Scraper conveyer conveying capacity calculation method and testing device

Abstract

The invention discloses a scraper conveyor conveying capacity calculation method and a scraper conveyor conveying capacity testing device, and relates to the technical field of coal mine conveying system optimization. Vertical speed distribution data of materials in a conveying groove are collected, and vertical speed distribution characteristics of different heights of a material layer in a scraper conveyor are obtained; dividing the cross section of the conveying groove into a plurality of speed layers according to the speed distribution characteristics, and setting a speed coefficient for each layer; and measuring and recording the material cross sectional area corresponding to each speed layer. According to the method, vertical speed distribution data of materials in a conveying groove are collected, speed characteristics of different height layers are recognized, speed layers are divided, speed coefficients are set, the cross sectional area of each layer is measured in combination with an image recognition or three-dimensional modeling technology, a correction calculation model is constructed, and the actual situation that the internal speed distribution of the materials is not uniform is considered; the idealized hypothesis that materials are regarded as overall uniform-speed motion in a traditional method is broken through, and therefore the accuracy of conveying capacity calculation is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of coal mine conveying system optimization technology, specifically to a method for calculating the conveying capacity of a scraper conveyor and a testing device. Background Technology

[0002] As the core equipment of the continuous conveying system in underground coal mines, the accurate assessment of the conveying capacity of scraper conveyors is directly related to equipment selection, system scheduling, and production efficiency. In coal mine production, scraper conveyors often face complex working conditions such as high accumulation and direct material drop from coal bunkers. The actual flow behavior of materials during the conveying process is affected by a variety of factors. With the development of intelligent and efficient coal mines, accurate control of the operating status of the conveying system has become the key to improving overall production efficiency. Traditional methods for capacity calculation under idealized assumptions are difficult to adapt to the needs of modern coal mines for dynamic scheduling and refined management.

[0003] Traditional methods for calculating conveying capacity assume that the material layer moves as a whole at the scraper speed, thus employing... As a formula for calculating ability, For scraper speed, The cross-sectional area of ​​the material. The method uses material density as an example. However, it does not consider the influence of material accumulation structure on internal flow velocity. Especially under extreme conveying conditions such as direct material drop from coal bunkers and increased coal retaining plate height, the increased accumulation height leads to the actual speed of the upper layer material participating in the conveying being much lower than the scraper speed. Traditional formulas underestimate the impact of this internal velocity distribution on the overall conveying capacity, which in turn leads to selection deviations and production plan imbalances. In recent years, the development of discrete element simulation and multi-source image analysis technology has provided tools to reveal the real flow characteristics of materials during the conveying process. However, existing methods have not yet effectively incorporated them into theoretical models, which restricts the accuracy and engineering applicability of conveying capacity assessment. Therefore, this paper proposes a method for calculating the conveying capacity of scraper conveyors and a testing device to solve the above-mentioned technical problems. Summary of the Invention

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: Firstly, a method for calculating the conveying capacity of a scraper conveyor, comprising the following steps: S1. Collect vertical velocity distribution data of materials in the conveying trough to obtain the vertical velocity distribution characteristics of different heights of the material layer in the scraper conveyor. S2. Based on the velocity distribution characteristics, the cross-section of the conveying trough is divided into several velocity layers, and a velocity coefficient is set for each layer. S3. Using image recognition or 3D modeling technology, measure and record the cross-sectional area of ​​the material corresponding to each velocity layer to ensure that the data covers the entire width of the conveying trough and identify the area ratio of each velocity layer on the cross-section of the conveying trough. S4. Combining the cross-sectional area, velocity coefficient, and material density of each layer, construct a modified calculation model for conveying capacity to calculate the total conveying capacity; S5. Set up a test device to simulate extreme working conditions and collect actual conveying data; S6. Compare the measured conveying volume obtained by the test device with the calculation results of the conveying capacity correction calculation model to verify whether the error is within ±5% and ensure the accuracy of the method.

[0005] Preferably, S1 specifically includes: An observation window is set on the wall of the scraper conveyor trough, and a high-speed camera is installed. The lighting and shooting angle are adjusted to ensure that the movement trajectory of material particles at different heights in the conveyor trough can be clearly and continuously captured. Under stable conveying conditions, a high-speed camera is activated to record the material flow process at a fixed frame rate. The image sequence of the particle group is recorded by timestamps to obtain its displacement information at different vertical positions. By using particle image velocimetry to process image sequences, the average velocity of materials at each height layer is calculated and output by tracking particle displacement and time intervals, thus obtaining the vertical velocity distribution characteristics of material layers at different heights within the scraper conveyor.

[0006] Preferably, S2 specifically includes: Based on the collected vertical velocity distribution characteristics, the cross-section of the conveying trough is divided into several continuous velocity intervals from top to bottom. Each interval represents a velocity layer with similar motion characteristics. The velocity layer includes at least four intervals: 1.0v to 0.8v, 0.8v to 0.6v, 0.6v to 0.4v, and 0.4v to 0.2v. Each defined velocity layer is assigned a corresponding velocity coefficient, which represents the ratio of the average velocity of the material in each velocity layer to the scraper running speed. This coefficient is obtained directly from simulation or measured data. Each velocity layer is associated and matched with its corresponding velocity coefficient to form a complete velocity layer-velocity coefficient mapping relationship, and it is ensured that the velocity layer division matches the actual material stacking structure and has no overlap.

[0007] Preferably, S3 specifically includes: High-speed cameras are arranged in an array along the width of the conveyor trough to capture images of material flow simultaneously. Point cloud data is obtained by combining this with a laser scanner. The geometric model of the material cross-section is reconstructed using 3D modeling software (MeshLab) to ensure full width coverage. Based on the defined velocity layer boundaries, the corresponding regions of each layer are identified and segmented in the geometric model of the material cross-section, the vertical boundaries of each velocity layer are located, and the cross-sectional area of ​​each layer is calculated by polygon fitting to ensure that the data is continuous and without omission. Summarize the area data of each velocity layer, calculate its ratio to the total cross-sectional area of ​​the conveying trough, and verify the consistency between the sum of the areas of all velocity layers and the actual cross-sectional area of ​​the conveying trough.

[0008] Preferably, S4 specifically includes: Integrate the pre-acquired cross-sectional area of ​​each velocity layer, the corresponding velocity coefficient, and the material density data. Normalize the velocity coefficient according to the conveying direction and unify the unit of the material density. Construct a three-dimensional parameter matrix to ensure that all data units are consistent and the format is standardized. Based on the area ratio of each velocity layer on the cross-section of the conveying trough, velocity coefficients (characterizing flow efficiency) are superimposed, and combined with material density and scraper velocity, a conveying capacity correction calculation model is constructed, which is then used to calculate the conveying capacity using the formula. Calculate the total conveying capacity, where Q is the total conveying capacity. This represents the area ratio of each velocity layer on the cross-section of the conveyor trough. Let v be the material density and v be the scraper speed. This is the velocity coefficient.

[0009] Preferably, S5 specifically includes: A testing device was set up, including a test coal bunker, an adjustable coal baffle, and a measuring box. The height of the coal bunker outlet and the baffle were adjusted to simulate the extreme feeding conditions of high accumulation and large drop, so as to ensure the formation of a stable and full material flow in the conveying trough. Keep the scraper speed and feed rate of the scraper conveyor constant. After the conveying process reaches a stable state, use a calibrated measuring box at the tail of the scraper conveyor to collect all output materials at regular intervals and in quantitative quantities. High-precision weighing sensors are used to weigh the materials in the measuring box in real time, and the collection time is recorded synchronously to calculate the actual conveying mass per unit time, which serves as the benchmark measured data to verify the accuracy of the model.

[0010] Preferably, S6 specifically includes: The measured conveying volume obtained by the testing device is synchronized with the calculation results of the conveying capacity correction calculation model in time and aligned with the operating conditions so that the two are under the same operating parameters. The relative error between the measured delivery volume and the model calculation results is calculated for each group, and statistical analysis is performed to confirm the error distribution characteristics and whether there is a systematic deviation. Determine whether the error statistics meet the ±5% tolerance requirement. If they do, the method is confirmed to be accurate; if they do not, the measurement process needs to be checked back or the model parameters need to be corrected.

[0011] A scraper conveyor conveying capacity testing device, applied to the scraper conveyor conveying capacity calculation method described above, includes: The scraper conveyor, which is the main body of the equipment under test, is used to transport the coal flow falling from the coal bunker. The scraper speed, chain speed and other parameters are adjustable. The conveying section is equipped with a transparent window for observing the coal seam structure and accumulation state, which facilitates image acquisition and velocity distribution analysis. The test coal bunker is located above the scraper conveyor to simulate the coal bunker stacking and feeding conditions underground. The coal bunker outlet size is adjustable to ensure a continuous and uniform coal flow, supporting coal sample experiments with different bulk densities, moisture contents and particle sizes. The measuring box, located at the tail of the scraper conveyor, is used to quantitatively collect coal samples during the testing phase. The total amount of material passing through the conveyor per unit time is monitored in real time by a weighing device and compared with the calculation results of the conveying capacity correction calculation model to verify the accuracy of the calculation.

[0012] Preferably, the testing device further includes: a conveying unit, a coal bunker feeding module, an adjustable coal retaining plate, a velocity profile acquisition system, an image processing module, a control calculation module, and an output unit; The conveying unit, as the core actuator of the testing device, is used to simulate the working state of an actual scraper conveyor, to carry and convey materials, and its scraper speed, chain speed and other operating parameters are adjustable. The coal bunker feeding module is used to simulate the feeding conditions of the underground coal bunker. Through the adjustable outlet and flow control mechanism, it forms a continuous, stable and rate-controllable initial coal flow to ensure that the expected accumulation shape and material flow height are formed in the conveying trough. The adjustable coal baffle is used to change the effective volume of the conveying trough and the material accumulation boundary. Its height and angle are adjustable, thereby controlling the filling rate and accumulation structure of the material in the trough. The height of the adjustable coal baffle is twice the conventional value to simulate the extreme full-load condition and test and verify the adaptability and accuracy of the method under extreme conditions. The velocity profile acquisition system is used to capture the motion state of materials during the conveying process, so as to obtain a continuous image sequence of material flow or surface three-dimensional point cloud data, and realize non-destructive measurement of the vertical velocity distribution of materials. The image processing module is used to process the image sequence or surface three-dimensional point cloud data acquired by the velocity profile acquisition system to identify the area of ​​the material layer by region and calculate the conveying capacity in conjunction with the velocity coefficient. The control calculation module is used to coordinate the various actuators to maintain stable operating conditions, and integrates the conveying capacity correction calculation model to calculate the total conveying capacity. At the same time, it has an error comparison function to compare and analyze the model calculation results with the measured conveying volume. The output unit is used to present the final result and output the result to the human-machine interface of the display screen and printer.

[0013] Preferably, the testing device is applicable to different models of scraper conveyors and is portable, wherein the scraper conveyor model is 800mm to 1250mm.

[0014] This invention provides a method for calculating the conveying capacity of a scraper conveyor and a testing device. It has the following beneficial effects: (I) The scraper conveyor conveying capacity calculation method and testing device collects the vertical velocity distribution data of the material in the conveying trough, identifies the velocity characteristics of different height layers, divides the velocity layers, sets the velocity coefficient, and combines image recognition or three-dimensional modeling technology to measure the cross-sectional area of ​​each layer, constructs a corrected calculation model, takes into account the actual situation of uneven velocity distribution inside the material, breaks through the ideal assumption of the traditional method that regards the material as a whole uniform motion, and thus significantly improves the accuracy of conveying capacity calculation.

[0015] (II) This scraper conveyor's conveying capacity calculation method and testing device, through the combined design of an adjustable coal bunker, a high-barrier coal plate, and a flow regulating valve, can simulate extreme feeding conditions such as high accumulation and large drop, while maintaining a constant scraper speed and feeding rate. Under stable conveying conditions, high-speed cameras and weighing sensors are used to collect real-time data on material flow and conveying mass per unit time, covering the entire process from start-up to steady state. This makes the test results closer to actual production scenarios and provides a reliable means for verifying the stability of the conveying system under variable load conditions.

[0016] (III) The scraper conveyor conveying capacity calculation method and testing device acquires the actual conveying volume data in real time through a high-precision weighing sensor and synchronizes the data with the results of the corrected calculation model in time and aligns it with the working conditions. By calculating the relative error group by group and statistically analyzing the error distribution characteristics, the system can determine whether the accuracy of the model meets the ±5% tolerance requirement. If it exceeds the error range, the measurement link is checked back or the model parameters are corrected, forming a closed-loop iterative mechanism of actual measurement-modeling-verification-optimization to ensure the long-term applicability of the calculation method under different working conditions. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the workflow of a scraper conveyor capacity calculation method according to the present invention. Figure 2 This is a schematic flowchart of a method for calculating the conveying capacity of a scraper conveyor according to the present invention; Figure 3 This is a schematic diagram of the material layer velocity distribution in the scraper conveyor of the present invention; Figure 4 This is a schematic diagram of the test device structure of the present invention.

[0018] In the diagram: 1. Test coal bunker; 2. Scraper conveyor; 3. Measuring box; 4. Initial coal flow; 5. Discharged coal flow. 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] Example 1, please refer to Figure 1 , Figure 2 This invention provides a technical solution: a method for calculating the conveying capacity of a scraper conveyor, comprising the following steps: S1. Collect vertical velocity distribution data of materials in the conveying trough, obtain the vertical velocity distribution characteristics of different heights of the material layer in the scraper conveyor, set up observation windows on the wall of the scraper conveyor trough, and install a high-speed camera. Adjust the lighting and shooting angle to ensure that the movement trajectory of material particles in different height layers of the conveying trough can be clearly and continuously captured. Under stable conveying conditions, start the high-speed camera to record the material flow process at a fixed frame rate, record the image sequence of the particle group through timestamps, obtain its displacement information at different vertical positions, use particle image velocimetry to process the image sequence, and calculate and output the average velocity of the material at each height layer by tracking particle displacement and time interval, thereby obtaining the vertical velocity distribution characteristics of different heights of the material layer in the scraper conveyor. The specific work involves: creating dedicated observation windows in the conveyor trough wall and equipping them with high-speed cameras for dynamic capture. The observation windows are made of high-strength transparent material (polycarbonate glass) to withstand the impact and abrasion of the materials while ensuring sufficient light transmission and visibility to clearly display the movement of materials at different heights within the trough. By adjusting the angle and brightness of the lighting system, interference from shadows within the trough is eliminated, ensuring the high-speed camera clearly records the movement trajectories of material particles at different heights. A fixed camera frame rate is maintained during shooting to ensure a precise correspondence between timestamps and particle displacement, thereby acquiring a continuous image sequence. Under stable conveying conditions, the high-speed camera is activated to continuously record the material flow at a preset frame rate. The process involves using timestamps to mark the acquisition time of each image frame, forming a time-series data of particle group displacement. During the shooting process, the operating parameters (scraper speed, feed rate) are kept constant to avoid speed fluctuations caused by external interference. The image sequence covers the entire process of the conveyor from start-up to steady state, ensuring that the speed distribution characteristics reflect the actual conveying state. The operating parameters are recorded synchronously during data storage. The image sequence is processed using particle image velocimetry (PIV) technology. By tracking particle displacement and time intervals, the average speed of each height layer is calculated. The vertical speed of each layer is calculated by partitioning, and the speed distribution curve and statistical values ​​are output. During analysis, the rationality of the speed layer division needs to be verified to ensure that it matches the actual material stacking structure. S2. Based on the velocity distribution characteristics, the cross-section of the conveying trough is divided into several velocity layers, and a velocity coefficient is set for each layer. Based on the collected vertical velocity distribution characteristics, the cross-section of the conveying trough is divided into several continuous velocity intervals from top to bottom. Each interval represents a velocity layer with similar motion characteristics. The velocity layer includes at least four intervals: 1.0v~0.8v, 0.8v~0.6v, 0.6v~0.4v, and 0.4v~0.2v. A corresponding velocity coefficient is assigned to each defined velocity layer. The velocity coefficient represents the ratio of the average velocity of the material in each velocity layer to the scraper running speed. It is directly obtained by combining simulation or measured data. Each velocity layer is associated and matched with its corresponding velocity coefficient to form a complete velocity layer-velocity coefficient mapping relationship, and it is ensured that the velocity layer division matches the actual material stacking structure and has no overlap. The specific work involves: based on the collected vertical velocity distribution characteristics, dividing the cross-section of the conveyor trough into several continuous velocity intervals. Each interval represents a velocity layer with similar motion characteristics. The division ensures clear boundaries for each velocity layer, covering the entire height range from the scraper surface to the top of the material, and includes at least four velocity layers (1.0V~0.8V, 0.8V~0.6V, 0.6V~0.4V, 0.4V~0.2V). Each velocity interval is continuous and non-overlapping. The division is based on high-speed camera measured velocity distribution curves, discrete element simulation results, and material accumulation structure characteristics, ensuring that the velocity layers match the actual material flow state. A corresponding velocity coefficient is assigned to each velocity layer. The velocity coefficient represents the ratio of the average material velocity to the scraper running speed. The velocity coefficient is obtained directly from simulation (EDEM software) or measured data, and needs to be combined with high-speed camera images. The average velocity of each layer is calculated by combining the particle displacement and timestamp. During the correlation matching, it is ensured that the velocity coefficient corresponds one-to-one with the velocity layer to form a complete mapping relationship table. The mapping relationship needs to be verified by statistical validation (variance analysis) to confirm its rationality and avoid coefficient distortion due to deviation in velocity layer division. After completing the velocity layer division and velocity coefficient assignment, the formed velocity layer-velocity coefficient mapping relationship is systematically verified. The verification content includes the rationality of the boundary setting of each velocity layer, the accuracy of the velocity coefficient value, and the degree of matching between the overall mapping relationship and the actual material stacking structure. It is ensured that each velocity layer is continuous and non-overlapping in physical space, completely covers the entire distribution range in velocity value domain, and truly reflects the material flow state in motion characteristic description. During the verification process, the adaptability of the mapping relationship under different working conditions is examined to confirm that it can accurately describe the velocity distribution characteristics of the material in the vertical direction. S3. Using image recognition or 3D modeling technology, measure and record the cross-sectional area of ​​the material corresponding to each velocity layer to ensure that the data covers the entire width of the conveyor trough. Identify the area ratio of each velocity layer on the cross-section of the conveyor trough. Use high-speed cameras arranged in an array along the width of the conveyor trough to capture material flow images simultaneously. Combine this with point cloud data obtained by a laser scanner. Reconstruct the geometric model of the material cross-section using 3D modeling software (MeshLab) to ensure full width coverage. Based on the defined velocity layer boundaries, identify and segment the corresponding regions of each layer in the geometric model of the material cross-section. Locate the vertical boundaries of each velocity layer. Calculate the cross-sectional area of ​​each layer through polygon fitting to ensure continuous and complete data. Summarize the area data of each velocity layer, calculate its ratio to the total cross-sectional area of ​​the conveyor trough, and verify the consistency between the sum of the areas of all velocity layers and the actual cross-sectional area of ​​the conveyor trough to ensure that the data completely covers the width of the trough. The specific work involves: Utilizing a high-speed camera array arranged along the width of the conveyor trough to form a full-width observation network, acquiring continuous image sequences of material flow; and employing a laser scanner to acquire point cloud data of the material surface through non-contact measurement, ensuring a point density ≥ 500 points / cm² to accurately capture surface morphology. The high-speed camera images and laser point cloud data are then imported into 3D modeling software (MeshLab). Image registration and point cloud fusion algorithms are used to reconstruct the geometric model of the material's cross-section. Based on pre-defined velocity layer boundaries, the vertical boundaries of each velocity layer are located in the reconstructed geometric model of the material's cross-section. A polygon fitting algorithm is used to fit the intersection lines between the velocity layers and the material surface, generating closed polygonal regions with smooth boundaries and no sharp corners. The area of ​​the polygonal region corresponding to each velocity layer is calculated using the Gaussian area formula. To ensure calculation accuracy is ≤1%, the overlap of adjacent velocity layer boundaries must be checked during the segmentation process to avoid overlapping or missing areas. All velocity layers must continuously cover the full width of the conveyor trough in the horizontal direction and be consistent with the velocity layer definition in the vertical direction. The cross-sectional area data of each velocity layer is summarized, and its ratio to the total cross-sectional area of ​​the conveyor trough is calculated to generate an area distribution statistics table. The consistency between the sum of the areas of all velocity layers and the actual cross-sectional area of ​​the conveyor trough is verified by weighted summation, with an allowable error range of ≤2%, to confirm data integrity. If the verification fails, the model reconstruction accuracy, velocity layer boundary positioning accuracy, or area calculation method are re-examined. The correlation between the velocity layer area ratio and material flow characteristics is further analyzed to ensure that the area distribution accurately reflects the material accumulation characteristics of different velocity layers, forming a velocity layer area database that covers the full width, is non-overlapping, and has complete data. S4. Combining the cross-sectional area, velocity coefficient, and material density of each layer, a conveying capacity correction calculation model is constructed to calculate the total conveying capacity. This integrates pre-acquired cross-sectional area, corresponding velocity coefficient, and material density data for each velocity layer. The velocity coefficients are normalized according to the conveying direction, and the material density is standardized to a uniform unit. A three-dimensional parameter matrix is ​​constructed, ensuring that all data units are consistent and the format is standardized. Based on the area ratio of each velocity layer on the cross-section of the conveying trough, the velocity coefficient (characterizing flow efficiency) is superimposed. Combined with material density and scraper speed, a conveying capacity correction calculation model is constructed using the formula... Calculate the total conveying capacity, where Q is the total conveying capacity. This represents the area ratio of each velocity layer on the cross-section of the conveyor trough. Let v be the material density and v be the scraper speed. The velocity coefficient; The specific work involves: after completing the division of velocity layers and area measurement, integrating the pre-acquired cross-sectional area of ​​each velocity layer, its corresponding velocity coefficient, and material physical property data, and standardizing all parameters: the velocity coefficient needs to be normalized according to the conveying direction to intuitively represent the relative motion efficiency of each layer; the material density is uniformly converted to standard units, and the area ratio, velocity coefficient, and material density of each velocity layer on the cross-section of the conveying trough are constructed into a structured three-dimensional parameter matrix to ensure that all input data are aligned mathematically, have unified units, and are formatted correctly; based on the integrated standardized data, a conveying capacity correction calculation model is constructed based on the area ratio, velocity coefficient, material density, and scraper speed of each velocity layer on the cross-section of the conveying trough, and the total conveying capacity on the entire cross-section of the conveying trough is analyzed to approximate the actual conveying volume; S5. Set up a test device to simulate extreme working conditions and collect actual conveying data. Set up a test device including a test coal bunker, an adjustable coal baffle, and a measuring box. Adjust the height of the coal bunker outlet and the baffle to simulate extreme feeding conditions with high accumulation and large drop, ensuring a stable and full material flow in the conveying trough. Keep the scraper speed and feeding amount of the scraper conveyor constant. After the conveying process reaches a stable state, use a calibrated measuring box at the tail of the scraper conveyor to collect all output materials at regular intervals and in quantitative quantities. Use a high-precision weighing sensor to weigh the material in the measuring box in real time, record the collection time synchronously, and calculate the actual conveying mass per unit time as the benchmark measured data to verify the accuracy of the model. The specific work involves: constructing a testing device including a test coal bunker, an adjustable retaining plate, and a measuring box. The outlet height of the test coal bunker is controlled by a hydraulic or electric adjustment mechanism. Combined with the adjustable retaining plate (the adjustable range of which must cover the fully loaded state of the conveyor trough), a dynamic drop space is formed. By adjusting the relative height difference between the coal bunker outlet and the adjustable retaining plate (recommended range 0.5-2.0m), the material falling speed and accumulation pattern are controlled to ensure a stable and full material flow in the conveyor trough. Simultaneously, a flow regulating valve is installed at the coal bunker outlet, which, in conjunction with the fine-tuning of the adjustable retaining plate angle (±5°), allows for precise adjustments. o To eliminate material supply fluctuations and maintain the material flow height at 90%-100% of the conveyor trough capacity, the scraper conveyor's scraper speed and material supply should be kept constant. This should be achieved through a frequency converter linked to the screw feeder, ensuring that the material supply rate fluctuation is ≤±2%. Once the conveying process reaches a stable state (continuous operation for over 30 minutes, material flow height fluctuation ≤±3%), a calibrated measuring box (capacity covering 5 minutes of output) should be installed at the tail of the scraper conveyor. The measuring box should employ a quick-opening and closing structure, controlling the material collection time via a pneumatic or electric valve (1-2 minutes per collection session is recommended) to ensure that each collected material represents the output volume within a complete cycle, avoiding... Due to the opening and closing delay causing data deviation, the measuring box and the tail of the conveying trough must be seamlessly connected during the collection process to prevent material spillage. A high-precision weighing sensor (range 0-2000kg, accuracy ±0.1%) is used to weigh the material in the measuring box in real time. The sensor signal is synchronously recorded by the data acquisition system (sampling frequency ≥10Hz) to record the collection time (accurate to 0.1 seconds). The actual conveying mass (kg / s) per unit time is calculated by the ratio of the weighing data to the collection time, which serves as the benchmark measured data to verify the accuracy of the model. To ensure data reliability, 10 sets of valid data are continuously collected for each working condition, and the average value is taken after removing extreme values. S6. Compare the measured conveying volume obtained by the testing device with the calculation results of the conveying capacity correction calculation model to verify whether the error is within ±5% and ensure the accuracy of the method. Synchronize the measured conveying volume obtained by the testing device with the calculation results of the conveying capacity correction calculation model in terms of time and operating conditions, so that the two are under the same operating parameters. Calculate the relative error between the measured conveying volume and the model calculation results group by group, perform statistical analysis, confirm the error distribution characteristics and whether there is a systematic deviation, and determine whether the error statistical results meet the ±5% tolerance requirement. If they meet the requirement, the method is confirmed to be accurate; if they exceed the requirement, the measurement link needs to be checked back or the model parameters need to be corrected. The specific work content is as follows: After the testing device acquires the measured conveying volume, it synchronizes the time and aligns the result with the conveying capacity correction calculation model. For time synchronization, a high-precision clock source (GPS timing module) is used to calibrate the clocks of the data acquisition system and the model calculation program to ensure that their time bases are consistent and to avoid data misalignment due to time deviation. For operating condition alignment, operating parameters, including variables such as scraper speed, feed rate, drop height, and coal retaining plate angle, are matched. These parameters are recorded in real time by the PLC and transmitted to the model calculation terminal to ensure that the model input conditions are exactly the same as the measured operating conditions. After completing the time and operating condition alignment, the relative error between the measured conveying volume and the model calculation result is calculated group by group. Statistical analysis is performed on the error data under all operating conditions, including calculating the average error. Calculate the standard deviation, maximum / minimum error values, and plot the error distribution histogram to identify the error concentration intervals and dispersion. Use the normality test (Shapiro-Wilk test) to determine whether the error follows a random distribution or has a systematic deviation. Based on the error statistics, determine whether the ±5% tolerance requirement is met. If the error mean is close to zero and the 95% confidence interval is within ±5%, and the error distribution has no significant systematic deviation, then the test method and model calculation results are confirmed to be accurate and reliable. If the error exceeds the tolerance range, it is necessary to backtrack and check the measurement links (linearity of the weighing sensor, accuracy of the flow valve control, and synchronization of data acquisition) or model parameters. Locate the main error sources through sensitivity analysis, adjust the model parameters or optimize the measurement system, and retest until the error meets the requirements.

[0021] Example 2, as Figures 1 to 4 As shown, based on Embodiment 1, the present invention also provides a scraper conveyor conveying capacity testing device, applied to the above-mentioned scraper conveyor conveying capacity calculation method, including: Scraper conveyor 2, which is the main body of the device under test, is used to transport the coal flow falling in the coal bunker. The scraper speed, chain speed and other parameters are adjustable. The conveying section is equipped with a transparent window for observing the coal seam structure and accumulation state, which facilitates image acquisition and velocity distribution analysis. Test coal bunker 1, which is set above scraper conveyor 2, is used to simulate the coal bunker stacking and feeding conditions in the mine. The coal bunker outlet size is adjustable to ensure the formation of a continuous and uniform coal flow, and supports coal sample experiments with different bulk densities, moisture contents and particle sizes. The measuring box 3 is located at the tail of the scraper conveyor 2 and is used to quantitatively collect coal samples during the testing phase. The total amount of material passing through the conveyor per unit time is monitored in real time by a weighing device and compared with the calculation results of the conveying capacity correction calculation model to verify the accuracy of the calculation. During the test, the coal flow first falls freely from the test coal bunker 1 to form the initial coal flow 4. Under the action of gravity, the initial coal flow 4 naturally accumulates in the conveying trough of the scraper conveyor 2 and is horizontally conveyed by the scraper of the scraper conveyor 2. As the scraper moves, the initial coal flow 4 is conveyed to the end to form the discharge coal flow 5, and finally falls into the measuring box 3 to complete the collection of the conveying volume. The state changes of the two coal flows reflect the velocity stratification characteristics of the initial accumulation state and the conveying process, respectively. The initial coal flow 4 forms different pile angles and particle distributions during the accumulation process, while the continuity and falling speed of the discharged coal flow 5 can be used as important parameters of the scraper conveying efficiency. By taking high-frequency images of the discharged coal flow 5 and combining them with timestamp analysis, the average particle speed and intermittent conveying rhythm can be effectively extracted, thereby verifying the rationality and dynamic response capability of the conveying capacity correction calculation model. The testing device also includes: a conveying unit, a coal bunker feeding module, an adjustable coal retaining plate, a velocity profile acquisition system, an image processing module, a control calculation module, and an output unit; Among them, the conveying unit, as the core actuator of the test device, is used to simulate the working state of the actual scraper conveyor 2, to carry and convey materials. Its scraper speed, chain speed and other operating parameters are adjustable to match different test conditions and provide a real and controllable material conveying environment. The coal bunker feeding module is used to simulate the feeding conditions of underground coal bunkers. Through the adjustable outlet and flow control mechanism, it forms a continuous, stable and rate-controllable initial coal flow 4, ensuring that the expected accumulation shape and material flow height are formed in the conveying trough. It can accurately reproduce key working conditions such as high accumulation and continuous feeding, and provide a stable and reliable material source for testing. Adjustable coal baffles are used to change the effective volume of the conveying trough and the material accumulation boundary. Their height and angle are adjustable, thereby controlling the filling rate and accumulation structure of the material in the trough. The height of the adjustable coal baffles is twice the conventional value to simulate extreme full-load conditions and test and verify the adaptability and accuracy of the method under extreme conditions. The velocity profile acquisition system is used to capture the motion state of materials during the conveying process. It is used by high-speed cameras or simulation modeling systems to obtain continuous image sequences of material flow or surface three-dimensional point cloud data, so as to realize non-destructive measurement of the vertical velocity distribution of materials. The image processing module is used to process the image sequence or surface three-dimensional point cloud data acquired by the velocity profile acquisition system, including image registration, particle tracking, velocity calculation, three-dimensional model reconstruction, and automatic identification and calculation of the cross-sectional area of ​​each velocity layer, so as to identify the area of ​​the material layer in zones and calculate the conveying capacity in conjunction with the velocity coefficient. The control calculation module is used to coordinate various actuators to maintain stable operating conditions and integrates a conveying capacity correction calculation model to calculate the total conveying capacity. At the same time, it has an error comparison function to compare and analyze the model calculation results with the measured conveying volume, thereby realizing automated control of the testing process, application of model calculations, and preliminary verification of results, improving testing efficiency and intelligence level. The output unit is used to present the final results and output the results to the human-machine interface of the display screen and printer. At the same time, it directly transmits the corrected total conveying capacity data to the data interface of the upper-level intelligent scheduling system, so that the test results are visualized, recordable and usable. In addition, the testing device is applicable to different models of scraper conveyors 2 and is portable, wherein the scraper conveyor 2 has a model of 800mm to 1250mm.

[0022] Example 3, as Figures 1 to 4 As shown, based on Examples 1-2, this invention provides an example: taking an SGB800 scraper conveyor as an example, the scraper speed is set to 1.2 m / s. EDEM simulation software is used to model the material accumulation structure and motion state, dividing the material cross-section into four vertical velocity regions, corresponding to the following velocity ranges: S1 region (1.0v~0.8v), S2 region (0.8v~0.6v), S3 region (0.6v~0.4v), and S4 region (0.4v~0.2v). The area ratio of each velocity layer on the cross-section of the conveyor trough is obtained from the simulation data, which are: S1 = 0.603 m². 2 S2=0.261m 2 S3=0.257m 2 S4=0.781m 2 Corresponding speed coefficient The values ​​are 1.0, 0.8, 0.6, and 0.4 respectively. The material density is set to 850 kg / m³. Substituting these values ​​into the corrected model, the conveying capacity is calculated as: Q = 850 × [0.603 × 1 + 0.261 × 0.8 + 0.257 × 0.6 + 0.781 × 0.4] × 1.2 ≈ 4179.91 kg / h.

[0023] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0024] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the conveying capacity of a scraper conveyor, characterized in that, Includes the following steps: S1. Collect vertical velocity distribution data of materials in the conveying trough to obtain the vertical velocity distribution characteristics of different heights of the material layer in the scraper conveyor. S2. Based on the velocity distribution characteristics, the cross-section of the conveying trough is divided into several velocity layers, and a velocity coefficient is set for each layer. S3. Measure and record the cross-sectional area of ​​the material corresponding to each velocity layer, and identify the area ratio of each velocity layer on the cross-section of the conveying trough. S4. Combining the cross-sectional area, velocity coefficient, and material density of each layer, construct a modified calculation model for conveying capacity to calculate the total conveying capacity; S5. Set up a test device to simulate extreme working conditions and collect actual conveying data; S6. Compare the measured conveying volume obtained by the test device with the calculation results of the conveying capacity correction calculation model to verify whether the error is within ±5%.

2. The method for calculating the conveying capacity of a scraper conveyor according to claim 1, characterized in that: S1 specifically includes: An observation window is set on the wall of the scraper conveyor trough, and a high-speed camera is installed. The lighting and shooting angle are adjusted to continuously capture the movement trajectory of material particles at different heights in the conveyor trough. Under stable conveying conditions, a high-speed camera is activated to record the material flow process at a fixed frame rate. The image sequence of the particle group is recorded by timestamps to obtain its displacement information at different vertical positions. By using particle image velocimetry to process image sequences, the average velocity of materials at each height layer is calculated and output by tracking particle displacement and time intervals, thus obtaining the vertical velocity distribution characteristics of material layers at different heights within the scraper conveyor.

3. The method for calculating the conveying capacity of a scraper conveyor according to claim 1, characterized in that: S2 specifically includes: Based on the collected vertical velocity distribution characteristics, the cross-section of the conveying trough is divided into several continuous velocity intervals from top to bottom. Each interval represents a velocity layer with similar motion characteristics. The velocity layer includes at least four intervals: 1.0v to 0.8v, 0.8v to 0.6v, 0.6v to 0.4v, and 0.4v to 0.2v. Each defined speed layer is assigned a corresponding speed coefficient, which represents the ratio of the average material speed in each speed layer to the scraper running speed. Each velocity layer is associated and matched with its corresponding velocity coefficient to form a complete velocity layer-velocity coefficient mapping relationship.

4. The method for calculating the conveying capacity of a scraper conveyor according to claim 1, characterized in that: S3 specifically includes: High-speed cameras are arrayed along the width of the conveying trough to capture images of material flow simultaneously. Point cloud data is obtained by combining this with a laser scanner, and the geometric model of the material cross-section is reconstructed using 3D modeling software. Based on the defined velocity layer boundaries, the regions corresponding to each layer are identified and segmented in the geometric model of the material cross-section, the vertical boundaries of each velocity layer are located, and the cross-sectional area of ​​each layer is calculated by polygon fitting. Summarize the area data of each velocity layer, calculate its ratio to the total cross-sectional area of ​​the conveying trough, and verify the consistency between the sum of the areas of all velocity layers and the actual cross-sectional area of ​​the conveying trough.

5. The method for calculating the conveying capacity of a scraper conveyor according to claim 1, characterized in that: S4 specifically includes: By integrating the pre-acquired cross-sectional area of ​​each velocity layer, the corresponding velocity coefficient, and the material density data, the velocity coefficient is normalized according to the conveying direction, the material density is standardized to a uniform unit, and a three-dimensional parameter matrix is ​​constructed. Based on the area ratio of each velocity layer on the cross-section of the conveying trough, a velocity coefficient is superimposed, and combined with material density and scraper speed, a conveying capacity correction calculation model is constructed, which is then used to calculate the conveying capacity using the formula. Calculate the total conveying capacity, where Q is the total conveying capacity. This represents the area ratio of each velocity layer on the cross-section of the conveyor trough. Let v be the material density and v be the scraper speed. This is the velocity coefficient.

6. The method for calculating the conveying capacity of a scraper conveyor according to claim 5, characterized in that: S5 specifically includes: A testing device was set up, including a test coal bunker, an adjustable coal baffle, and a measuring box. The height of the coal bunker outlet and the baffle were adjusted to simulate the extreme feeding conditions of high stacking and large drop. Keep the scraper speed and feed rate of the scraper conveyor constant. After the conveying process reaches a stable state, use a calibrated measuring box at the tail of the scraper conveyor to collect all output materials at regular intervals and in quantitative quantities. High-precision weighing sensors are used to weigh the materials in the measuring box in real time, and the collection time is recorded synchronously to calculate the actual conveying mass per unit time, which serves as the benchmark measured data to verify the accuracy of the model.

7. The method for calculating the conveying capacity of a scraper conveyor according to claim 1, characterized in that: S6 specifically includes: The measured conveying volume obtained by the testing device is synchronized with the calculation results of the conveying capacity correction calculation model in time and aligned with the operating conditions so that the two are under the same operating parameters. The relative error between the measured delivery volume and the model calculation results is calculated for each group, and statistical analysis is performed to confirm the error distribution characteristics and whether there is a systematic deviation. Determine whether the error statistics meet the ±5% tolerance requirement. If they do, the method is confirmed to be accurate; if they do not, the measurement process needs to be checked back or the model parameters need to be corrected.

8. A scraper conveyor conveying capacity testing device, applied to the scraper conveyor conveying capacity calculation method according to any one of claims 1-7, characterized in that, include: The scraper conveyor (2) is the main body of the equipment to be tested. It is used to transport the coal flow falling in the coal bunker. The conveying section is equipped with a transparent window for observing the coal seam structure and accumulation state. Test coal bunker (1), which is set above scraper conveyor (2), is used to simulate the coal bunker stacking and feeding conditions in the mine. The coal bunker outlet size is adjustable. The measuring box (3) is installed at the tail of the scraper conveyor (2) to collect coal samples quantitatively during the testing phase. The total amount of material passing through the conveyor per unit time is monitored in real time by the weighing device and compared with the calculation results of the conveying capacity correction calculation model to verify the accuracy of the calculation.

9. The scraper conveyor conveying capacity testing device according to claim 8, characterized in that: The testing device also includes: a conveying unit, a coal bunker feeding module, an adjustable coal baffle, a velocity profile acquisition system, an image processing module, a control calculation module, and an output unit; The conveying unit is used to simulate the working state of an actual scraper conveyor (2) to carry and convey materials; The coal bunker feeding module is used to simulate the feeding conditions of the underground coal bunker and form a continuous, stable and rate-controllable initial coal flow through an adjustable outlet and flow control mechanism (4). The adjustable coal baffle is used to change the effective volume of the conveying trough and the material accumulation boundary. Its height and angle are adjustable, thereby controlling the filling rate and accumulation structure of the material in the trough. The height of the adjustable coal baffle is twice the conventional value to simulate the extreme full load condition. The velocity profile acquisition system is used to capture the motion state of materials during the conveying process in order to obtain a continuous image sequence of material flow or surface three-dimensional point cloud data. The image processing module is used to process the image sequence or surface three-dimensional point cloud data acquired by the velocity profile acquisition system to identify the area of ​​the material layer by region and calculate the conveying capacity in conjunction with the velocity coefficient. The control calculation module is used to coordinate the various actuators to maintain stable operating conditions, and integrates the conveying capacity correction calculation model to calculate the total conveying capacity. At the same time, it has an error comparison function to compare and analyze the model calculation results with the measured conveying volume. The output unit is used to present the final result and output the result to the human-machine interface of the display screen and printer.

10. The scraper conveyor conveying capacity testing device according to claim 8, characterized in that: The testing device is applicable to different models of scraper conveyors (2) and is portable. The scraper conveyor (2) has a model of 800mm to 1250mm.

Images