background Technology

[0002] Many mines have complex geological conditions, such as faults, folds, and large variations in coal seam dip angles. In the mining of these fully mechanized longwall faces, traditional straight-line mining methods are often unsustainable, requiring the use of special techniques such as rotary mining to bypass or adapt to these geological obstacles. To ensure mining progress and stability, transportation needs to be controlled.

[0003] Existing technologies, such as the control method, control device and coal transportation system for a coal feeder disclosed in Chinese invention patent application No. 202211625432.2, obtain the actual operating current value of the main motor of the upstream target belt conveyor of the coal feeder, determine the target speed of the coal feeder based on the current value and adjust it, so as to balance the transport volume of the upstream and downstream belt conveyors.

[0004] Existing technologies, such as the belt conveyor system for coal disclosed in Chinese invention patent application No. 202510600875.3, identify the specifications of the transported materials through a camera module, mark abnormal materials, remove abnormal materials using a restriction module and an operation module, and adjust the conveying speed according to the material conveying status through a control module.

[0005] The first existing technical solution addresses overload issues by dynamically balancing the transport volume based on the current data of upstream and downstream equipment. The second existing technical solution addresses material spillage / falling issues by identifying material specifications and handling abnormal materials. Clearly, both aim to improve the stability of the coal transportation process. However, the overlap angle between the transfer machine and the conveyor during coal transportation directly affects coal transmission and the solutions to the problems addressed in the existing technical solutions. Currently, this detail receives less attention, and the following issues remain: 1. It cannot adapt to the dynamic changes in the overlap angle between the transfer machine and the conveyor during rotary mining, resulting in the inability to achieve the expected results in resolving coal flow jamming or spillage.

[0006] 2. The lack of geological data collection in the tunnels and the failure to link transportation control with the mining environment resulted in a certain deficiency in the targeting and effectiveness of the control measures.

[0007] 3. Failure to consider the coordinated control of the coal flow and equipment overlap angle can easily lead to coal accumulation in the receiving trough or coal flow deviation, increasing the probability of triggering unstable coal transmission. Summary of the Invention

[0008] In view of this, in order to solve the above problems, a coal transportation control system for large-angle rotary mining in fully mechanized longwall faces is proposed.

[0009] The objective of this invention can be achieved through the following technical solution: This invention provides a coal transportation control system for large-angle rotating mining in a fully mechanized longwall face. The system includes: a module for judging overlap changes, which collects the operating images of the transfer machine and the conveyor and identifies the horizontal projection distance between the unloading center and the receiving center and the vertical height difference between the unloading point and the receiving point, and judges the overlap angle change by combining the roadway slope and the roadway surface image.

[0010] The overlap change secondary judgment module, when it is judged that no change is required, collects coal flow and conveyor vibration frequency in real time, and combines the operation image to analyze the accuracy of coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough, and performs secondary overlap angle change judgment.

[0011] The overlap change determination module determines the direction and value of the overlap angle change when it is determined to be a change, taking into account the accuracy of the coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough.

[0012] The overlap change control terminal controls the overlap mechanism of the transfer machine and the transport machine to adjust the overlap angle according to the changed angle value.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention sets two judgments on the change of overlap angle. When it is determined that a change is needed, the change direction and proportion are determined by comprehensively considering relevant factors, and the change overlap angle is generated. It can effectively adapt to the dynamic changes of the overlap angle between the transfer machine and the conveyor in rotary mining, solve the problem that the coal flow jamming or spillage caused by the dynamic change of angle cannot achieve the expected solution, realize the smoothness of coal flow transmission, reduce the phenomenon of coal flow jamming and spillage, and improve the stability of coal transportation.

[0014] (2) This invention links transportation control with the mining environment by collecting technical features such as roadway slope and roadway surface images. Through this technical means, the situation where roadway geological data was not collected and transportation control was not linked with the mining environment has been changed, improving the pertinence and effectiveness of overlap angle control. This allows transportation control to be adjusted according to the geological data of the actual mining environment, improving the pertinence and effectiveness of control, and enabling the coal transportation system to better adapt to the complex mining environment.

[0015] (3) When the overlap angle is determined not to change, the present invention performs a secondary judgment on the overlap angle change by real-time acquisition of coal flow rate and conveyor vibration frequency, combined with analysis of the accuracy of coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough using operation images, thereby achieving coordinated control of the overlap angle between the coal flow and the equipment. This fully considers the problem that coordinated control of the overlap angle between the coal flow and the equipment can easily lead to coal accumulation in the receiving trough or coal flow deviation, reducing the probability of triggering unstable coal transmission and ensuring normal coal flow transmission and stable equipment operation. Attached Figure Description

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0018] Figure 2 This is a schematic diagram of the overall implementation process of the present invention.

[0019] Figure 3 This is a flowchart illustrating the process for determining a change in the overlap angle during a single operation, as described in this invention.

[0020] Figure 4 This is a flowchart for judging the change of the secondary overlap angle in this invention.

[0021] Figure 5 This is a flowchart illustrating the process of determining the direction of overlap angle change in this invention. Detailed Implementation

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] Please see Figure 1 and Figure 2 As shown, the present invention provides a coal transportation control system for large-angle rotating mining in a fully mechanized longwall face. The system includes: a primary judgment module for overlap change, a secondary judgment module for overlap change, a determination module for overlap change, and an overlap change control terminal.

[0024] The overlapping change secondary judgment module is connected to the overlapping change primary judgment module and the overlapping change determination module, respectively, and the overlapping change determination module is connected to the overlapping change control terminal.

[0025] The overlap change judgment module collects the operation images of the transfer machine and the transport machine, identifies the horizontal projection distance between the unloading center and the receiving center and the vertical height difference between the unloading point and the receiving point, and makes a judgment on the overlap angle change by combining the roadway slope and the roadway surface image.

[0026] In one specific embodiment, operational images and tunnel surface images can be acquired using an industrial camera or high-definition camera installed at the unloading end of the transfer machine. An image acquisition card converts the analog signals into digital signals and transmits them to a computer. During the image recognition stage, deep learning-based target detection algorithms, such as YOLO and Faster R-CNN, are used to locate the unloading center and receiving center in the image. By establishing a three-dimensional visual model and combining the intrinsic and extrinsic parameters obtained from camera calibration, the horizontal projection distance between the two points is calculated using triangulation principles. For the vertical height difference, a height reference point can be set on the equipment. Image processing is used to obtain the pixel coordinates of the unloading point and receiving point relative to the reference point, which are then converted into the actual vertical height difference according to the calibrated proportional relationship.

[0027] It should be added that the tunnel slope can be monitored in real time using a dual-axis tilt sensor integrated into the tunnel roof.

[0028] Specifically, please refer to Figure 3 As shown, the judgment of a change in overlap angle includes: A1, importing the current overlap angle settings of the transfer machine and the transport machine.

[0029] A2. Based on the set overlap angle, match the reference value range of horizontal projection distance, vertical height difference, and roadway slope at the corresponding angle.

[0030] A3. Compare the horizontal projection distance between the unloading center and the receiving center, the vertical height difference between the unloading point and the receiving point, and the roadway slope with their respective reference value ranges.

[0031] A4. If a parameter exceeds the reference value range, determine that the overlap angle has changed. If all three are within the corresponding reference value range, divide the roadway surface into sub-regions evenly and extract the image of each sub-region.

[0032] A5. The longitudinal flatness and lateral levelness of each sub-region image are obtained by using image recognition technology, and the surface condition matching degree of the roadway is obtained by weighted summation.

[0033] A6. Based on the degree of fit, determine whether the following conditions are triggered. If yes, determine that the overlap angle does not change; otherwise, determine that the overlap angle does not change. The conditions are as follows: There exists a sub-region where the surface state of the alleyway has a degree of fit greater than or equal to a preset threshold.

[0034] The proportion of the number of sub-regions whose surface condition matching degree of any sub-region is less than a preset threshold and whose surface condition matching degree is within the critical interval of the corresponding preset threshold to the total number of sub-regions exceeds a preset proportion.

[0035] This invention, through the acquisition of technical features such as roadway slope and roadway surface images, links transportation control with the mining environment. This technique addresses the previous situation where roadway geological data was not collected and transportation control was not linked to the mining environment. It improves the targeting and effectiveness of overlap angle control, allowing transportation control to be adjusted based on actual geological data from the mining environment, thus enhancing the targeting and effectiveness of control and enabling the coal transportation system to better adapt to complex mining environments.

[0036] Understandably, the weighting of longitudinal flatness and lateral levelness should comprehensively consider the actual usage requirements of the roadway and the importance of the measurement parameters. Quantitative analysis can be conducted based on engineering experience and actual working conditions. For example, if the roadway is mainly used for transportation, longitudinal flatness has a greater impact on equipment operational stability and can be assigned a higher weight, while lateral levelness has a significant effect on the overall structural stability of the roadway and can be assigned a corresponding weight. For instance, the values ​​for longitudinal flatness and lateral levelness can be 0.6 and 0.4, respectively.

[0037] It should also be noted that the benchmark values ​​for the overlapping angle matching parameters are obtained from a pre-set overlapping parameter mapping table. The data in this table can be derived by integrating several operational steps, including geometric calculations, equipment constraints, standards, and engineering verification. For example, trigonometric functions are used to calculate the horizontal projection distance and vertical height difference. Then, the geometric relationship between the equipment operating slope limit and the actual overlapping angle is considered to determine the allowable range of the roadway slope. Finally, spatial interference is checked using 3D modeling, and after on-site measurement calibration and trial operation verification, the final benchmark value range is determined.

[0038] For example, a scraper conveyor in a coal mine overlaps at a preset angle. The overlap section is 4.5m long. Calculations show a horizontal projection distance of approximately 4.23m and a vertical height difference of approximately 1.54m. This is combined with the maximum slope of the scraper conveyor. Determine that the slope of the tunnel is less than or equal to After verification through 3D modeling and adjustments during on-site trial operation, the relevant benchmark value range was finally calibrated.

[0039] It is important to note that the surface condition of different areas in the tunnel is uneven due to factors such as equipment operation and support variations. Overall analysis can easily mask local anomalies. Segmenting the tunnel into sub-regions allows for precise detection of local protrusions, depressions, and abrupt slope changes, ensuring more accurate assessment of equipment overlap compatibility and timely identification of potential impacts of local areas on the overlap angle.

[0040] Understandingly, longitudinal flatness reflects the undulations of the roadway along the excavation direction, affecting the continuity of material transport during equipment operation. Lateral levelness reflects the horizontal deviation of the roadway cross-section, impacting the lateral stability and alignment accuracy of the equipment. The two affect the equipment overlap angle through different mechanisms; longitudinal anomalies easily lead to material accumulation or spillage, while lateral deviations cause uneven stress and equipment deviation. Separate analysis can clearly distinguish surface defects in different dimensions, accurately determine their impact on the overlap angle, and further improve the targeting and accuracy of angle change judgments.

[0041] Furthermore, the specific identification process for the longitudinal flatness includes: using a total station to obtain the coordinates of the roadway reference surface, and simultaneously acquiring roadway surface images.

[0042] Using the tunnel design axis as a reference, measurement points are marked on the tunnel surface image at regular intervals along the longitudinal direction, and the elevation values ​​of each measurement point relative to the reference surface are identified in sequence.

[0043] The standard deviation of the elevation values ​​is calculated to obtain the fluctuation, and the ratio of the elevation difference between two adjacent measurement points to the distance between them is calculated to obtain the slope of the measurement point.

[0044] The longitudinal smoothness is calculated by taking the maximum slope, normalizing the undulation and the maximum slope, and then calculating the weighted sum.

[0045] Understandably, by marking measurement points in the image and establishing the transformation relationship between image pixel coordinates and actual three-dimensional coordinates, the elevation values ​​of each point relative to the reference plane can be obtained from the image. It is important to note that in the specific implementation process, camera calibration and reference plane calibration must be combined to convert the two-dimensional image information into three-dimensional spatial coordinates.

[0046] For example, the spacing can be 1 to 2 meters, and the marked measurement points need to ensure that they cover the entire length of the tunnel. The spacing can refer to industry standards, such as the allowable longitudinal deviation of less than or equal to 50 mm per 10m in coal mine tunnels, which can be adjusted according to the type of equipment.

[0047] In one specific embodiment, the specific process of identifying elevation values ​​includes: taking multiple checkerboard images using tools such as OpenCV and MATLAB, calculating intrinsic parameters such as camera focal length and distortion coefficients, recording the pixel coordinates of each measurement point, converting the image pixel coordinates of each measurement point into camera coordinate system coordinates (Xc, Yc, Zc) using camera intrinsic parameters such as the intrinsic parameter matrix and distortion coefficients, and using hand-eye calibration algorithms such as PnP and ICP to deduce the rotation matrix R and translation vector T, setting the design reference plane of the tunnel as the world coordinate system. On the plane, establish the transformation relationship between the camera coordinate system and the world coordinate system. Then, based on the formula... The formula shown That is, the elevation value of the corresponding measurement point relative to the reference surface. and as well as These correspond to the three-dimensional coordinate components in the world coordinate system.

[0048] It should be added that the normalization method for volatility and maximum slope is based on the same principle. Taking volatility as an example, normalization means calculating the relative deviation between volatility and a preset reference volatility. When volatility is less than the preset reference volatility, the relative deviation is assigned a value of 0. Otherwise, the relative deviation is imported into the Sigmoid function to limit the final normalization result to a value range between 0 and 1.

[0049] Understandably, the preset reference fluctuation is based on design specifications or industry standards, selecting an ideal fluctuation threshold for the roadway surface condition, such as the smoothness tolerance range specified in the design drawings. It also relies on statistical analysis of historical monitoring data, taking the average, median, or quantile of the fluctuation under normal operating conditions, such as the upper limit of the 90% confidence interval, as a reference. If real-time calibration conditions exist, the benchmark value can be obtained through initial state calibration, such as the average measured fluctuation value during the acceptance of a newly built roadway. The specific values ​​can be determined according to the actual situation.

[0050] It should also be noted that the weighting of fluctuation and maximum slope follows the principle of prioritizing the impact of slope climbing during rotary propulsion. The specific weighting ratios are derived from the restrictive requirements of the coal mine roadway construction quality acceptance specifications regarding slope abrupt changes and the regression analysis results of multiple sets of roadway deformation data, ensuring that the primary safety risk factor receives a higher weight. For example, for roadways under mining, maximum slope is more critical during rotary propulsion because sudden slope changes can cause difficulties in equipment climbing. Maximum slope has a weight of 0.7, while fluctuation has a weight of 0.3. Furthermore, when rotary mining propels to sections with a radius of curvature less than 200m, the weight of maximum slope can be increased to 0.75, effectively preventing equipment jamming.

[0051] Furthermore, the specific identification process of the lateral levelness includes: taking the roadway design horizontal baseline as the reference, selecting the waistline of the two sides of the roadway or the top surface of the track as the measurement reference surface.

[0052] Cross-sectional images are acquired at predetermined intervals along the longitudinal direction of the tunnel, and based on the cross-sectional images, several measurement points are selected at equal intervals along the transverse direction.

[0053] Identify the elevation values ​​of each measurement point relative to the measurement reference plane, calculate the elevation difference between all adjacent measurement points, and take the ratio of the absolute value of the maximum elevation difference to the actual width of the roadway as the lateral inclination.

[0054] The total number of concave and convex features in the corresponding sub-region image is counted using target recognition technology, and the concave and convex density is obtained by comparing it with the area of ​​the segmented sub-region.

[0055] Connect all the protrusions and depressions in spatial order to generate the boundary polygon of the region with concentrated protrusions and depressions. Calculate the percentage of the area enclosed by the polygon to the area of ​​the original sub-region, and use this as the abnormal area ratio.

[0056] The three indicators of lateral tilt, concavity density, and abnormal area ratio are normalized, and the lateral levelness is obtained by weighted summation of the normalized indicators.

[0057] It should be added that the specific identification process of the elevation value relative to the reference plane is the same as the elevation value identification method involved in longitudinal flatness, and will not be repeated here.

[0058] Understandably, a convex point must simultaneously satisfy the conditions of having a local elevation higher than surrounding continuous points and a deviation exceeding a positive threshold, while a concave point must satisfy the opposite conditions. The positive threshold can be comprehensively set by combining surface smoothness technical indicators in roadway engineering design specifications, statistical analysis of historical monitoring data from similar projects, such as the upper limit of the normal fluctuation range, and the safety margin required for safe production.

[0059] It should be added that the specific processing procedure for normalizing the three indicators of lateral tilt, concavity density and abnormal area ratio is as follows: Take the absolute value of the lateral tilt, set the maximum allowable tilt threshold to 2%, if the actual tilt is less than or equal to 2%, divide the actual value by 2% to obtain the proportional coefficient, if the actual tilt is greater than 2%, directly take the proportional coefficient as 1, and use the proportional coefficient as the normalized tilt indicator.

[0060] The maximum allowable number of bumps per unit area is set to 10 per square meter, and the maximum allowable percentage of abnormal areas is set to 30%. Similarly, the normalized bump density index and the normalized area ratio index are determined in the same way as the normalized slope index.

[0061] It should be added that the threshold settings for indicators related to the lateral levelness of roadways are based on engineering specifications, construction and acceptance requirements, and historical testing data statistics. For example, the 2% threshold for inclination refers to the limit for lateral slope in the coal mine roadway engineering quality acceptance specifications, and the 10 defects / square meter threshold for unevenness density originates from the control standard for the number of defect points per unit area in the acceptance of concrete surface flatness. The 30% threshold for abnormal area ratio is derived from statistical analysis of roadway repair cases; if the defective area accounts for more than 30%, a complete rework is required. Each threshold can be dynamically adjusted according to the roadway type, such as rock / coal roadways, functional zones, etc. The values ​​given are only general examples and are not fixed values.

[0062] Understandably, inclination reflects the overall slope, unevenness density describes the number of local defects, and abnormal area ratio characterizes the degree of defect aggregation. During rotary mining, the equipment is far more sensitive to lateral inclination than in static conditions because centrifugal force exacerbates the risk of sideslip. Meanwhile, the impact of unevenness density cannot be ignored, as vibration can cause chain skipping. While abnormal area ratio is important, its weight can be appropriately reduced under dynamic conditions. That is, in evaluating the lateral levelness of the roadway, the weighting of inclination, unevenness density, and abnormal area ratio follows the principle of prioritizing overlap stability. The weighting coefficient for lateral inclination can be set to 0.6, the weighting coefficient for unevenness density to 0.25, and the weighting coefficient for abnormal area ratio to 0.15. Furthermore, when the working face rotation angle is greater than 35°, the weighting coefficient for inclination increases to 0.70, and when the conveyor chain tension changes abruptly, the weighting coefficient for unevenness density can be increased by 0.1.

[0063] The overlapping change secondary judgment module, when it is determined that there is no change, collects coal flow and conveyor vibration frequency in real time, and combines the operation image to analyze the accuracy of coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough, and makes a secondary judgment on the overlapping angle change.

[0064] It should be added that coal flow can be measured using machine vision-based technologies, such as laser triangulation combined with an industrial camera and a line laser emitter, installed in a direct-shoot, oblique-receive configuration at an angle between 30° and 60° to build a coal flow detection system. The system processes the acquired coal flow images, such as using the HALCON assistant module to calibrate the camera's intrinsic and extrinsic parameters, converting pixel coordinates to world coordinates, and then performing distortion correction. Analytical geometry theorems are used to calibrate the laser plane, obtain image depth information, and then calculate the coal flow cross-section and volume, achieving real-time coal flow acquisition. Alternatively, a coal quantity monitoring system based on dual lidar can be used, with two lidars measuring the contours of the left and right sides of the coal flow separately, constructing a coal flow contour feature point scanning model, calculating the cross-sectional area of ​​the coal flow using the trapezoidal area accumulation method, and calculating the coal quantity based on surface element integration.

[0065] It should be added that vibration frequency acquisition of the transport aircraft can be achieved by installing vibration sensors in key parts of the transport aircraft, such as idlers and drive units. These sensors convert vibration signals into electrical signals. Signal acquisition equipment is used to collect the electrical signals output by the vibration sensors in real time, and the collected data is processed using algorithms such as spectrum analysis to extract vibration frequency information from the collected time-domain vibration signals.

[0066] Specifically, the analysis process for the accuracy of the coal flow landing point includes: B1. Using a high-speed camera to acquire a sequence of coal flow images with timestamps, after preprocessing, edge detection is performed on each frame of the image, the coal flow contour is extracted, and the centroid coordinates are calculated as the image landing point.

[0067] B2. Based on the camera calibration parameters, the image landing point is converted into actual spatial coordinates. If the landing point exceeds the preset expected landing point area, it is marked as an off-frame.

[0068] B3. Calculate the ratio of the total number of deviation frames to the total number of frames to obtain the deviation image ratio, and calculate the ratio of the maximum number of consecutive deviation frames to the total number of deviation frames to obtain the highest continuous deviation ratio. At the same time, calculate the ratio of the total number of deviation frames to the total number of frames in the second half of the acquisition time period to obtain the image deviation influence coefficient.

[0069] B4. The initial coal flow landing point position deviation is obtained by weighted summation of the deviation ratio and the highest continuous deviation ratio, and the final coal flow landing point position deviation is obtained by correcting the deviation using the image deviation influence coefficient.

[0070] B5. If the deviation of the final coal flow landing point is 0, the accuracy of the coal flow landing point is assigned to 1; otherwise, the reciprocal of the deviation of the final coal flow landing point is taken as the accuracy of the coal flow landing point.

[0071] Understandably, preprocessing includes converting the acquired images to grayscale to simplify subsequent image processing. Appropriate filtering algorithms, such as Gaussian filtering, are used to remove noise interference from the image, improving image quality. Image segmentation algorithms are then employed to separate the coal flow from the background, highlighting its outline. The preprocessing methods mentioned are all commonly used existing techniques, and their specific execution processes will not be elaborated upon.

[0072] It should be added that correcting the deviation refers to multiplying the sum of the image deviation influence coefficient and 1 by the initial coal flow landing point deviation, and limiting the maximum value of the final coal flow landing point deviation to 1, so as to ensure the consistency of the data range in subsequent analysis and calculation.

[0073] Understandably, the deviation ratio reflects the prevalence of deviation phenomena in the overall time series. High-frequency deviations usually indicate insufficient system stability. The highest sustained deviation ratio focuses on the relationship between the longest duration of continuous deviations and the total number of deviation frames, used to identify whether there is a persistent and systematic point offset. Compared with scattered deviations, it has a greater risk warning significance. The image deviation impact coefficient uses the middle position of the time series as the boundary, focusing on the statistical proportion of deviation frames in the later stages. This aligns with the pattern in industrial scenarios where factors such as equipment wear and material accumulation may exacerbate deviations over time, highlighting the weight of the impact of later deviations on the long-term operation of the system. The combination of these three factors can comprehensively cover the frequency, persistence, and temporal distribution characteristics of deviations, providing multi-perspective quantitative basis for accurate calculations.

[0074] Specifically, the analysis process of the impact of coal accumulation at the inlet of the receiving trough includes: C1, acquiring images of the receiving trough inlet using an industrial camera, and generating a binary mask of coal accumulation by identifying and segmenting the coal accumulation area using a deep learning algorithm.

[0075] C2. Count the total number of coal accumulation pixels within the mask, calculate the actual area per unit pixel based on camera calibration parameters, extract the three-dimensional contour of the coal accumulation, and generate a cross-sectional contour group by equidistantly cutting along the normal direction perpendicular to the reference plane of the receiving trough.

[0076] C3. Using the reference plane, extract the height component of each cross-section vertex in the accumulation direction as the coal accumulation height.

[0077] C4. Calculate the average stacking height and stacking height fluctuation of all cross sections. The stacking height fluctuation is the standard deviation of the coal stacking height of all cross sections.

[0078] C5. Multiply the total number of coal accumulation pixels, the actual area per pixel, and the average accumulation height to obtain the coal accumulation volume.

[0079] C6. The volume of the coal pile and the ratio of the maximum coal pile height to the depth of the receiving trough are used as risk assessment indicators.

[0080] C7. If the risk assessment index meets the high-risk condition, the coal accumulation impact degree is assigned a value of 1; if it meets the low-risk condition, it is assigned a value of 0; if neither condition is met, the coal accumulation impact compensation coefficient is set based on the real-time coal flow rate and the vibration frequency of the conveyor.

[0081] C8. After normalizing the risk assessment indicators, import them into the Sigmoid function to obtain the output results. Then, compensate the output results using the coal accumulation impact compensation coefficient to obtain the final coal accumulation impact degree at the inlet of the receiving trough.

[0082] Understandably, coal deposits are mostly irregular in shape. Therefore, the volume is calculated by converting the pixel statistics of the coal deposit area with the actual scale. If it is a regular shape, the corresponding geometric volume formula can be used for direct calculation.

[0083] It should be added that the compensation formula is as follows: , The final impact of coal accumulation at the inlet of the receiving hopper. The compensation coefficient for the impact of coal accumulation. This is the output of the Sigmoid function.

[0084] It should be added that using deep learning algorithms to identify and segment coal accumulation areas and generate binary masks of coal accumulation areas is an existing image processing method. For example, a suitable deep learning model for semantic segmentation, such as U-Net or DeepLab, is selected. The model is trained using labeled data and a large number of collected images. After the model is trained, the input real-time image of the tunnel is used to generate a probability map of each pixel belonging to the coal accumulation area through forward propagation. An appropriate threshold, such as 0.5, is set to convert the probability map into a binary image. Then, morphological operations, such as erosion and dilation to remove noise and fill holes, are performed to finally generate an accurate binary mask of coal accumulation areas, thereby achieving accurate identification and segmentation of coal accumulation areas.

[0085] It should also be noted that in a binary coal mask, the pixel values ​​of coal accumulation areas are typically set to 1 or 255, while those of non-coal accumulation areas are set to 0. Then, each pixel in the mask image is iterated over, and each pixel value is checked to see if it is a marker value for a coal accumulation area. If it is a marker value, the count is incremented by 1. Finally, the total number of pixels that meet the criteria is accumulated to obtain the total number of coal accumulation pixels in the mask.

[0086] Understandably, a high-risk condition is when the volume of the coal pile exceeds the preset safe stacking volume or the ratio of the maximum coal pile height to the depth of the receiving trough exceeds the upper limit of the preset safe ratio range. A low-risk condition is when the volume of the coal pile is lower than the set stable transmission coal pile volume and the ratio of the maximum coal pile height to the depth of the receiving trough is lower than the lower limit of the preset ratio range.

[0087] In one specific embodiment, the specific process for normalizing the risk assessment indicators is as follows: the volume of the coal pile is compared with the preset safe stacking volume, and the ratio is used as the normalized result of the coal pile volume; the ratio of the maximum coal pile height to the receiving trough depth is compared with the upper limit of the preset safe ratio range, and the ratio is used as the normalized result of the maximum coal pile height to the receiving trough depth.

[0088] In real-world scenarios, the value of the preset safe stacking volume can be determined with reference to relevant industry standards. For example, for the safe stacking of coal near the receiving trough in underground mines, it can be determined based on the statistical analysis of historical data under similar working conditions, taking into account the volume of the receiving trough, the daily coal output, and the space requirements for ventilation, transportation, and other operations.

[0089] The upper limit of the preset safety ratio range can be determined by simulating the impact of different coal accumulation height to receiving trough depth ratios on the operation of transport equipment and the structural stability of the receiving trough, combined with expert experience and actual risk tolerance. Alternatively, a large amount of past roadway operation data can be collected to analyze the distribution of the maximum coal accumulation height to receiving trough depth ratio when no safety accidents occur, and a suitable quantile, such as the value corresponding to the 95th percentile, can be selected as the upper limit of the preset safety ratio range.

[0090] Furthermore, the specific setting process of the coal accumulation impact compensation coefficient in step C7 includes: calculating the average coal flow rate and the average conveyor vibration frequency. If both are lower than the corresponding preset threshold, the coal accumulation impact compensation coefficient is 0.

[0091] Otherwise, the ratio of the duration during which the coal flow rate continuously exceeds the corresponding preset threshold to the current cumulative collection duration is used as the coal flow rate interference ratio. Similarly, the vibration frequency interference ratio is calculated using the same statistical method as the coal flow rate interference ratio.

[0092] Based on preset weights, the average of the coal flow interference ratio and the vibration frequency interference ratio is used as the compensation coefficient for the impact of coal accumulation.

[0093] For another specific example, please refer to Figure 4 As shown, the determination of the second overlap angle change includes: if either the accuracy of the coal flow drop point or the influence of coal accumulation at the inlet of the receiving trough exceeds the corresponding preset threshold, the overlap angle is changed.

[0094] Otherwise, the overlap angle will be changed if the following conditions are met simultaneously; otherwise, the overlap angle will not be changed. The conditions are as follows: the accuracy of the coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough are both within the critical range of the corresponding preset threshold.

[0095] The current coal flow rate and conveyor vibration frequency both exceed the corresponding preset thresholds.

[0096] It should be added that the accuracy threshold of coal flow landing point can be determined based on the design parameters of the transportation equipment and the material conveying efficiency requirements. The impact threshold of coal accumulation at the inlet of the receiving trough is set in combination with the structural bearing capacity of the receiving trough and the degree of impact of coal accumulation on equipment operation. The coal flow rate threshold is based on the rated conveying capacity of the conveyor and the maximum flow rate value that has not caused blockage or overload in historical operating data. The vibration frequency threshold of the conveyor is set according to the safe operating range provided by the equipment manufacturer and the frequency boundary value of abnormal vibration in historical fault data.

[0097] In this embodiment of the invention, when it is determined that the overlap angle will not be changed, a secondary overlap angle change judgment is made by real-time acquisition of coal flow rate and conveyor vibration frequency, combined with analysis of operational images to determine the accuracy of coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough. This achieves coordinated control of the overlap angle between the coal flow and the equipment. It fully considers the problem that coordinated control of the overlap angle between the coal flow and the equipment can easily lead to coal accumulation in the receiving trough or coal flow deviation, reducing the probability of triggering unstable coal transmission and ensuring normal coal flow transmission and stable equipment operation.

[0098] When the overlap change determination module determines that a change has occurred, it also determines the direction and value of the overlap angle change by comprehensively considering the accuracy of the coal flow landing point and the impact of coal accumulation at the inlet of the receiving trough.

[0099] Specifically, please refer to Figure 5As shown, the specific process for determining the direction of the overlap angle change includes: D1. Obtaining coal flow images through a high-speed camera, using edge detection and centroid calculation to output the three-dimensional coordinate deviation value of the actual landing point relative to the preset ideal landing point, and extracting the horizontal deviation.

[0100] D2. Obtain the coal accumulation area by scanning the inlet of the receiving trough with a laser scanner, and calculate the obstacle level coefficient based on the coal accumulation area and the coal accumulation influence degree at the inlet of the receiving trough.

[0101] D3. If the horizontal deviation and the obstruction level coefficient both exceed the corresponding preset threshold, the angle will be increased as the overlap angle to change the direction.

[0102] D4. If the obstruction level coefficient does not exceed the corresponding preset threshold, the overlap angle will not be changed.

[0103] D5. If the horizontal deviation does not exceed the corresponding preset threshold, but the obstruction level coefficient exceeds the corresponding preset threshold, the angle will be reduced as the direction of the overlap angle change.

[0104] It should be added that the specific statistical process of the obstruction level coefficient includes: dividing the receiving trough area into a core obstruction area, a secondary obstruction area, and an edge influence area; matching the receiving trough area category based on the coal accumulation location area; and extracting the influence weight coefficient under the matched category as the preliminary obstruction weight coefficient.

[0105] If the impact of coal accumulation at the inlet of the receiving trough is greater than or equal to the preset threshold, the obstacle level coefficient is obtained by correcting the impact of coal accumulation at the inlet of the receiving trough through the preliminary obstacle weight coefficient; otherwise, the obstacle level coefficient is set to 0.

[0106] Understandably, the correction of the impact of coal accumulation at the inlet of the receiving trough by the initial obstacle weighting coefficient is the same as the correction of the initial coal flow drop point position deviation, and will not be elaborated further.

[0107] It should be added that the area division is mainly based on the distance from the inlet of the receiving trough. For example, the core obstruction area can be set within 0.5m inside the inlet of the receiving trough, which directly affects the coal flow introduction, and the weight coefficient can be set to 0.5. The secondary obstruction area can be set within 0.5-1.5m outside the inlet, which may cause coal flow deviation, and the weight coefficient can be set to 0.3. The edge influence area can be set in the area beyond 1.5m, which has a smaller impact, and the weight coefficient can be set to 0.2. Moreover, such weight setting is mainly based on coal flow dynamics simulation, and the specific values ​​can be dynamically adjusted according to the actual situation and combined with experience.

[0108] Understandably, when the influence of coal accumulation at the inlet of the receiving hopper is small, even if the position deviates, the obstruction is not significant and does not require special attention. However, when the influence of coal accumulation at the inlet of the receiving hopper is large, the positional influence needs to be given special attention. Therefore, a preliminary obstruction weighting coefficient is used for correction.

[0109] It is also understandable that high-speed cameras can be installed above the receiving chute and at transfer points to ensure that the trajectory of the coal flow can be clearly captured.

[0110] In another specific instance, the specific process for determining the change angle value includes: if the change direction is to increase the angle, obtaining the horizontal deviation of the coal flow landing point, and dividing it by a preset horizontal deviation threshold to obtain the horizontal deviation rate.

[0111] The angle is adjusted based on the horizontal deviation rate, and the current coal flow velocity is obtained in real time. The velocity influence factor is obtained by dividing the velocity by the design rated velocity.

[0112] If the speed influence factor is lower than the preset threshold, the basic adjustment angle is used as the final change angle; otherwise, the basic adjustment angle is corrected by the speed influence factor to obtain the final change angle.

[0113] If the direction is changed and the angle is reduced, the angle is adjusted based on the corresponding basic adjustment based on the obstacle level coefficient, and the current coal quality moisture data is obtained in real time to calculate the coal flow viscosity coefficient.

[0114] The final change angle is obtained by multiplying the basic adjustment angle by the viscosity coefficient of the coal flow.

[0115] In one specific embodiment, the associated horizontal deviation rate value and obstacle level coefficient value of the basic adjustment angle can be set by combining past operation data and experience data. For example, when the horizontal deviation rate is less than or equal to 0%, the basic adjustment angle is set to... When the horizontal deviation rate is greater than 50% and less than or equal to 1, the basic adjustment angle is set to... When the horizontal deviation rate is greater than 100%, the basic adjustment angle is set to... When the coal accumulation obstruction level coefficient is greater than 0.3 and less than or equal to 0.6, the basic adjustment angle is set as follows: When the coal accumulation obstruction level coefficient is greater than 0.6 and less than or equal to 0.9, the basic adjustment angle is set as follows: When the coal accumulation obstruction level coefficient is greater than 0.9, the basic adjustment angle is set as follows: Furthermore, based on mechanical constraints and safety boundary protection, the adjustment angle increment limit is set to [value missing] when the adjustment is increased. When the hour is adjusted, the angle increment limit is set to... .

[0116] The overlap change control terminal controls the overlap mechanism of the transfer machine and the transport machine to perform overlap angle adjustment according to the change angle value.

[0117] This invention, through two judgments on the change of overlap angle, determines the direction and proportion of change by comprehensively considering relevant factors when a change is deemed necessary, and generates the changed overlap angle. This effectively adapts to the dynamic changes in the overlap angle between the transfer machine and the conveyor in rotary mining, solving the problem of coal flow jamming or spillage caused by dynamic angle changes, thus achieving smooth coal flow transmission, reducing coal flow jamming and spillage, and improving the stability of coal transportation.

[0118] 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 and additions should fall within the protection scope of the present invention.

Claims

1. A coal transportation control system for large-angle rotary mining in a fully mechanized longwall face, characterized in that, The system includes: The overlap change judgment module collects the operation images of the transfer machine and the conveyor and identifies the horizontal projection distance between the unloading center and the receiving center and the vertical height difference between the unloading point and the receiving point. It also makes a judgment on the overlap angle change by combining the roadway slope and roadway surface images. The overlap change secondary judgment module, when it is judged that no change is required, collects coal flow and conveyor vibration frequency in real time and combines the operation image to analyze the accuracy of coal flow landing point and the impact of coal accumulation at the inlet of receiving trough, and performs secondary overlap angle change judgment. The overlap change determination module determines the direction and value of the overlap angle change when a change is determined, taking into account the accuracy of the coal flow drop point and the impact of coal accumulation at the inlet of the receiving hopper. The overlap change control terminal controls the overlap mechanism of the transfer machine and the transport machine to adjust the overlap angle according to the changed angle value; The determination of the change in the secondary overlap angle includes: If either the accuracy of the coal flow point or the impact of coal accumulation at the inlet of the receiving hopper exceeds the corresponding preset threshold, the overlap angle will be changed. Otherwise, the overlap angle will change only if the following conditions are met simultaneously; otherwise, the overlap angle will not change. The conditions are as follows: The accuracy of the coal flow landing point and the impact of coal accumulation at the inlet of the receiving hopper are both within the critical range of the corresponding preset thresholds; The current coal flow rate and conveyor vibration frequency both exceed the corresponding preset thresholds.

2. The coal transportation control system for large-angle rotary mining in a fully mechanized longwall face as described in claim 1, characterized in that: The specific analysis process for the accuracy of the coal flow point includes: A high-speed camera was used to acquire a sequence of coal flow images with timestamps. After preprocessing, edge detection was performed on each frame of the image to extract the coal flow contour and calculate the centroid coordinates as the image landing point. Based on camera calibration parameters, the image landing point is converted into actual spatial coordinates. If the landing point exceeds the preset expected landing point area, it is marked as an off-frame. The deviation ratio is obtained by calculating the ratio of the total number of deviation frames to the total number of frames. The maximum continuous deviation ratio is obtained by calculating the ratio of the maximum number of consecutive deviation frames to the total number of deviation frames. At the same time, the image deviation influence coefficient is obtained by calculating the ratio of the total number of deviation frames to the total number of frames in the second half of the acquisition time period. The initial deviation of the coal flow landing point is obtained by weighted summation of the deviation ratio and the highest sustained deviation ratio, and the final deviation of the coal flow landing point is obtained by correcting the deviation using the image deviation influence coefficient. If the deviation of the final coal flow landing point is 0, the accuracy of the coal flow landing point is assigned a value of 1; otherwise, the reciprocal of the deviation of the final coal flow landing point is taken as the accuracy of the coal flow landing point.

3. The coal transportation control system for large-angle rotary mining in a fully mechanized longwall face as described in claim 1, characterized in that: The specific analysis process of the impact of coal accumulation at the inlet of the receiving trough includes: The image of the material receiving trough inlet is captured by an industrial camera, and the coal accumulation area is identified and segmented by a deep learning algorithm to generate a binary mask of coal accumulation. The total number of coal-accumulated pixels within the mask is counted, the actual area per unit pixel is calculated based on camera calibration parameters, and the three-dimensional contour of the coal-accumulated material is extracted. The contours are then cut at equal intervals along the normal direction perpendicular to the reference plane of the receiving trough to generate a set of cross-sectional contours. Using the reference plane, extract the height component of each cross-section vertex in the accumulation direction as the coal accumulation height; Calculate the average stacking height and stacking height fluctuation of all cross sections, where the stacking height fluctuation is the standard deviation of the coal stacking height of all cross sections; The volume of coal accumulation is obtained by multiplying the total number of coal accumulation pixels, the actual area per pixel, and the average accumulation height. The volume of the coal pile and the ratio of the maximum coal pile height to the depth of the receiving trough are used as risk assessment indicators. If the risk assessment index meets the high-risk condition, the coal accumulation impact degree is assigned a value of 1; if it meets the low-risk condition, it is assigned a value of 0; if neither condition is met, the coal accumulation impact compensation coefficient is set based on the real-time coal flow rate and the vibration frequency of the conveyor. After normalizing the risk assessment indicators, they are imported into the Sigmoid function to obtain the output results. The output results are then compensated by the coal accumulation impact compensation coefficient to obtain the final coal accumulation impact degree at the inlet of the receiving trough.

4. The coal transportation control system for large-angle rotary mining in a fully mechanized longwall face as described in claim 3, characterized in that: The specific process for setting the compensation coefficient for the impact of coal accumulation includes: Calculate the average coal flow rate and the average conveyor vibration frequency. If both are lower than the corresponding preset threshold, the coal accumulation impact compensation coefficient is 0. Otherwise, the ratio of the duration during which the coal flow rate continuously exceeds the corresponding preset threshold to the current cumulative collection duration is used as the coal flow rate interference ratio. Similarly, the vibration frequency interference ratio is calculated using the same statistical method as the coal flow rate interference ratio. Based on preset weights, the average of the coal flow interference ratio and the vibration frequency interference ratio is used as the compensation coefficient for the impact of coal accumulation.

5. A coal transportation control system for large-angle rotary mining in a fully mechanized longwall face as described in claim 1, characterized in that: The specific process for determining the direction of the overlap angle change includes: The coal flow image is acquired by a high-speed camera. Edge detection and centroid calculation are used to output the three-dimensional coordinate deviation value of the actual landing point relative to the preset ideal landing point, and the horizontal deviation is extracted. The coal accumulation area is obtained by scanning the inlet of the receiving trough with a laser scanner. The obstruction level coefficient is calculated based on the coal accumulation area and the coal accumulation influence degree at the inlet of the receiving trough. If both the horizontal deviation and the obstruction level coefficient exceed the corresponding preset threshold, the angle will be increased to change the direction of the overlap angle. If the obstruction level coefficient does not exceed the corresponding preset threshold, the tower connection angle will not be changed. If the horizontal deviation does not exceed the corresponding preset threshold, but the obstruction level coefficient exceeds the corresponding preset threshold, the angle will be reduced as the direction of the overlap angle change.

6. The coal transportation control system for large-angle rotary mining in a fully mechanized longwall face as described in claim 5, characterized in that: The specific process for determining the changed angle value includes: If the change of direction is to increase the angle, obtain the horizontal deviation of the coal flow landing point, and divide it by the preset horizontal deviation threshold to obtain the horizontal deviation rate. The angle is adjusted based on the horizontal deviation rate matching, and the current coal flow velocity is obtained in real time. The velocity influence factor is obtained by dividing the velocity by the design rated velocity. If the speed influence factor is lower than the preset threshold, the basic adjustment angle is used as the final change angle; otherwise, the basic adjustment angle is corrected by the speed influence factor to obtain the final change angle. If the direction is changed and the angle is reduced, the angle is adjusted based on the corresponding basic adjustment according to the obstacle level coefficient, and the current coal quality moisture data is obtained in real time to calculate the coal flow viscosity coefficient; The final change angle is obtained by multiplying the basic adjustment angle by the viscosity coefficient of the coal flow.

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